sobremesa.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium\n",
    "from shapely.ops import cascaded_union\n",
    "from folium import Marker, PolyLine\n",
    "from folium.plugins import HeatMap, HeatMapWithTime, MarkerCluster\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import Point, LineString\n",
    "TURK_LAT = 39.0618\n",
    "TURK_LNG = 33.7500\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px\n",
    "import seaborn as sns\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "utf_16 :\n",
      "    ID                DATE_            LOCATION_      LAT      LNG  MAG  DEPTH  \\\n",
      "0   1  2005-01-01 00:29:42  KORKUTELi (ANTALYA)  36.9197  30.3133  2.9   30.0   \n",
      "1   2  2005-01-01 03:03:40        YUNAK (KONYA)  38.8177  31.8875  3.5    5.8   \n",
      "2   3  2005-01-01 04:40:14              AKDENiZ  36.1153  28.4915  3.5   74.5   \n",
      "3   4  2005-01-01 09:35:00       CUBUK (ANKARA)  40.3485  32.9603  3.0   15.1   \n",
      "4   5  2005-01-01 11:17:43      MENEMEN (iZMiR)  38.8013  27.2075  2.9   28.3   \n",
      "\n",
      "                      RECORDDATE  \n",
      "0  2023-02-27 15:01:52.367000000  \n",
      "1  2023-02-27 15:01:52.367000000  \n",
      "2  2023-02-27 15:01:52.367000000  \n",
      "3  2023-02-27 15:01:52.367000000  \n",
      "4  2023-02-27 15:01:52.367000000  \n"
     ]
    }
   ],
   "source": [
    "\n",
    "encoding_list = ['ascii', 'big5', 'big5hkscs', 'cp037', 'cp273', 'cp424', 'cp437', 'cp500', 'cp720', 'cp737'\n",
    "                 , 'cp775', 'cp850', 'cp852', 'cp855', 'cp856', 'cp857', 'cp858', 'cp860', 'cp861', 'cp862'\n",
    "                 , 'cp863', 'cp864', 'cp865', 'cp866', 'cp869', 'cp874', 'cp875', 'cp932', 'cp949', 'cp950'\n",
    "                 , 'cp1006', 'cp1026', 'cp1125', 'cp1140', 'cp1250', 'cp1251', 'cp1252', 'cp1253', 'cp1254'\n",
    "                 , 'cp1255', 'cp1256', 'cp1257', 'cp1258', 'euc_jp', 'euc_jis_2004', 'euc_jisx0213', 'euc_kr'\n",
    "                 , 'gb2312', 'gbk', 'gb18030', 'hz', 'iso2022_jp', 'iso2022_jp_1', 'iso2022_jp_2'\n",
    "                 , 'iso2022_jp_2004', 'iso2022_jp_3', 'iso2022_jp_ext', 'iso2022_kr', 'latin_1', 'iso8859_2'\n",
    "                 , 'iso8859_3', 'iso8859_4', 'iso8859_5', 'iso8859_6', 'iso8859_7', 'iso8859_8', 'iso8859_9'\n",
    "                 , 'iso8859_10', 'iso8859_11', 'iso8859_13', 'iso8859_14', 'iso8859_15', 'iso8859_16', 'johab'\n",
    "                 , 'koi8_r', 'koi8_t', 'koi8_u', 'kz1048', 'mac_cyrillic', 'mac_greek', 'mac_iceland', 'mac_latin2'\n",
    "                 , 'mac_roman', 'mac_turkish', 'ptcp154', 'shift_jis', 'shift_jis_2004', 'shift_jisx0213', 'utf_32'\n",
    "                 , 'utf_32_be', 'utf_32_le', 'utf_16']\n",
    "\n",
    "for encoding in encoding_list:\n",
    "    worked = True\n",
    "    try:\n",
    "        df = pd.read_csv(\"eq20.csv\", encoding=encoding, nrows=5)\n",
    "    except:\n",
    "        worked = False\n",
    "    if worked and str(df[df.columns[0]][0]) != \"nan\":\n",
    "        print(encoding, ':\\n', df.head())\n",
    "        break\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "b'Skipping line 114421: expected 8 fields, saw 9\\nSkipping line 115729: expected 8 fields, saw 9\\nSkipping line 117563: expected 8 fields, saw 9\\nSkipping line 118716: expected 8 fields, saw 9\\nSkipping line 127421: expected 8 fields, saw 9\\nSkipping line 128142: expected 8 fields, saw 9\\n'\n",
      "b'Skipping line 137960: expected 8 fields, saw 9\\nSkipping line 138066: expected 8 fields, saw 9\\nSkipping line 139689: expected 8 fields, saw 9\\nSkipping line 140753: expected 8 fields, saw 9\\nSkipping line 141426: expected 8 fields, saw 9\\nSkipping line 142841: expected 8 fields, saw 9\\nSkipping line 142844: expected 8 fields, saw 9\\nSkipping line 142846: expected 8 fields, saw 9\\nSkipping line 144861: expected 8 fields, saw 9\\nSkipping line 145582: expected 8 fields, saw 9\\nSkipping line 146689: expected 8 fields, saw 9\\nSkipping line 149056: expected 8 fields, saw 9\\nSkipping line 150251: expected 8 fields, saw 9\\nSkipping line 152718: expected 8 fields, saw 9\\nSkipping line 154023: expected 8 fields, saw 9\\nSkipping line 154171: expected 8 fields, saw 9\\nSkipping line 155132: expected 8 fields, saw 9\\nSkipping line 159717: expected 8 fields, saw 9\\nSkipping line 161472: expected 8 fields, saw 9\\nSkipping line 161542: expected 8 fields, saw 9\\nSkipping line 163838: expected 8 fields, saw 9\\nSkipping line 166821: expected 8 fields, saw 9\\nSkipping line 171306: expected 8 fields, saw 9\\nSkipping line 176724: expected 8 fields, saw 9\\nSkipping line 179671: expected 8 fields, saw 9\\nSkipping line 189437: expected 8 fields, saw 9\\n'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>DATE_</th>\n",
       "      <th>LOCATION_</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LNG</th>\n",
       "      <th>MAG</th>\n",
       "      <th>DEPTH</th>\n",
       "      <th>RECORDDATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2005-01-01 00:29:42</td>\n",
       "      <td>KORKUTELi (ANTALYA)</td>\n",
       "      <td>36.9197</td>\n",
       "      <td>30.3133</td>\n",
       "      <td>2.9</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2005-01-01 03:03:40</td>\n",
       "      <td>YUNAK (KONYA)</td>\n",
       "      <td>38.8177</td>\n",
       "      <td>31.8875</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2005-01-01 04:40:14</td>\n",
       "      <td>AKDENiZ</td>\n",
       "      <td>36.1153</td>\n",
       "      <td>28.4915</td>\n",
       "      <td>3.5</td>\n",
       "      <td>74.5</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2005-01-01 09:35:00</td>\n",
       "      <td>CUBUK (ANKARA)</td>\n",
       "      <td>40.3485</td>\n",
       "      <td>32.9603</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2005-01-01 11:17:43</td>\n",
       "      <td>MENEMEN (iZMiR)</td>\n",
       "      <td>38.8013</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>2.9</td>\n",
       "      <td>28.3</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284578</th>\n",
       "      <td>284611</td>\n",
       "      <td>2023-02-18 21:57:48</td>\n",
       "      <td>KARAHASANUSAGI-ELBISTAN (KAHRAMANMARAS)       ...</td>\n",
       "      <td>38.1273</td>\n",
       "      <td>37.5453</td>\n",
       "      <td>3.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284579</th>\n",
       "      <td>284612</td>\n",
       "      <td>2023-02-26 06:38:19</td>\n",
       "      <td>UMUTLU-NURHAK (KAHRAMANMARAS)                 ...</td>\n",
       "      <td>37.8832</td>\n",
       "      <td>37.2213</td>\n",
       "      <td>2.1</td>\n",
       "      <td>8.2</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284580</th>\n",
       "      <td>284613</td>\n",
       "      <td>2023-02-26 07:13:10</td>\n",
       "      <td>TURKIYE-IRAN SINIR BOLGESI                    ...</td>\n",
       "      <td>38.5592</td>\n",
       "      <td>44.8275</td>\n",
       "      <td>2.5</td>\n",
       "      <td>8.9</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284581</th>\n",
       "      <td>284614</td>\n",
       "      <td>2023-02-26 07:30:34</td>\n",
       "      <td>YAYLA-VARTO (MUS)                             ...</td>\n",
       "      <td>39.0577</td>\n",
       "      <td>41.2510</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284582</th>\n",
       "      <td>284615</td>\n",
       "      <td>2023-02-26 07:39:48</td>\n",
       "      <td>YENIKOY-EKINOZU (KAHRAMANMARAS)               ...</td>\n",
       "      <td>38.0267</td>\n",
       "      <td>37.1017</td>\n",
       "      <td>2.6</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>284583 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ID                DATE_  \\\n",
       "0            1  2005-01-01 00:29:42   \n",
       "1            2  2005-01-01 03:03:40   \n",
       "2            3  2005-01-01 04:40:14   \n",
       "3            4  2005-01-01 09:35:00   \n",
       "4            5  2005-01-01 11:17:43   \n",
       "...        ...                  ...   \n",
       "284578  284611  2023-02-18 21:57:48   \n",
       "284579  284612  2023-02-26 06:38:19   \n",
       "284580  284613  2023-02-26 07:13:10   \n",
       "284581  284614  2023-02-26 07:30:34   \n",
       "284582  284615  2023-02-26 07:39:48   \n",
       "\n",
       "                                                LOCATION_      LAT      LNG  \\\n",
       "0                                     KORKUTELi (ANTALYA)  36.9197  30.3133   \n",
       "1                                           YUNAK (KONYA)  38.8177  31.8875   \n",
       "2                                                 AKDENiZ  36.1153  28.4915   \n",
       "3                                          CUBUK (ANKARA)  40.3485  32.9603   \n",
       "4                                         MENEMEN (iZMiR)  38.8013  27.2075   \n",
       "...                                                   ...      ...      ...   \n",
       "284578  KARAHASANUSAGI-ELBISTAN (KAHRAMANMARAS)       ...  38.1273  37.5453   \n",
       "284579  UMUTLU-NURHAK (KAHRAMANMARAS)                 ...  37.8832  37.2213   \n",
       "284580  TURKIYE-IRAN SINIR BOLGESI                    ...  38.5592  44.8275   \n",
       "284581  YAYLA-VARTO (MUS)                             ...  39.0577  41.2510   \n",
       "284582  YENIKOY-EKINOZU (KAHRAMANMARAS)               ...  38.0267  37.1017   \n",
       "\n",
       "        MAG  DEPTH                     RECORDDATE  \n",
       "0       2.9   30.0  2023-02-27 15:01:52.367000000  \n",
       "1       3.5    5.8  2023-02-27 15:01:52.367000000  \n",
       "2       3.5   74.5  2023-02-27 15:01:52.367000000  \n",
       "3       3.0   15.1  2023-02-27 15:01:52.367000000  \n",
       "4       2.9   28.3  2023-02-27 15:01:52.367000000  \n",
       "...     ...    ...                            ...  \n",
       "284578  3.2    5.0  2023-02-27 15:02:29.527000000  \n",
       "284579  2.1    8.2  2023-02-27 15:02:29.527000000  \n",
       "284580  2.5    8.9  2023-02-27 15:02:29.527000000  \n",
       "284581  2.6    8.5  2023-02-27 15:02:29.527000000  \n",
       "284582  2.6    3.8  2023-02-27 15:02:29.527000000  \n",
       "\n",
       "[284583 rows x 8 columns]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"eq20.csv\", encoding=encoding, error_bad_lines=False)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE_</th>\n",
       "      <th>LOCATION_</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LNG</th>\n",
       "      <th>MAG</th>\n",
       "      <th>DEPTH</th>\n",
       "      <th>RECORDDATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005-01-01 00:29:42</td>\n",
       "      <td>KORKUTELi (ANTALYA)</td>\n",
       "      <td>36.9197</td>\n",
       "      <td>30.3133</td>\n",
       "      <td>2.9</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005-01-01 03:03:40</td>\n",
       "      <td>YUNAK (KONYA)</td>\n",
       "      <td>38.8177</td>\n",
       "      <td>31.8875</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005-01-01 04:40:14</td>\n",
       "      <td>AKDENiZ</td>\n",
       "      <td>36.1153</td>\n",
       "      <td>28.4915</td>\n",
       "      <td>3.5</td>\n",
       "      <td>74.5</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005-01-01 09:35:00</td>\n",
       "      <td>CUBUK (ANKARA)</td>\n",
       "      <td>40.3485</td>\n",
       "      <td>32.9603</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005-01-01 11:17:43</td>\n",
       "      <td>MENEMEN (iZMiR)</td>\n",
       "      <td>38.8013</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>2.9</td>\n",
       "      <td>28.3</td>\n",
       "      <td>2023-02-27 15:01:52.367000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284578</th>\n",
       "      <td>2023-02-18 21:57:48</td>\n",
       "      <td>KARAHASANUSAGI-ELBISTAN (KAHRAMANMARAS)       ...</td>\n",
       "      <td>38.1273</td>\n",
       "      <td>37.5453</td>\n",
       "      <td>3.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284579</th>\n",
       "      <td>2023-02-26 06:38:19</td>\n",
       "      <td>UMUTLU-NURHAK (KAHRAMANMARAS)                 ...</td>\n",
       "      <td>37.8832</td>\n",
       "      <td>37.2213</td>\n",
       "      <td>2.1</td>\n",
       "      <td>8.2</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284580</th>\n",
       "      <td>2023-02-26 07:13:10</td>\n",
       "      <td>TURKIYE-IRAN SINIR BOLGESI                    ...</td>\n",
       "      <td>38.5592</td>\n",
       "      <td>44.8275</td>\n",
       "      <td>2.5</td>\n",
       "      <td>8.9</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284581</th>\n",
       "      <td>2023-02-26 07:30:34</td>\n",
       "      <td>YAYLA-VARTO (MUS)                             ...</td>\n",
       "      <td>39.0577</td>\n",
       "      <td>41.2510</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284582</th>\n",
       "      <td>2023-02-26 07:39:48</td>\n",
       "      <td>YENIKOY-EKINOZU (KAHRAMANMARAS)               ...</td>\n",
       "      <td>38.0267</td>\n",
       "      <td>37.1017</td>\n",
       "      <td>2.6</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2023-02-27 15:02:29.527000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>284583 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      DATE_  \\\n",
       "0       2005-01-01 00:29:42   \n",
       "1       2005-01-01 03:03:40   \n",
       "2       2005-01-01 04:40:14   \n",
       "3       2005-01-01 09:35:00   \n",
       "4       2005-01-01 11:17:43   \n",
       "...                     ...   \n",
       "284578  2023-02-18 21:57:48   \n",
       "284579  2023-02-26 06:38:19   \n",
       "284580  2023-02-26 07:13:10   \n",
       "284581  2023-02-26 07:30:34   \n",
       "284582  2023-02-26 07:39:48   \n",
       "\n",
       "                                                LOCATION_      LAT      LNG  \\\n",
       "0                                     KORKUTELi (ANTALYA)  36.9197  30.3133   \n",
       "1                                           YUNAK (KONYA)  38.8177  31.8875   \n",
       "2                                                 AKDENiZ  36.1153  28.4915   \n",
       "3                                          CUBUK (ANKARA)  40.3485  32.9603   \n",
       "4                                         MENEMEN (iZMiR)  38.8013  27.2075   \n",
       "...                                                   ...      ...      ...   \n",
       "284578  KARAHASANUSAGI-ELBISTAN (KAHRAMANMARAS)       ...  38.1273  37.5453   \n",
       "284579  UMUTLU-NURHAK (KAHRAMANMARAS)                 ...  37.8832  37.2213   \n",
       "284580  TURKIYE-IRAN SINIR BOLGESI                    ...  38.5592  44.8275   \n",
       "284581  YAYLA-VARTO (MUS)                             ...  39.0577  41.2510   \n",
       "284582  YENIKOY-EKINOZU (KAHRAMANMARAS)               ...  38.0267  37.1017   \n",
       "\n",
       "        MAG  DEPTH                     RECORDDATE  \n",
       "0       2.9   30.0  2023-02-27 15:01:52.367000000  \n",
       "1       3.5    5.8  2023-02-27 15:01:52.367000000  \n",
       "2       3.5   74.5  2023-02-27 15:01:52.367000000  \n",
       "3       3.0   15.1  2023-02-27 15:01:52.367000000  \n",
       "4       2.9   28.3  2023-02-27 15:01:52.367000000  \n",
       "...     ...    ...                            ...  \n",
       "284578  3.2    5.0  2023-02-27 15:02:29.527000000  \n",
       "284579  2.1    8.2  2023-02-27 15:02:29.527000000  \n",
       "284580  2.5    8.9  2023-02-27 15:02:29.527000000  \n",
       "284581  2.6    8.5  2023-02-27 15:02:29.527000000  \n",
       "284582  2.6    3.8  2023-02-27 15:02:29.527000000  \n",
       "\n",
       "[284583 rows x 7 columns]"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(columns=[\"ID\"],axis=1,inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 284583 entries, 0 to 284582\n",
      "Data columns (total 7 columns):\n",
      " #   Column      Non-Null Count   Dtype  \n",
      "---  ------      --------------   -----  \n",
      " 0   DATE_       284583 non-null  object \n",
      " 1   LOCATION_   284583 non-null  object \n",
      " 2   LAT         284583 non-null  float64\n",
      " 3   LNG         284583 non-null  float64\n",
      " 4   MAG         284583 non-null  float64\n",
      " 5   DEPTH       284583 non-null  float64\n",
      " 6   RECORDDATE  284583 non-null  object \n",
      "dtypes: float64(4), object(3)\n",
      "memory usage: 15.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DATE_         0\n",
       "LOCATION_     0\n",
       "LAT           0\n",
       "LNG           0\n",
       "MAG           0\n",
       "DEPTH         0\n",
       "RECORDDATE    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LAT</th>\n",
       "      <th>LNG</th>\n",
       "      <th>MAG</th>\n",
       "      <th>DEPTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>284583.000000</td>\n",
       "      <td>284583.000000</td>\n",
       "      <td>284583.000000</td>\n",
       "      <td>284583.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>38.234964</td>\n",
       "      <td>31.376644</td>\n",
       "      <td>2.212529</td>\n",
       "      <td>9.774072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.478462</td>\n",
       "      <td>5.534374</td>\n",
       "      <td>0.666044</td>\n",
       "      <td>10.137096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>30.288700</td>\n",
       "      <td>18.343500</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>37.078500</td>\n",
       "      <td>27.400700</td>\n",
       "      <td>1.700000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>38.309500</td>\n",
       "      <td>28.804700</td>\n",
       "      <td>2.100000</td>\n",
       "      <td>7.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>39.233000</td>\n",
       "      <td>35.924300</td>\n",
       "      <td>2.700000</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>45.809300</td>\n",
       "      <td>48.572500</td>\n",
       "      <td>7.600000</td>\n",
       "      <td>188.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 LAT            LNG            MAG          DEPTH\n",
       "count  284583.000000  284583.000000  284583.000000  284583.000000\n",
       "mean       38.234964      31.376644       2.212529       9.774072\n",
       "std         1.478462       5.534374       0.666044      10.137096\n",
       "min        30.288700      18.343500       0.100000       0.000000\n",
       "25%        37.078500      27.400700       1.700000       5.000000\n",
       "50%        38.309500      28.804700       2.100000       7.300000\n",
       "75%        39.233000      35.924300       2.700000      12.000000\n",
       "max        45.809300      48.572500       7.600000     188.000000"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION_</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LNG</th>\n",
       "      <th>MAG</th>\n",
       "      <th>DEPTH</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KORKUTELi (ANTALYA)</td>\n",
       "      <td>36.9197</td>\n",
       "      <td>30.3133</td>\n",
       "      <td>2.9</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>00:29:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>YUNAK (KONYA)</td>\n",
       "      <td>38.8177</td>\n",
       "      <td>31.8875</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>03:03:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AKDENiZ</td>\n",
       "      <td>36.1153</td>\n",
       "      <td>28.4915</td>\n",
       "      <td>3.5</td>\n",
       "      <td>74.5</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>04:40:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CUBUK (ANKARA)</td>\n",
       "      <td>40.3485</td>\n",
       "      <td>32.9603</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>09:35:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MENEMEN (iZMiR)</td>\n",
       "      <td>38.8013</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>2.9</td>\n",
       "      <td>28.3</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>11:17:43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             LOCATION_      LAT      LNG  MAG  DEPTH        Date      Time\n",
       "0  KORKUTELi (ANTALYA)  36.9197  30.3133  2.9   30.0  2005-01-01  00:29:42\n",
       "1        YUNAK (KONYA)  38.8177  31.8875  3.5    5.8  2005-01-01  03:03:40\n",
       "2              AKDENiZ  36.1153  28.4915  3.5   74.5  2005-01-01  04:40:14\n",
       "3       CUBUK (ANKARA)  40.3485  32.9603  3.0   15.1  2005-01-01  09:35:00\n",
       "4      MENEMEN (iZMiR)  38.8013  27.2075  2.9   28.3  2005-01-01  11:17:43"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Date', 'Time']] = df['DATE_'].str.split(' ', n=1, expand=True)\n",
    "df.drop(columns=[\"DATE_\",'RECORDDATE'],inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION_</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LNG</th>\n",
       "      <th>MAG</th>\n",
       "      <th>DEPTH</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KORKUTELi (ANTALYA)</td>\n",
       "      <td>36.9197</td>\n",
       "      <td>30.3133</td>\n",
       "      <td>2.9</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>00:29:42</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>YUNAK (KONYA)</td>\n",
       "      <td>38.8177</td>\n",
       "      <td>31.8875</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>03:03:40</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AKDENiZ</td>\n",
       "      <td>36.1153</td>\n",
       "      <td>28.4915</td>\n",
       "      <td>3.5</td>\n",
       "      <td>74.5</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>04:40:14</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CUBUK (ANKARA)</td>\n",
       "      <td>40.3485</td>\n",
       "      <td>32.9603</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>09:35:00</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MENEMEN (iZMiR)</td>\n",
       "      <td>38.8013</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>2.9</td>\n",
       "      <td>28.3</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>11:17:43</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             LOCATION_      LAT      LNG  MAG  DEPTH       Date      Time  \\\n",
       "0  KORKUTELi (ANTALYA)  36.9197  30.3133  2.9   30.0 2005-01-01  00:29:42   \n",
       "1        YUNAK (KONYA)  38.8177  31.8875  3.5    5.8 2005-01-01  03:03:40   \n",
       "2              AKDENiZ  36.1153  28.4915  3.5   74.5 2005-01-01  04:40:14   \n",
       "3       CUBUK (ANKARA)  40.3485  32.9603  3.0   15.1 2005-01-01  09:35:00   \n",
       "4      MENEMEN (iZMiR)  38.8013  27.2075  2.9   28.3 2005-01-01  11:17:43   \n",
       "\n",
       "   year  \n",
       "0  2005  \n",
       "1  2005  \n",
       "2  2005  \n",
       "3  2005  \n",
       "4  2005  "
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Date\"] = pd.to_datetime(df[\"Date\"], format=\"%Y %m %d\", errors = 'coerce')\n",
    "df['year'] = df['Date'].dt.year\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mag_ = df[df['MAG']>6]\n",
    "\n",
    "plt.figure(figsize=(16,6))\n",
    "pal = sns.cubehelix_palette(len(mag_.year.value_counts().index), start=.5, rot=-.75)\n",
    "sns.barplot(x=np.sort(mag_.year.value_counts().index) ,y = mag_.year.value_counts().values,palette =pal )\n",
    "plt.xticks(rotation=90 , color ='black')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def extract_location(data):\n",
    "    pattern = r'\\((.*?)\\)'  # Parantez içindeki kısmı ayıklamak için regex deseni\n",
    "    extracted_data = re.findall(pattern, data)\n",
    "    if extracted_data:\n",
    "        return extracted_data[0].strip()\n",
    "    else:\n",
    "        return data.strip()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION_</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LNG</th>\n",
       "      <th>MAG</th>\n",
       "      <th>DEPTH</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ANTALYA</td>\n",
       "      <td>36.9197</td>\n",
       "      <td>30.3133</td>\n",
       "      <td>2.9</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>00:29:42</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KONYA</td>\n",
       "      <td>38.8177</td>\n",
       "      <td>31.8875</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>03:03:40</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AKDENiZ</td>\n",
       "      <td>36.1153</td>\n",
       "      <td>28.4915</td>\n",
       "      <td>3.5</td>\n",
       "      <td>74.5</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>04:40:14</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ANKARA</td>\n",
       "      <td>40.3485</td>\n",
       "      <td>32.9603</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>09:35:00</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>iZMiR</td>\n",
       "      <td>38.8013</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>2.9</td>\n",
       "      <td>28.3</td>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>11:17:43</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  LOCATION_      LAT      LNG  MAG  DEPTH       Date      Time  year\n",
       "0   ANTALYA  36.9197  30.3133  2.9   30.0 2005-01-01  00:29:42  2005\n",
       "1     KONYA  38.8177  31.8875  3.5    5.8 2005-01-01  03:03:40  2005\n",
       "2   AKDENiZ  36.1153  28.4915  3.5   74.5 2005-01-01  04:40:14  2005\n",
       "3    ANKARA  40.3485  32.9603  3.0   15.1 2005-01-01  09:35:00  2005\n",
       "4     iZMiR  38.8013  27.2075  2.9   28.3 2005-01-01  11:17:43  2005"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['LOCATION_'] = df['LOCATION_'].apply(extract_location)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mag_ = df[df['MAG']>5]\n",
    "\n",
    "plt.figure(figsize=(16,6))\n",
    "pal = sns.cubehelix_palette(len(mag_.LOCATION_.value_counts().index), start=.5, rot=-.75)\n",
    "sns.barplot(x=np.sort(mag_.LOCATION_.value_counts().index) ,y = mag_.LOCATION_.value_counts().values,palette =pal )\n",
    "plt.xticks(rotation=90 , color ='black')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['MUGLA', 'KAS ACIKLARI- AKDENiZ', 'HAKKARi', 'AKDENiZ', 'BiNGOL',\n",
       "       'ANKARA', 'EGE DENiZi', 'iZMiR',\n",
       "       'SEFERiHiSAR ACIKLARI-iZMiR (EGE DENiZi', 'MALATYA', 'KUS GOLU',\n",
       "       'MARMARA DENiZi', 'ELAZIG', 'DENiZLi', 'YUNANiSTAN', 'ADIYAMAN',\n",
       "       'EGE DENIZI', 'AKDENIZ', 'KARADENIZ', 'GURCiSTAN', 'KUTAHYA',\n",
       "       '2011.07.25 20:57:19', 'ERZiNCAN', 'VAN', '2011.11.09 00:05:50',\n",
       "       'ONiKi ADALAR YUNANiSTAN', 'IRAK', 'BULGARiSTAN',\n",
       "       'MARMARA EREGLiSi ACIKLARI-TEKiRDAG (MARMARA DENiZi', 'SIRNAK',\n",
       "       '2012.09.12 06:27:48', 'KAHRAMANMARAS', 'iRAN', 'KARADENiZ',\n",
       "       'EGE DENIZI                                        REVIZE01',\n",
       "       '2013.04.06 14:26:11', '2013.06.15 19:11:05', 'CANAKKALE',\n",
       "       'YUNANISTAN',\n",
       "       'GURCISTAN                                         İlksel', 'MUS',\n",
       "       'IRAK                                              İlksel',\n",
       "       '2013.12.28 17:21:02',\n",
       "       'YUNANISTAN                                        İlksel',\n",
       "       'EGE DENIZI                                        İlksel',\n",
       "       'AKDENIZ                                           İlksel',\n",
       "       'IRAN-IRAK SINIR BOLGESI                           REVIZE01',\n",
       "       'IRAN                                              İlksel',\n",
       "       'IRAN-IRAK SINIR BOLGESI                           İlksel',\n",
       "       'BURDUR',\n",
       "       'KIBRIS RUM KESIMI                                 İlksel',\n",
       "       'AZERBAYCAN                                        İlksel',\n",
       "       'ANTALYA', 'TOKAT', 'BINGOL', '2015.12.26 13:00:49', 'KIRSEHIR',\n",
       "       '2016.07.28 19:13:33', 'ROMANYA', 'MANISA',\n",
       "       'MERKEZ-MANISA                                     Otomatik',\n",
       "       '2017.05.17 14:30:32', '2017.06.12 15:28:39',\n",
       "       '2017.06.17 22:50:04', '2017.10.12 01:49:43',\n",
       "       '2017.11.12 21:18:18', '2017.11.13 07:27:58', 'IRAN',\n",
       "       'IRAN-IRAQ BORDER REGION                           Otomatik',\n",
       "       '2018.06.05 21:40:25', '2019.01.24 17:30:54', 'DENIZLI',\n",
       "       '2019.07.19 14:13:13', 'CANKIRI', 'MARMARA DENIZI',\n",
       "       'TURKIYE-IRAN SINIR BOLGESI                        İlksel',\n",
       "       'NIGDE', 'SIIRT', 'SURIYE', 'DUZCE', 'KONYA', 'ERZURUM',\n",
       "       '2022.01.11 04:07:51', 'KAYSERI', '2022.01.05 06:21:14',\n",
       "       'ERMENISTAN-GURCISTAN SINIR BOLGESI', 'ARDAHAN', 'IZMIR', 'RUSYA',\n",
       "       'TURKIYE-IRAN SINIR BOLGESI', 'ADANA', 'HATAY'], dtype=object)"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mag_.LOCATION_.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mag_ = df[df['MAG'] > 5]\n",
    "\n",
    "plt.figure(figsize=(16,6))\n",
    "# Sayısal olmayan verilerin seçimi\n",
    "non_numeric_indices = [i for i, val in enumerate(mag_.LOCATION_.value_counts().index) if not val.isnumeric()]\n",
    "non_numeric_values = mag_.LOCATION_.value_counts().values[non_numeric_indices]\n",
    "non_numeric_labels = np.array(mag_.LOCATION_.value_counts().index)[non_numeric_indices]\n",
    "\n",
    "pal = sns.cubehelix_palette(len(non_numeric_labels), start=.5, rot=-.75)\n",
    "sns.barplot(x=non_numeric_labels, y=non_numeric_values, palette=pal)\n",
    "plt.xticks(rotation=90, color='black')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "customdata": [
          [
           15.9,
           5.1,
           "2005-01-11T00:00:00"
          ],
          [
           34.2,
           5.5,
           "2005-01-24T00:00:00"
          ],
          [
           30,
           5.5,
           "2005-01-25T00:00:00"
          ],
          [
           33.8,
           5.3,
           "2005-01-30T00:00:00"
          ],
          [
           5,
           5.7,
           "2005-03-12T00:00:00"
          ],
          [
           5,
           5.9,
           "2005-03-14T00:00:00"
          ],
          [
           5,
           5.5,
           "2005-03-23T00:00:00"
          ],
          [
           34.9,
           5.7,
           "2005-06-06T00:00:00"
          ],
          [
           5,
           5.3,
           "2005-07-31T00:00:00"
          ],
          [
           36,
           5.1,
           "2005-08-24T00:00:00"
          ],
          [
           8.099999999999998,
           5.7,
           "2005-10-17T00:00:00"
          ],
          [
           10.4,
           5.9,
           "2005-10-17T00:00:00"
          ],
          [
           20.7,
           5.2,
           "2005-10-17T00:00:00"
          ],
          [
           7.5,
           5.9,
           "2005-10-21T00:00:00"
          ],
          [
           8.5,
           5.3,
           "2005-11-26T00:00:00"
          ],
          [
           5,
           5.3,
           "2005-12-10T00:00:00"
          ],
          [
           67.4,
           5.2,
           "2006-04-10T00:00:00"
          ],
          [
           78.79999999999998,
           5.1,
           "2006-08-22T00:00:00"
          ],
          [
           12.9,
           5.2,
           "2006-10-20T00:00:00"
          ],
          [
           14.3,
           5.2,
           "2006-10-24T00:00:00"
          ],
          [
           5,
           5.3,
           "2007-02-09T00:00:00"
          ],
          [
           5,
           5.9,
           "2007-02-21T00:00:00"
          ],
          [
           5,
           5.4,
           "2007-08-26T00:00:00"
          ],
          [
           32.3,
           5.3,
           "2007-08-31T00:00:00"
          ],
          [
           5,
           5.2,
           "2007-09-23T00:00:00"
          ],
          [
           5,
           5.1,
           "2007-10-29T00:00:00"
          ],
          [
           10.4,
           5.3,
           "2007-11-09T00:00:00"
          ],
          [
           3.4,
           5.2,
           "2007-11-09T00:00:00"
          ],
          [
           5,
           5.7,
           "2007-12-20T00:00:00"
          ],
          [
           5,
           5.5,
           "2007-12-27T00:00:00"
          ],
          [
           32.6,
           5.4,
           "2008-03-28T00:00:00"
          ],
          [
           18.7,
           6.4,
           "2008-07-15T00:00:00"
          ],
          [
           5,
           5.3,
           "2008-08-03T00:00:00"
          ],
          [
           5.7,
           5.1,
           "2008-09-03T00:00:00"
          ],
          [
           8.599999999999998,
           5.2,
           "2008-12-29T00:00:00"
          ],
          [
           36.1,
           5.2,
           "2009-01-13T00:00:00"
          ],
          [
           40.7,
           5.6,
           "2009-06-19T00:00:00"
          ],
          [
           10.3,
           6.2,
           "2009-07-01T00:00:00"
          ],
          [
           30.9,
           5.1,
           "2009-08-05T00:00:00"
          ],
          [
           39.2,
           5.4,
           "2009-12-22T00:00:00"
          ],
          [
           5,
           6,
           "2010-03-08T00:00:00"
          ],
          [
           5,
           5.5,
           "2010-03-08T00:00:00"
          ],
          [
           5,
           5.1,
           "2010-03-08T00:00:00"
          ],
          [
           5,
           5.3,
           "2010-03-08T00:00:00"
          ],
          [
           4.5,
           5.1,
           "2010-03-24T00:00:00"
          ],
          [
           15.3,
           5.3,
           "2010-11-03T00:00:00"
          ],
          [
           8.099999999999998,
           5.3,
           "2011-01-19T00:00:00"
          ],
          [
           42.8,
           5.3,
           "2011-02-28T00:00:00"
          ],
          [
           12.1,
           6.3,
           "2011-04-01T00:00:00"
          ],
          [
           6.2,
           5.1,
           "2011-05-08T00:00:00"
          ],
          [
           7.599999999999999,
           5.9,
           "2011-05-19T00:00:00"
          ],
          [
           5,
           5.4,
           "2011-06-23T00:00:00"
          ],
          [
           15.3,
           5.2,
           "2011-07-25T00:00:00"
          ],
          [
           5,
           5.6,
           "2011-09-22T00:00:00"
          ],
          [
           5,
           5.4,
           "2011-10-25T00:00:00"
          ],
          [
           5,
           6.6,
           "2011-10-23T00:00:00"
          ],
          [
           9,
           5.4,
           "2011-10-23T00:00:00"
          ],
          [
           5,
           5.5,
           "2011-10-23T00:00:00"
          ],
          [
           5,
           5.5,
           "2011-10-23T00:00:00"
          ],
          [
           5,
           5.7,
           "2011-10-23T00:00:00"
          ],
          [
           18.3,
           5.4,
           "2011-10-27T00:00:00"
          ],
          [
           5,
           5.2,
           "2011-10-30T00:00:00"
          ],
          [
           4.3,
           5.5,
           "2011-11-09T00:00:00"
          ],
          [
           5,
           5.6,
           "2011-11-09T00:00:00"
          ],
          [
           7.8,
           5.2,
           "2011-11-15T00:00:00"
          ],
          [
           6,
           5.1,
           "2011-12-05T00:00:00"
          ],
          [
           16.2,
           5.2,
           "2012-01-26T00:00:00"
          ],
          [
           22.9,
           5.3,
           "2012-01-27T00:00:00"
          ],
          [
           37.5,
           5.2,
           "2012-03-05T00:00:00"
          ],
          [
           5,
           5.2,
           "2012-04-16T00:00:00"
          ],
          [
           3.1,
           5.1,
           "2012-05-03T00:00:00"
          ],
          [
           19.1,
           5.4,
           "2012-05-11T00:00:00"
          ],
          [
           28.1,
           6.4,
           "2012-05-22T00:00:00"
          ],
          [
           14.9,
           5.1,
           "2012-06-07T00:00:00"
          ],
          [
           19.4,
           6,
           "2012-06-10T00:00:00"
          ],
          [
           5.4,
           5.5,
           "2012-06-14T00:00:00"
          ],
          [
           26.4,
           5.3,
           "2012-06-25T00:00:00"
          ],
          [
           21.1,
           6,
           "2012-07-09T00:00:00"
          ],
          [
           5.4,
           5.3,
           "2012-08-05T00:00:00"
          ],
          [
           40.4,
           5.5,
           "2012-09-12T00:00:00"
          ],
          [
           8.3,
           5.1,
           "2012-09-19T00:00:00"
          ],
          [
           43.1,
           5.3,
           "2012-10-19T00:00:00"
          ],
          [
           5,
           5.6,
           "2012-11-07T00:00:00"
          ],
          [
           5,
           5.5,
           "2012-12-23T00:00:00"
          ],
          [
           8.699999999999998,
           5.4,
           "2012-12-26T00:00:00"
          ],
          [
           8.4,
           5.7,
           "2013-01-08T00:00:00"
          ],
          [
           5,
           5.2,
           "2013-03-11T00:00:00"
          ],
          [
           28,
           5.2,
           "2013-04-06T00:00:00"
          ],
          [
           10,
           6,
           "2013-06-15T00:00:00"
          ],
          [
           15.8,
           5.7,
           "2013-06-17T00:00:00"
          ],
          [
           9.8,
           5.3,
           "2013-07-30T00:00:00"
          ],
          [
           5,
           5.1,
           "2013-08-07T00:00:00"
          ],
          [
           5,
           5.2,
           "2013-09-17T00:00:00"
          ],
          [
           2.5,
           5.1,
           "2013-09-17T00:00:00"
          ],
          [
           52.8,
           6.4,
           "2013-10-12T00:00:00"
          ],
          [
           5,
           5.3,
           "2013-11-24T00:00:00"
          ],
          [
           46,
           6,
           "2013-12-28T00:00:00"
          ],
          [
           110.4,
           5.4,
           "2014-04-04T00:00:00"
          ],
          [
           54.1,
           5.1,
           "2014-04-14T00:00:00"
          ],
          [
           21.2,
           6.8,
           "2014-05-24T00:00:00"
          ],
          [
           7.2,
           5.1,
           "2014-05-24T00:00:00"
          ],
          [
           97.8,
           5.2,
           "2014-06-11T00:00:00"
          ],
          [
           10,
           5.7,
           "2014-08-18T00:00:00"
          ],
          [
           10,
           5.1,
           "2014-08-23T00:00:00"
          ],
          [
           10,
           5.5,
           "2014-08-20T00:00:00"
          ],
          [
           14.4,
           5.2,
           "2014-08-22T00:00:00"
          ],
          [
           8.9,
           5.8,
           "2014-08-18T00:00:00"
          ],
          [
           10,
           5.6,
           "2014-08-18T00:00:00"
          ],
          [
           7.4,
           5.1,
           "2014-08-24T00:00:00"
          ],
          [
           29.6,
           5.4,
           "2014-08-22T00:00:00"
          ],
          [
           10,
           5.1,
           "2014-08-20T00:00:00"
          ],
          [
           10,
           6.1,
           "2014-08-18T00:00:00"
          ],
          [
           15,
           5.1,
           "2014-08-24T00:00:00"
          ],
          [
           10,
           5.6,
           "2014-08-29T00:00:00"
          ],
          [
           25.6,
           5.2,
           "2014-09-05T00:00:00"
          ],
          [
           14.1,
           5.1,
           "2014-11-18T00:00:00"
          ],
          [
           12.1,
           5.3,
           "2014-11-18T00:00:00"
          ],
          [
           13.7,
           5.2,
           "2014-12-06T00:00:00"
          ],
          [
           31.1,
           5.1,
           "2015-03-28T00:00:00"
          ],
          [
           22.1,
           6.1,
           "2015-04-16T00:00:00"
          ],
          [
           13.5,
           5.5,
           "2015-04-15T00:00:00"
          ],
          [
           18.6,
           5.5,
           "2015-04-17T00:00:00"
          ],
          [
           8.199999999999998,
           5.3,
           "2015-06-09T00:00:00"
          ],
          [
           11,
           5.3,
           "2015-06-10T00:00:00"
          ],
          [
           21.5,
           5.2,
           "2015-07-30T00:00:00"
          ],
          [
           14.1,
           5.8,
           "2015-09-04T00:00:00"
          ],
          [
           22.4,
           5.5,
           "2015-10-07T00:00:00"
          ],
          [
           5,
           5.1,
           "2015-10-09T00:00:00"
          ],
          [
           2.3,
           5.1,
           "2015-11-29T00:00:00"
          ],
          [
           5,
           5.5,
           "2015-12-03T00:00:00"
          ],
          [
           14.8,
           5.4,
           "2015-12-26T00:00:00"
          ],
          [
           5,
           5.1,
           "2016-01-10T00:00:00"
          ],
          [
           6,
           5.3,
           "2016-05-25T00:00:00"
          ],
          [
           5,
           5.2,
           "2016-07-28T00:00:00"
          ],
          [
           83.29999999999998,
           5.4,
           "2016-09-27T00:00:00"
          ],
          [
           7.3,
           5.1,
           "2016-11-19T00:00:00"
          ],
          [
           49.7,
           5.9,
           "2016-12-28T00:00:00"
          ],
          [
           118.8,
           5.4,
           "2016-12-20T00:00:00"
          ],
          [
           22.1,
           5.3,
           "2017-01-25T00:00:00"
          ],
          [
           14,
           5.3,
           "2017-02-06T00:00:00"
          ],
          [
           9.8,
           5.4,
           "2017-02-06T00:00:00"
          ],
          [
           11.1,
           5.3,
           "2017-02-12T00:00:00"
          ],
          [
           12.3,
           5.3,
           "2017-02-07T00:00:00"
          ],
          [
           5.6,
           5.1,
           "2017-04-21T00:00:00"
          ],
          [
           10,
           5.1,
           "2017-04-21T00:00:00"
          ],
          [
           8.3,
           5.1,
           "2017-05-17T00:00:00"
          ],
          [
           13.2,
           5.2,
           "2017-05-27T00:00:00"
          ],
          [
           19.5,
           6.3,
           "2017-06-12T00:00:00"
          ],
          [
           14.1,
           5.6,
           "2017-06-17T00:00:00"
          ],
          [
           5,
           6.6,
           "2017-07-21T00:00:00"
          ],
          [
           5,
           5.3,
           "2017-08-08T00:00:00"
          ],
          [
           16.2,
           5.3,
           "2017-08-01T00:00:00"
          ],
          [
           8.199999999999998,
           5.2,
           "2017-10-12T00:00:00"
          ],
          [
           6.3,
           5.1,
           "2017-11-25T00:00:00"
          ],
          [
           11.7,
           7.1,
           "2017-11-12T00:00:00"
          ],
          [
           8.599999999999998,
           5.1,
           "2017-11-13T00:00:00"
          ],
          [
           4.2,
           5.1,
           "2017-11-13T00:00:00"
          ],
          [
           13.4,
           5.4,
           "2018-04-24T00:00:00"
          ],
          [
           10,
           5.3,
           "2018-04-01T00:00:00"
          ],
          [
           26.8,
           5.4,
           "2018-04-19T00:00:00"
          ],
          [
           24.6,
           5.3,
           "2018-06-25T00:00:00"
          ],
          [
           11.6,
           5.4,
           "2018-06-05T00:00:00"
          ],
          [
           5.5,
           5.1,
           "2018-07-13T00:00:00"
          ],
          [
           13.1,
           5.3,
           "2018-09-12T00:00:00"
          ],
          [
           46.6,
           5.3,
           "2019-01-24T00:00:00"
          ],
          [
           7.599999999999999,
           5.4,
           "2019-02-20T00:00:00"
          ],
          [
           5,
           5.7,
           "2019-03-20T00:00:00"
          ],
          [
           5.3,
           5.1,
           "2019-03-31T00:00:00"
          ],
          [
           1.2,
           5.3,
           "2019-04-04T00:00:00"
          ],
          [
           5.3,
           5.5,
           "2019-07-19T00:00:00"
          ],
          [
           83.59999999999998,
           5.1,
           "2019-08-03T00:00:00"
          ],
          [
           8.9,
           5.7,
           "2019-08-08T00:00:00"
          ],
          [
           19.2,
           5.1,
           "2019-09-24T00:00:00"
          ],
          [
           6.1,
           5.1,
           "2019-09-14T00:00:00"
          ],
          [
           12.3,
           5.7,
           "2019-09-26T00:00:00"
          ],
          [
           9.3,
           5.2,
           "2019-10-03T00:00:00"
          ],
          [
           86.79999999999998,
           6,
           "2019-11-27T00:00:00"
          ],
          [
           82,
           5.3,
           "2019-12-11T00:00:00"
          ],
          [
           3.8,
           5.1,
           "2019-12-27T00:00:00"
          ],
          [
           13.6,
           5.1,
           "2020-01-28T00:00:00"
          ],
          [
           5,
           5.5,
           "2020-01-30T00:00:00"
          ],
          [
           5,
           6.7,
           "2020-01-24T00:00:00"
          ],
          [
           5.8,
           5.5,
           "2020-01-28T00:00:00"
          ],
          [
           5.1,
           5.1,
           "2020-01-25T00:00:00"
          ],
          [
           7.1,
           5.8,
           "2020-01-30T00:00:00"
          ],
          [
           12.2,
           5.6,
           "2020-01-22T00:00:00"
          ],
          [
           13,
           5.2,
           "2020-02-18T00:00:00"
          ],
          [
           7.2,
           6,
           "2020-02-23T00:00:00"
          ],
          [
           5,
           5.8,
           "2020-02-23T00:00:00"
          ],
          [
           5.2,
           5.1,
           "2020-02-26T00:00:00"
          ],
          [
           5.4,
           5.2,
           "2020-03-19T00:00:00"
          ],
          [
           5,
           5.7,
           "2020-05-19T00:00:00"
          ],
          [
           8.9,
           5.1,
           "2020-05-27T00:00:00"
          ],
          [
           55.1,
           6.6,
           "2020-05-02T00:00:00"
          ],
          [
           5,
           5.2,
           "2020-05-02T00:00:00"
          ],
          [
           6.4,
           5.3,
           "2020-05-02T00:00:00"
          ],
          [
           5,
           5.1,
           "2020-05-24T00:00:00"
          ],
          [
           5.3,
           5.4,
           "2020-06-25T00:00:00"
          ],
          [
           1.8,
           5.6,
           "2020-06-15T00:00:00"
          ],
          [
           78.2,
           5.4,
           "2020-06-28T00:00:00"
          ],
          [
           5,
           5.9,
           "2020-06-14T00:00:00"
          ],
          [
           5.4,
           5.3,
           "2020-06-05T00:00:00"
          ],
          [
           10.9,
           5.5,
           "2020-06-26T00:00:00"
          ],
          [
           5.5,
           5.7,
           "2020-08-04T00:00:00"
          ],
          [
           68.2,
           5.8,
           "2020-09-18T00:00:00"
          ],
          [
           5,
           5.2,
           "2020-09-20T00:00:00"
          ],
          [
           14.7,
           5.6,
           "2020-09-27T00:00:00"
          ],
          [
           5,
           5.1,
           "2020-10-31T00:00:00"
          ],
          [
           12.1,
           6.9,
           "2020-10-30T00:00:00"
          ],
          [
           13.2,
           5.2,
           "2020-10-30T00:00:00"
          ],
          [
           9.1,
           5.1,
           "2020-10-12T00:00:00"
          ],
          [
           5,
           5.2,
           "2020-11-10T00:00:00"
          ],
          [
           5,
           5.2,
           "2020-12-03T00:00:00"
          ],
          [
           6,
           5.6,
           "2020-12-27T00:00:00"
          ],
          [
           98.6,
           5.5,
           "2020-12-05T00:00:00"
          ],
          [
           38.3,
           5.4,
           "2021-01-26T00:00:00"
          ],
          [
           51.4,
           5.1,
           "2021-01-21T00:00:00"
          ],
          [
           8.9,
           5.3,
           "2021-04-13T00:00:00"
          ],
          [
           4.6,
           5.3,
           "2021-06-25T00:00:00"
          ],
          [
           12,
           5.5,
           "2021-06-22T00:00:00"
          ],
          [
           8.8,
           5.1,
           "2021-07-19T00:00:00"
          ],
          [
           9,
           5.7,
           "2021-08-01T00:00:00"
          ],
          [
           7.2,
           5.1,
           "2021-08-07T00:00:00"
          ],
          [
           5.4,
           5.2,
           "2021-08-03T00:00:00"
          ],
          [
           4.2,
           6,
           "2021-09-27T00:00:00"
          ],
          [
           5.8,
           5.3,
           "2021-09-28T00:00:00"
          ],
          [
           16.2,
           6.3,
           "2021-10-12T00:00:00"
          ],
          [
           28.4,
           6.1,
           "2021-10-19T00:00:00"
          ],
          [
           7.4,
           5.2,
           "2021-11-17T00:00:00"
          ],
          [
           4.8,
           5.3,
           "2021-11-30T00:00:00"
          ],
          [
           5,
           5.1,
           "2021-11-08T00:00:00"
          ],
          [
           5,
           5.2,
           "2021-11-19T00:00:00"
          ],
          [
           84.5,
           5.7,
           "2021-12-29T00:00:00"
          ],
          [
           5,
           5.1,
           "2021-12-26T00:00:00"
          ],
          [
           5,
           5.5,
           "2021-12-26T00:00:00"
          ],
          [
           36.3,
           6.2,
           "2022-01-11T00:00:00"
          ],
          [
           5,
           5.1,
           "2022-01-18T00:00:00"
          ],
          [
           18.3,
           5.6,
           "2022-01-16T00:00:00"
          ],
          [
           18.1,
           5.3,
           "2022-01-05T00:00:00"
          ],
          [
           5,
           5.1,
           "2022-02-03T00:00:00"
          ],
          [
           5.6,
           5.6,
           "2022-02-13T00:00:00"
          ],
          [
           5,
           5.2,
           "2022-04-09T00:00:00"
          ],
          [
           5,
           5.3,
           "2022-06-12T00:00:00"
          ],
          [
           13.5,
           5.3,
           "2022-08-31T00:00:00"
          ],
          [
           5,
           5.3,
           "2022-09-03T00:00:00"
          ],
          [
           3.2,
           5.3,
           "2022-09-27T00:00:00"
          ],
          [
           5,
           5.8,
           "2022-10-05T00:00:00"
          ],
          [
           21.9,
           5.3,
           "2022-10-02T00:00:00"
          ],
          [
           69.2,
           5.3,
           "2022-11-21T00:00:00"
          ],
          [
           10.6,
           6,
           "2022-11-23T00:00:00"
          ],
          [
           158.4,
           5.1,
           "2022-11-03T00:00:00"
          ],
          [
           4.5,
           5.1,
           "2022-11-04T00:00:00"
          ],
          [
           1.1,
           5.2,
           "2022-12-08T00:00:00"
          ],
          [
           30.3,
           5.7,
           "2023-01-25T00:00:00"
          ],
          [
           5,
           6.1,
           "2023-01-28T00:00:00"
          ],
          [
           5,
           5.9,
           "2023-01-18T00:00:00"
          ],
          [
           11.2,
           5.1,
           "2023-01-07T00:00:00"
          ],
          [
           4.5,
           5.1,
           "2023-01-10T00:00:00"
          ],
          [
           5,
           5.3,
           "2023-02-25T00:00:00"
          ],
          [
           1.9,
           6,
           "2023-02-06T00:00:00"
          ],
          [
           3.4,
           5.5,
           "2023-02-08T00:00:00"
          ],
          [
           11.5,
           5.7,
           "2023-02-06T00:00:00"
          ],
          [
           5,
           5.5,
           "2023-02-06T00:00:00"
          ],
          [
           9.4,
           5.7,
           "2023-02-06T00:00:00"
          ],
          [
           5,
           7.599999999999999,
           "2023-02-06T00:00:00"
          ],
          [
           5.4,
           5.1,
           "2023-02-06T00:00:00"
          ],
          [
           2,
           5.1,
           "2023-02-07T00:00:00"
          ],
          [
           3.3,
           5.4,
           "2023-02-06T00:00:00"
          ],
          [
           5,
           5.3,
           "2023-02-06T00:00:00"
          ],
          [
           7.8,
           5.3,
           "2023-02-06T00:00:00"
          ],
          [
           5,
           5.3,
           "2023-02-08T00:00:00"
          ],
          [
           17.4,
           5.2,
           "2023-02-06T00:00:00"
          ],
          [
           7.599999999999999,
           5.1,
           "2023-02-06T00:00:00"
          ],
          [
           4.4,
           5.3,
           "2023-02-06T00:00:00"
          ],
          [
           6.1,
           5.3,
           "2023-02-18T00:00:00"
          ],
          [
           5,
           5.2,
           "2023-02-06T00:00:00"
          ],
          [
           2.6,
           5.2,
           "2023-02-12T00:00:00"
          ],
          [
           2.3,
           5.6,
           "2023-02-07T00:00:00"
          ],
          [
           8.599999999999998,
           5.4,
           "2023-02-07T00:00:00"
          ],
          [
           5,
           5.1,
           "2023-02-07T00:00:00"
          ],
          [
           5,
           5.5,
           "2023-02-27T00:00:00"
          ],
          [
           8.5,
           6.4,
           "2023-02-20T00:00:00"
          ],
          [
           5.3,
           5.2,
           "2023-02-06T00:00:00"
          ],
          [
           5.4,
           5.2,
           "2023-02-27T00:00:00"
          ],
          [
           5,
           5.5,
           "2023-02-07T00:00:00"
          ],
          [
           5,
           5.3,
           "2023-02-07T00:00:00"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>LAT=%{lat}<br>LNG=%{lon}<br>DEPTH=%{customdata[0]}<br>MAG=%{customdata[1]}<br>Date=%{customdata[2]}<extra></extra>",
         "hovertext": [
          "MUGLA",
          "KAS ACIKLARI- AKDENiZ",
          "HAKKARi",
          "AKDENiZ",
          "BiNGOL",
          "BiNGOL",
          "BiNGOL",
          "BiNGOL",
          "ANKARA",
          "EGE DENiZi",
          "EGE DENiZi",
          "iZMiR",
          "EGE DENiZi",
          "SEFERiHiSAR ACIKLARI-iZMiR (EGE DENiZi",
          "MALATYA",
          "BiNGOL",
          "AKDENiZ",
          "AKDENiZ",
          "KUS GOLU",
          "MARMARA DENiZi",
          "ELAZIG",
          "ELAZIG",
          "BiNGOL",
          "AKDENiZ",
          "AKDENiZ",
          "DENiZLi",
          "EGE DENiZi",
          "EGE DENiZi",
          "ANKARA",
          "ANKARA",
          "AKDENiZ",
          "AKDENiZ",
          "YUNANiSTAN",
          "ADIYAMAN",
          "EGE DENIZI",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "KARADENIZ",
          "AKDENIZ",
          "ELAZIG",
          "ELAZIG",
          "ELAZIG",
          "ELAZIG",
          "ELAZIG",
          "EGE DENiZi",
          "GURCiSTAN",
          "AKDENiZ",
          "AKDENiZ",
          "AKDENiZ",
          "KUTAHYA",
          "ELAZIG",
          "2011.07.25 20:57:19",
          "ERZiNCAN",
          "VAN",
          "VAN",
          "VAN",
          "VAN",
          "VAN",
          "VAN",
          "HAKKARi",
          "VAN",
          "2011.11.09 00:05:50",
          "VAN",
          "VAN",
          "EGE DENiZi",
          "ONiKi ADALAR YUNANiSTAN",
          "ONiKi ADALAR YUNANiSTAN",
          "IRAK",
          "YUNANiSTAN",
          "KUTAHYA",
          "AKDENiZ",
          "BULGARiSTAN",
          "MARMARA EREGLiSi ACIKLARI-TEKiRDAG (MARMARA DENiZi",
          "AKDENiZ",
          "SIRNAK",
          "AKDENiZ",
          "AKDENiZ",
          "SIRNAK",
          "2012.09.12 06:27:48",
          "KAHRAMANMARAS",
          "AKDENiZ",
          "iRAN",
          "KARADENiZ",
          "KARADENiZ",
          "EGE DENIZI                                        REVIZE01",
          "IRAK",
          "2013.04.06 14:26:11",
          "2013.06.15 19:11:05",
          "AKDENiZ",
          "CANAKKALE",
          "YUNANISTAN",
          "GURCISTAN                                         İlksel",
          "MUS",
          "YUNANISTAN",
          "IRAK                                              İlksel",
          "2013.12.28 17:21:02",
          "YUNANISTAN                                        İlksel",
          "AKDENIZ",
          "EGE DENIZI                                        İlksel",
          "EGE DENIZI",
          "AKDENIZ                                           İlksel",
          "IRAN-IRAK SINIR BOLGESI                           REVIZE01",
          "IRAN                                              İlksel",
          "IRAN-IRAK SINIR BOLGESI                           İlksel",
          "YUNANISTAN                                        İlksel",
          "IRAN-IRAK SINIR BOLGESI                           İlksel",
          "IRAN-IRAK SINIR BOLGESI                           İlksel",
          "BURDUR",
          "IRAK                                              İlksel",
          "IRAN-IRAK SINIR BOLGESI                           İlksel",
          "IRAN-IRAK SINIR BOLGESI                           REVIZE01",
          "IRAN-IRAK SINIR BOLGESI                           İlksel",
          "YUNANISTAN                                        İlksel",
          "AKDENIZ                                           İlksel",
          "YUNANISTAN                                        İlksel",
          "YUNANISTAN                                        İlksel",
          "EGE DENIZI                                        İlksel",
          "AKDENIZ                                           İlksel",
          "AKDENIZ",
          "KIBRIS RUM KESIMI                                 İlksel",
          "AKDENIZ",
          "YUNANISTAN                                        İlksel",
          "AKDENIZ",
          "AKDENIZ",
          "AZERBAYCAN                                        İlksel",
          "ANTALYA",
          "TOKAT",
          "MALATYA",
          "BINGOL",
          "2015.12.26 13:00:49",
          "KIRSEHIR",
          "AKDENIZ",
          "2016.07.28 19:13:33",
          "AKDENIZ",
          "YUNANISTAN",
          "ROMANYA",
          "AKDENIZ",
          "AKDENIZ",
          "CANAKKALE",
          "CANAKKALE",
          "CANAKKALE",
          "CANAKKALE",
          "MANISA",
          "MERKEZ-MANISA                                     Otomatik",
          "2017.05.17 14:30:32",
          "MANISA",
          "2017.06.12 15:28:39",
          "2017.06.17 22:50:04",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "2017.10.12 01:49:43",
          "MUGLA",
          "2017.11.12 21:18:18",
          "2017.11.13 07:27:58",
          "IRAN",
          "ADIYAMAN",
          "IRAN-IRAQ BORDER REGION                           Otomatik",
          "IRAN",
          "YUNANISTAN",
          "2018.06.05 21:40:25",
          "AKDENIZ",
          "AKDENIZ                                           İlksel",
          "2019.01.24 17:30:54",
          "CANAKKALE",
          "DENIZLI",
          "DENIZLI",
          "ELAZIG",
          "2019.07.19 14:13:13",
          "AKDENIZ",
          "DENIZLI",
          "AKDENIZ",
          "CANKIRI",
          "MARMARA DENIZI",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "ELAZIG",
          "MANISA",
          "AKDENIZ                                           İlksel",
          "ELAZIG",
          "AKDENIZ                                           İlksel",
          "ELAZIG",
          "AKDENIZ                                           İlksel",
          "MANISA",
          "MANISA",
          "TURKIYE-IRAN SINIR BOLGESI                        İlksel",
          "TURKIYE-IRAN SINIR BOLGESI                        İlksel",
          "MALATYA",
          "ELAZIG",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "VAN",
          "BINGOL",
          "MUGLA",
          "BINGOL",
          "MALATYA",
          "MANISA",
          "MALATYA",
          "AKDENIZ",
          "NIGDE",
          "YUNANISTAN                                        İlksel",
          "EGE DENIZI",
          "EGE DENIZI                                        İlksel",
          "EGE DENIZI",
          "AKDENIZ                                           İlksel",
          "IRAN                                              İlksel",
          "SIIRT",
          "ELAZIG",
          "AKDENIZ",
          "SURIYE",
          "AKDENIZ",
          "AKDENIZ",
          "ELAZIG",
          "AKDENIZ                                           İlksel",
          "SURIYE",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "DUZCE",
          "AKDENIZ",
          "KONYA",
          "ERZURUM",
          "AKDENIZ",
          "AKDENIZ",
          "AKDENIZ",
          "2022.01.11 04:07:51",
          "KAYSERI",
          "YUNANISTAN",
          "2022.01.05 06:21:14",
          "AKDENIZ",
          "ERMENISTAN-GURCISTAN SINIR BOLGESI",
          "MALATYA",
          "VAN",
          "EGE DENIZI",
          "AKDENIZ",
          "ARDAHAN",
          "IRAN",
          "AKDENIZ",
          "AKDENIZ",
          "DUZCE",
          "ROMANYA",
          "IZMIR",
          "RUSYA",
          "AKDENIZ",
          "IRAN",
          "TURKIYE-IRAN SINIR BOLGESI",
          "EGE DENIZI",
          "EGE DENIZI",
          "NIGDE",
          "ADANA",
          "MALATYA",
          "MALATYA",
          "MALATYA",
          "MALATYA",
          "KAHRAMANMARAS",
          "MALATYA",
          "KAHRAMANMARAS",
          "KAHRAMANMARAS",
          "KAHRAMANMARAS",
          "KAHRAMANMARAS",
          "KAHRAMANMARAS",
          "MALATYA",
          "MALATYA",
          "KAHRAMANMARAS",
          "KAHRAMANMARAS",
          "KAHRAMANMARAS",
          "MALATYA",
          "ADIYAMAN",
          "ADIYAMAN",
          "KAHRAMANMARAS",
          "MALATYA",
          "HATAY",
          "KAHRAMANMARAS",
          "ADIYAMAN",
          "MALATYA",
          "KAHRAMANMARAS"
         ],
         "lat": [
          37.0167,
          35.8642,
          37.805,
          35.7783,
          39.384,
          39.3502,
          39.3945,
          39.3803,
          39.4375,
          39.7197,
          38.1307,
          38.169,
          38.1425,
          38.168,
          38.2597,
          39.3758,
          35.0482,
          35.121,
          40.2635,
          40.424,
          38.3868,
          38.373,
          39.2538,
          36.7982,
          34.8183,
          37.0327,
          38.823,
          38.7658,
          39.4043,
          39.4168,
          34.139,
          35.786,
          39.61,
          37.5072,
          40.4047,
          35.4915,
          35.0882,
          33.6008,
          43.4152,
          35.6192,
          38.807,
          38.7805,
          38.828,
          38.776,
          38.8212,
          40.4232,
          41.9415,
          34.899,
          35.587,
          36.7028,
          39.152,
          38.5717,
          40.8108,
          39.7853,
          38.7733,
          38.726,
          38.7513,
          38.8137,
          38.8095,
          38.6345,
          37.3283,
          38.891,
          38.7242,
          38.4295,
          38.6983,
          38.8097,
          36.1308,
          36.3177,
          34.814,
          37.5367,
          39.1747,
          34.227,
          42.606,
          40.8483,
          36.4542,
          37.2935,
          36.4393,
          35.5087,
          37.3975,
          34.9612,
          37.3195,
          32.4392,
          38.4003,
          42.4447,
          42.4255,
          39.6462,
          36.7547,
          35.0172,
          34.307,
          34.5657,
          40.3037,
          38.7952,
          42.1058,
          39.0263,
          35.5193,
          34.2732,
          35.9873,
          37.1863,
          34.064,
          40.3043,
          40.427,
          34.6453,
          32.7274,
          32.7648,
          32.5844,
          39.9463,
          32.593,
          32.7097,
          37.6705,
          33.9332,
          32.798,
          32.7354,
          32.8,
          36.736,
          36.2118,
          38.6722,
          38.6812,
          38.8917,
          35.7065,
          35.075,
          34.7067,
          35.0917,
          38.6645,
          35.102,
          36.5065,
          40.8965,
          36.1682,
          40.6847,
          38.8207,
          39.2688,
          35.488,
          39.5768,
          34.86,
          35.0497,
          36.3868,
          40.9645,
          45.3533,
          36.5657,
          35.4378,
          39.5287,
          39.5443,
          39.5177,
          39.5227,
          38.7932,
          38.67,
          36.0655,
          38.723,
          38.8497,
          38.8542,
          36.962,
          37.0198,
          34.1567,
          39.1557,
          37.1412,
          34.8122,
          34.256,
          34.2377,
          37.5233,
          34.29,
          33.8425,
          36.7492,
          41.4755,
          34.3677,
          36.0875,
          36.012,
          39.626,
          37.4425,
          37.4898,
          38.3513,
          38.1943,
          35.1108,
          37.9012,
          34.2365,
          40.7475,
          40.8823,
          36.3147,
          35.5152,
          35.3738,
          38.3427,
          39.1045,
          35.164,
          38.3922,
          35.24,
          38.3553,
          35.1038,
          39.0577,
          39.106,
          38.4143,
          38.3578,
          38.27,
          38.3897,
          34.1502,
          34.2668,
          34.1563,
          34.122,
          34.1598,
          34.2157,
          38.4658,
          39.3552,
          36.7083,
          39.3353,
          38.2457,
          38.7885,
          38.1945,
          35.0137,
          38.0163,
          39.9533,
          37.8073,
          37.8917,
          37.8342,
          35.681,
          35.5952,
          37.9468,
          38.5088,
          35.9945,
          36.2405,
          34.8897,
          36.5012,
          39.1718,
          36.3563,
          33.7758,
          36.3752,
          36.3305,
          36.3828,
          35.2082,
          35.1293,
          35.0113,
          34.4782,
          40.8413,
          37.6612,
          37.8718,
          39.8053,
          34.8107,
          35.1003,
          35.1918,
          35.289,
          39.0475,
          40.0363,
          36.0663,
          35.1603,
          41.1763,
          38.1503,
          38.8018,
          37.5815,
          35.0497,
          40.8193,
          38.418,
          34.3552,
          35.835,
          40.8175,
          45.5443,
          38.3535,
          42.17,
          35.8503,
          38.3003,
          38.4913,
          39.3728,
          39.3647,
          37.9925,
          38.0445,
          37.9947,
          38.1788,
          38.2775,
          38.1487,
          38.0818,
          38.1825,
          38.0568,
          37.2465,
          37.9575,
          38.1555,
          38.0297,
          38.4542,
          38.0183,
          38.0372,
          38.0775,
          38.0648,
          38.8358,
          37.83,
          38.1403,
          38.0708,
          38.2535,
          36.0077,
          38.0187,
          37.8942,
          38.15,
          38.1005
         ],
         "legendgroup": "",
         "lon": [
          27.8038,
          29.6237,
          43.6793,
          29.6212,
          40.8497,
          40.891,
          40.7853,
          40.843,
          33.089,
          25.2675,
          26.5582,
          26.5268,
          26.6152,
          26.5818,
          38.814,
          40.8577,
          27.181,
          26.9398,
          27.9843,
          28.9947,
          39.0612,
          39.3212,
          41.0402,
          26.1525,
          26.9903,
          29.2325,
          25.6762,
          25.5777,
          33.0457,
          33.0902,
          24.7305,
          27.853,
          23.7208,
          38.5027,
          25.7602,
          26.1897,
          28.3895,
          25.2318,
          28.7405,
          31.4507,
          40.0998,
          40.066,
          40.1187,
          40.1433,
          40.1382,
          26.3332,
          42.6068,
          25.3965,
          26.6332,
          27.1078,
          29.0882,
          39.6195,
          27.7388,
          38.8423,
          43.5468,
          43.427,
          43.5952,
          43.4462,
          43.3003,
          43.0775,
          43.932,
          43.5577,
          43.087,
          43.2342,
          43.1578,
          26.2345,
          25.0455,
          25.1792,
          43.9468,
          22.5735,
          29.0918,
          34.1332,
          23.0912,
          27.921,
          28.9047,
          42.3248,
          28.9413,
          28.9858,
          42.9357,
          24.1078,
          37.1155,
          30.906,
          47.0928,
          41.0165,
          40.9522,
          25.4833,
          43.4402,
          24.1425,
          25.015,
          25.1382,
          25.7803,
          22.5712,
          45.6373,
          41.4258,
          23.2283,
          45.3755,
          31.2785,
          23.6807,
          25.9295,
          25.458,
          26.2398,
          28.4212,
          47.8498,
          47.858,
          47.7931,
          23.4982,
          47.8,
          47.6397,
          30.6183,
          45.1172,
          47.6583,
          47.6748,
          46.87,
          23.6692,
          30.9268,
          23.4262,
          23.4573,
          26.2603,
          26.6533,
          26.9095,
          32.3415,
          26.7982,
          23.4518,
          26.7337,
          35.0727,
          47.8302,
          29.8952,
          36.6897,
          37.8458,
          40.2195,
          27.3933,
          34.359,
          26.29,
          39.0992,
          27.5877,
          22.7455,
          26.5457,
          26.9275,
          26.4485,
          26.099,
          26.1068,
          26.116,
          26.1148,
          29.0535,
          27.58,
          27.4463,
          27.8303,
          26.26,
          26.4365,
          27.4053,
          27.6033,
          23.9122,
          24.2575,
          28.6097,
          45.4803,
          44.9928,
          45.5305,
          38.5022,
          45.78,
          46.5897,
          21.3862,
          46.824,
          25.5772,
          31.145,
          28.0917,
          26.4387,
          29.44,
          29.3933,
          39.1585,
          23.5992,
          27.801,
          29.595,
          26.2845,
          32.9705,
          28.2095,
          28.5437,
          23.008,
          26.5032,
          38.9853,
          27.8383,
          27.8722,
          39.0847,
          27.8698,
          39.1012,
          27.8682,
          27.839,
          27.8257,
          44.4925,
          44.5345,
          38.776,
          39.0925,
          25.5277,
          25.6977,
          25.7505,
          25.547,
          25.5772,
          25.5263,
          44.1668,
          40.7597,
          28.2475,
          40.7577,
          38.74,
          27.7937,
          38.727,
          25.294,
          34.0815,
          24.345,
          26.7305,
          26.7108,
          26.8578,
          26.2272,
          45.2815,
          41.6892,
          39.2165,
          31.8,
          41.089,
          33.7372,
          27.0728,
          40.2232,
          27.0483,
          39.7635,
          27.0002,
          26.9582,
          26.9755,
          25.2642,
          25.2252,
          26.3135,
          28.3707,
          31.031,
          25.9855,
          32.1197,
          41.916,
          25.1173,
          26.9293,
          26.9537,
          32.1068,
          35.9318,
          24.3413,
          31.2102,
          32.0237,
          43.9798,
          38.6062,
          43.6332,
          26.7897,
          26.4552,
          42.8227,
          44.981,
          26.2498,
          26.4292,
          30.9868,
          26.476,
          27.1907,
          46.3403,
          28.4935,
          45.336,
          44.8007,
          26.2807,
          26.2407,
          34.0147,
          36.2933,
          37.6197,
          37.9933,
          38.14,
          37.7812,
          37.1773,
          38.2932,
          36.5238,
          37.0335,
          36.4545,
          37.5443,
          36.4765,
          37.7935,
          37.6265,
          37.0667,
          36.6112,
          36.4788,
          38.0798,
          37.629,
          38.5188,
          37.0447,
          38.2932,
          36.131,
          36.482,
          37.6138,
          38.6052,
          36.6337
         ],
         "marker": {
          "color": "white"
         },
         "mode": "markers",
         "name": "",
         "showlegend": false,
         "subplot": "mapbox",
         "type": "scattermapbox"
        }
       ],
       "layout": {
        "height": 800,
        "legend": {
         "tracegroupgap": 0
        },
        "mapbox": {
         "center": {
          "lat": 37.48347412587411,
          "lon": 33.05566328671326
         },
         "domain": {
          "x": [
           0,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "layers": [
          {
           "below": "traces",
           "source": [
            "https://basemap.nationalmap.gov/arcgis/rest/services/USGSImageryOnly/MapServer/tile/{z}/{y}/{x}"
           ],
           "sourceattribution": "United States Geological Survey",
           "sourcetype": "raster"
          }
         ],
         "style": "white-bg",
         "zoom": 5
        },
        "margin": {
         "b": 0,
         "l": 0,
         "r": 0,
         "t": 0
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.scatter_mapbox(mag_, lat=\"LAT\", lon=\"LNG\", hover_name=\"LOCATION_\", hover_data=[\"DEPTH\", \"MAG\",\"Date\"],\n",
    "                        color_discrete_sequence=[\"white\"], zoom=5, height=800)\n",
    "fig.update_layout(\n",
    "    mapbox_style=\"white-bg\",\n",
    "    mapbox_layers=[\n",
    "        {\n",
    "            \"below\": 'traces',\n",
    "            \"sourcetype\": \"raster\",\n",
    "            \"sourceattribution\": \"United States Geological Survey\",\n",
    "            \"source\": [\n",
    "                \"https://basemap.nationalmap.gov/arcgis/rest/services/USGSImageryOnly/MapServer/tile/{z}/{y}/{x}\"\n",
    "            ]\n",
    "        }\n",
    "      ])\n",
    "fig.update_layout(margin={\"r\":0,\"t\":0,\"l\":0,\"b\":0})\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mag_ = df[df['MAG'] > 5]\n",
    "\n",
    "deprem_sayisi = mag_['year'].value_counts().sort_index()\n",
    "\n",
    "# Çizgi grafiği oluşturma\n",
    "plt.plot(deprem_sayisi.index, deprem_sayisi.values, marker='o')\n",
    "plt.xlabel('Yıl')\n",
    "plt.ylabel('Deprem Sayısı')\n",
    "plt.title('Yıl İçinde Gerçekleşen Deprem Sayısı')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2005    16\n",
       "2006     4\n",
       "2007    10\n",
       "2008     5\n",
       "2009     5\n",
       "2010     6\n",
       "2011    20\n",
       "2012    19\n",
       "2013    12\n",
       "2014    21\n",
       "2015    13\n",
       "2016     7\n",
       "2017    19\n",
       "2018     7\n",
       "2019    15\n",
       "2020    36\n",
       "2021    20\n",
       "2022    18\n",
       "2023    33\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deprem_sayisi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import LSTM, Dense\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([16.,  4., 10.,  5.,  5.,  6., 20., 19., 12., 21., 13.,  7., 19.,\n",
       "        7., 15., 36., 20., 18., 33.], dtype=float32)"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deprem_sayisi = mag_.groupby('year').size()\n",
    "deprem_sayisi = deprem_sayisi.values.astype('float32')\n",
    "deprem_sayisi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Veriyi ölçeklendirin\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "deprem_sayisi = scaler.fit_transform(deprem_sayisi.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Eğitim ve test veri setlerini ayırın\n",
    "train_size = int(len(deprem_sayisi) * 0.8)\n",
    "test_size = len(deprem_sayisi) - train_size\n",
    "train, test = deprem_sayisi[0:train_size, :], deprem_sayisi[train_size:len(deprem_sayisi), :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Veriyi LSTM modeli için uygun hale getirin\n",
    "def create_dataset(dataset, look_back=1):\n",
    "    dataX, dataY = [], []\n",
    "    for i in range(len(dataset) - look_back - 1):\n",
    "        a = dataset[i:(i + look_back), 0]\n",
    "        dataX.append(a)\n",
    "        dataY.append(dataset[i + look_back, 0])\n",
    "    return np.array(dataX), np.array(dataY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "look_back = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainX, trainY = create_dataset(train, look_back)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "testX, testY = create_dataset(test, look_back)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n",
      "13/13 - 6s - loss: 0.1215 - 6s/epoch - 461ms/step\n",
      "Epoch 2/1000\n",
      "13/13 - 0s - loss: 0.1103 - 56ms/epoch - 4ms/step\n",
      "Epoch 3/1000\n",
      "13/13 - 0s - loss: 0.1019 - 80ms/epoch - 6ms/step\n",
      "Epoch 4/1000\n",
      "13/13 - 0s - loss: 0.0936 - 70ms/epoch - 5ms/step\n",
      "Epoch 5/1000\n",
      "13/13 - 0s - loss: 0.0860 - 45ms/epoch - 3ms/step\n",
      "Epoch 6/1000\n",
      "13/13 - 0s - loss: 0.0805 - 48ms/epoch - 4ms/step\n",
      "Epoch 7/1000\n",
      "13/13 - 0s - loss: 0.0743 - 43ms/epoch - 3ms/step\n",
      "Epoch 8/1000\n",
      "13/13 - 0s - loss: 0.0700 - 52ms/epoch - 4ms/step\n",
      "Epoch 9/1000\n",
      "13/13 - 0s - loss: 0.0656 - 47ms/epoch - 4ms/step\n",
      "Epoch 10/1000\n",
      "13/13 - 0s - loss: 0.0620 - 42ms/epoch - 3ms/step\n",
      "Epoch 11/1000\n",
      "13/13 - 0s - loss: 0.0597 - 43ms/epoch - 3ms/step\n",
      "Epoch 12/1000\n",
      "13/13 - 0s - loss: 0.0558 - 54ms/epoch - 4ms/step\n",
      "Epoch 13/1000\n",
      "13/13 - 0s - loss: 0.0535 - 45ms/epoch - 3ms/step\n",
      "Epoch 14/1000\n",
      "13/13 - 0s - loss: 0.0514 - 50ms/epoch - 4ms/step\n",
      "Epoch 15/1000\n",
      "13/13 - 0s - loss: 0.0494 - 46ms/epoch - 4ms/step\n",
      "Epoch 16/1000\n",
      "13/13 - 0s - loss: 0.0485 - 71ms/epoch - 5ms/step\n",
      "Epoch 17/1000\n",
      "13/13 - 0s - loss: 0.0463 - 45ms/epoch - 3ms/step\n",
      "Epoch 18/1000\n",
      "13/13 - 0s - loss: 0.0451 - 40ms/epoch - 3ms/step\n",
      "Epoch 19/1000\n",
      "13/13 - 0s - loss: 0.0442 - 48ms/epoch - 4ms/step\n",
      "Epoch 20/1000\n",
      "13/13 - 0s - loss: 0.0436 - 41ms/epoch - 3ms/step\n",
      "Epoch 21/1000\n",
      "13/13 - 0s - loss: 0.0425 - 59ms/epoch - 5ms/step\n",
      "Epoch 22/1000\n",
      "13/13 - 0s - loss: 0.0417 - 49ms/epoch - 4ms/step\n",
      "Epoch 23/1000\n",
      "13/13 - 0s - loss: 0.0411 - 44ms/epoch - 3ms/step\n",
      "Epoch 24/1000\n",
      "13/13 - 0s - loss: 0.0406 - 54ms/epoch - 4ms/step\n",
      "Epoch 25/1000\n",
      "13/13 - 0s - loss: 0.0404 - 46ms/epoch - 4ms/step\n",
      "Epoch 26/1000\n",
      "13/13 - 0s - loss: 0.0399 - 47ms/epoch - 4ms/step\n",
      "Epoch 27/1000\n",
      "13/13 - 0s - loss: 0.0396 - 43ms/epoch - 3ms/step\n",
      "Epoch 28/1000\n",
      "13/13 - 0s - loss: 0.0394 - 49ms/epoch - 4ms/step\n",
      "Epoch 29/1000\n",
      "13/13 - 0s - loss: 0.0391 - 42ms/epoch - 3ms/step\n",
      "Epoch 30/1000\n",
      "13/13 - 0s - loss: 0.0390 - 39ms/epoch - 3ms/step\n",
      "Epoch 31/1000\n",
      "13/13 - 0s - loss: 0.0388 - 43ms/epoch - 3ms/step\n",
      "Epoch 32/1000\n",
      "13/13 - 0s - loss: 0.0387 - 46ms/epoch - 4ms/step\n",
      "Epoch 33/1000\n",
      "13/13 - 0s - loss: 0.0385 - 40ms/epoch - 3ms/step\n",
      "Epoch 34/1000\n",
      "13/13 - 0s - loss: 0.0385 - 41ms/epoch - 3ms/step\n",
      "Epoch 35/1000\n",
      "13/13 - 0s - loss: 0.0384 - 51ms/epoch - 4ms/step\n",
      "Epoch 36/1000\n",
      "13/13 - 0s - loss: 0.0384 - 41ms/epoch - 3ms/step\n",
      "Epoch 37/1000\n",
      "13/13 - 0s - loss: 0.0383 - 35ms/epoch - 3ms/step\n",
      "Epoch 38/1000\n",
      "13/13 - 0s - loss: 0.0382 - 44ms/epoch - 3ms/step\n",
      "Epoch 39/1000\n",
      "13/13 - 0s - loss: 0.0382 - 47ms/epoch - 4ms/step\n",
      "Epoch 40/1000\n",
      "13/13 - 0s - loss: 0.0381 - 46ms/epoch - 4ms/step\n",
      "Epoch 41/1000\n",
      "13/13 - 0s - loss: 0.0382 - 49ms/epoch - 4ms/step\n",
      "Epoch 42/1000\n",
      "13/13 - 0s - loss: 0.0382 - 43ms/epoch - 3ms/step\n",
      "Epoch 43/1000\n",
      "13/13 - 0s - loss: 0.0380 - 49ms/epoch - 4ms/step\n",
      "Epoch 44/1000\n",
      "13/13 - 0s - loss: 0.0380 - 58ms/epoch - 4ms/step\n",
      "Epoch 45/1000\n",
      "13/13 - 0s - loss: 0.0381 - 68ms/epoch - 5ms/step\n",
      "Epoch 46/1000\n",
      "13/13 - 0s - loss: 0.0380 - 72ms/epoch - 6ms/step\n",
      "Epoch 47/1000\n",
      "13/13 - 0s - loss: 0.0380 - 55ms/epoch - 4ms/step\n",
      "Epoch 48/1000\n",
      "13/13 - 0s - loss: 0.0379 - 45ms/epoch - 3ms/step\n",
      "Epoch 49/1000\n",
      "13/13 - 0s - loss: 0.0379 - 51ms/epoch - 4ms/step\n",
      "Epoch 50/1000\n",
      "13/13 - 0s - loss: 0.0380 - 40ms/epoch - 3ms/step\n",
      "Epoch 51/1000\n",
      "13/13 - 0s - loss: 0.0379 - 32ms/epoch - 2ms/step\n",
      "Epoch 52/1000\n",
      "13/13 - 0s - loss: 0.0383 - 41ms/epoch - 3ms/step\n",
      "Epoch 53/1000\n",
      "13/13 - 0s - loss: 0.0380 - 43ms/epoch - 3ms/step\n",
      "Epoch 54/1000\n",
      "13/13 - 0s - loss: 0.0379 - 43ms/epoch - 3ms/step\n",
      "Epoch 55/1000\n",
      "13/13 - 0s - loss: 0.0379 - 34ms/epoch - 3ms/step\n",
      "Epoch 56/1000\n",
      "13/13 - 0s - loss: 0.0379 - 48ms/epoch - 4ms/step\n",
      "Epoch 57/1000\n",
      "13/13 - 0s - loss: 0.0379 - 45ms/epoch - 3ms/step\n",
      "Epoch 58/1000\n",
      "13/13 - 0s - loss: 0.0379 - 48ms/epoch - 4ms/step\n",
      "Epoch 59/1000\n",
      "13/13 - 0s - loss: 0.0378 - 38ms/epoch - 3ms/step\n",
      "Epoch 60/1000\n",
      "13/13 - 0s - loss: 0.0378 - 53ms/epoch - 4ms/step\n",
      "Epoch 61/1000\n",
      "13/13 - 0s - loss: 0.0378 - 44ms/epoch - 3ms/step\n",
      "Epoch 62/1000\n",
      "13/13 - 0s - loss: 0.0378 - 36ms/epoch - 3ms/step\n",
      "Epoch 63/1000\n",
      "13/13 - 0s - loss: 0.0377 - 44ms/epoch - 3ms/step\n",
      "Epoch 64/1000\n",
      "13/13 - 0s - loss: 0.0378 - 47ms/epoch - 4ms/step\n",
      "Epoch 65/1000\n",
      "13/13 - 0s - loss: 0.0381 - 46ms/epoch - 4ms/step\n",
      "Epoch 66/1000\n",
      "13/13 - 0s - loss: 0.0377 - 40ms/epoch - 3ms/step\n",
      "Epoch 67/1000\n",
      "13/13 - 0s - loss: 0.0378 - 41ms/epoch - 3ms/step\n",
      "Epoch 68/1000\n",
      "13/13 - 0s - loss: 0.0379 - 46ms/epoch - 4ms/step\n",
      "Epoch 69/1000\n",
      "13/13 - 0s - loss: 0.0376 - 47ms/epoch - 4ms/step\n",
      "Epoch 70/1000\n",
      "13/13 - 0s - loss: 0.0377 - 44ms/epoch - 3ms/step\n",
      "Epoch 71/1000\n",
      "13/13 - 0s - loss: 0.0377 - 36ms/epoch - 3ms/step\n",
      "Epoch 72/1000\n",
      "13/13 - 0s - loss: 0.0378 - 41ms/epoch - 3ms/step\n",
      "Epoch 73/1000\n",
      "13/13 - 0s - loss: 0.0377 - 50ms/epoch - 4ms/step\n",
      "Epoch 74/1000\n",
      "13/13 - 0s - loss: 0.0377 - 36ms/epoch - 3ms/step\n",
      "Epoch 75/1000\n",
      "13/13 - 0s - loss: 0.0377 - 36ms/epoch - 3ms/step\n",
      "Epoch 76/1000\n",
      "13/13 - 0s - loss: 0.0376 - 72ms/epoch - 6ms/step\n",
      "Epoch 77/1000\n",
      "13/13 - 0s - loss: 0.0377 - 50ms/epoch - 4ms/step\n",
      "Epoch 78/1000\n",
      "13/13 - 0s - loss: 0.0377 - 43ms/epoch - 3ms/step\n",
      "Epoch 79/1000\n",
      "13/13 - 0s - loss: 0.0376 - 50ms/epoch - 4ms/step\n",
      "Epoch 80/1000\n",
      "13/13 - 0s - loss: 0.0378 - 44ms/epoch - 3ms/step\n",
      "Epoch 81/1000\n",
      "13/13 - 0s - loss: 0.0375 - 45ms/epoch - 3ms/step\n",
      "Epoch 82/1000\n",
      "13/13 - 0s - loss: 0.0376 - 44ms/epoch - 3ms/step\n",
      "Epoch 83/1000\n",
      "13/13 - 0s - loss: 0.0377 - 44ms/epoch - 3ms/step\n",
      "Epoch 84/1000\n",
      "13/13 - 0s - loss: 0.0376 - 46ms/epoch - 4ms/step\n",
      "Epoch 85/1000\n",
      "13/13 - 0s - loss: 0.0377 - 42ms/epoch - 3ms/step\n",
      "Epoch 86/1000\n",
      "13/13 - 0s - loss: 0.0375 - 40ms/epoch - 3ms/step\n",
      "Epoch 87/1000\n",
      "13/13 - 0s - loss: 0.0375 - 46ms/epoch - 4ms/step\n",
      "Epoch 88/1000\n",
      "13/13 - 0s - loss: 0.0376 - 43ms/epoch - 3ms/step\n",
      "Epoch 89/1000\n",
      "13/13 - 0s - loss: 0.0376 - 41ms/epoch - 3ms/step\n",
      "Epoch 90/1000\n",
      "13/13 - 0s - loss: 0.0375 - 41ms/epoch - 3ms/step\n",
      "Epoch 91/1000\n",
      "13/13 - 0s - loss: 0.0376 - 45ms/epoch - 3ms/step\n",
      "Epoch 92/1000\n",
      "13/13 - 0s - loss: 0.0375 - 53ms/epoch - 4ms/step\n",
      "Epoch 93/1000\n",
      "13/13 - 0s - loss: 0.0375 - 42ms/epoch - 3ms/step\n",
      "Epoch 94/1000\n",
      "13/13 - 0s - loss: 0.0375 - 38ms/epoch - 3ms/step\n",
      "Epoch 95/1000\n",
      "13/13 - 0s - loss: 0.0375 - 45ms/epoch - 3ms/step\n",
      "Epoch 96/1000\n",
      "13/13 - 0s - loss: 0.0375 - 45ms/epoch - 3ms/step\n",
      "Epoch 97/1000\n",
      "13/13 - 0s - loss: 0.0375 - 45ms/epoch - 3ms/step\n",
      "Epoch 98/1000\n",
      "13/13 - 0s - loss: 0.0375 - 39ms/epoch - 3ms/step\n",
      "Epoch 99/1000\n",
      "13/13 - 0s - loss: 0.0375 - 43ms/epoch - 3ms/step\n",
      "Epoch 100/1000\n",
      "13/13 - 0s - loss: 0.0374 - 39ms/epoch - 3ms/step\n",
      "Epoch 101/1000\n",
      "13/13 - 0s - loss: 0.0374 - 31ms/epoch - 2ms/step\n",
      "Epoch 102/1000\n",
      "13/13 - 0s - loss: 0.0375 - 40ms/epoch - 3ms/step\n",
      "Epoch 103/1000\n",
      "13/13 - 0s - loss: 0.0374 - 40ms/epoch - 3ms/step\n",
      "Epoch 104/1000\n",
      "13/13 - 0s - loss: 0.0375 - 38ms/epoch - 3ms/step\n",
      "Epoch 105/1000\n",
      "13/13 - 0s - loss: 0.0375 - 45ms/epoch - 3ms/step\n",
      "Epoch 106/1000\n",
      "13/13 - 0s - loss: 0.0374 - 39ms/epoch - 3ms/step\n",
      "Epoch 107/1000\n",
      "13/13 - 0s - loss: 0.0374 - 51ms/epoch - 4ms/step\n",
      "Epoch 108/1000\n",
      "13/13 - 0s - loss: 0.0374 - 45ms/epoch - 3ms/step\n",
      "Epoch 109/1000\n",
      "13/13 - 0s - loss: 0.0374 - 48ms/epoch - 4ms/step\n",
      "Epoch 110/1000\n",
      "13/13 - 0s - loss: 0.0374 - 45ms/epoch - 3ms/step\n",
      "Epoch 111/1000\n",
      "13/13 - 0s - loss: 0.0374 - 50ms/epoch - 4ms/step\n",
      "Epoch 112/1000\n",
      "13/13 - 0s - loss: 0.0374 - 48ms/epoch - 4ms/step\n",
      "Epoch 113/1000\n",
      "13/13 - 0s - loss: 0.0373 - 61ms/epoch - 5ms/step\n",
      "Epoch 114/1000\n",
      "13/13 - 0s - loss: 0.0375 - 58ms/epoch - 4ms/step\n",
      "Epoch 115/1000\n",
      "13/13 - 0s - loss: 0.0375 - 60ms/epoch - 5ms/step\n",
      "Epoch 116/1000\n",
      "13/13 - 0s - loss: 0.0373 - 61ms/epoch - 5ms/step\n",
      "Epoch 117/1000\n",
      "13/13 - 0s - loss: 0.0373 - 48ms/epoch - 4ms/step\n",
      "Epoch 118/1000\n",
      "13/13 - 0s - loss: 0.0374 - 46ms/epoch - 4ms/step\n",
      "Epoch 119/1000\n",
      "13/13 - 0s - loss: 0.0374 - 41ms/epoch - 3ms/step\n",
      "Epoch 120/1000\n",
      "13/13 - 0s - loss: 0.0374 - 42ms/epoch - 3ms/step\n",
      "Epoch 121/1000\n",
      "13/13 - 0s - loss: 0.0374 - 57ms/epoch - 4ms/step\n",
      "Epoch 122/1000\n",
      "13/13 - 0s - loss: 0.0374 - 46ms/epoch - 4ms/step\n",
      "Epoch 123/1000\n",
      "13/13 - 0s - loss: 0.0375 - 44ms/epoch - 3ms/step\n",
      "Epoch 124/1000\n",
      "13/13 - 0s - loss: 0.0375 - 39ms/epoch - 3ms/step\n",
      "Epoch 125/1000\n",
      "13/13 - 0s - loss: 0.0375 - 38ms/epoch - 3ms/step\n",
      "Epoch 126/1000\n",
      "13/13 - 0s - loss: 0.0374 - 37ms/epoch - 3ms/step\n",
      "Epoch 127/1000\n",
      "13/13 - 0s - loss: 0.0373 - 37ms/epoch - 3ms/step\n",
      "Epoch 128/1000\n",
      "13/13 - 0s - loss: 0.0373 - 41ms/epoch - 3ms/step\n",
      "Epoch 129/1000\n",
      "13/13 - 0s - loss: 0.0373 - 41ms/epoch - 3ms/step\n",
      "Epoch 130/1000\n",
      "13/13 - 0s - loss: 0.0374 - 42ms/epoch - 3ms/step\n",
      "Epoch 131/1000\n",
      "13/13 - 0s - loss: 0.0373 - 44ms/epoch - 3ms/step\n",
      "Epoch 132/1000\n",
      "13/13 - 0s - loss: 0.0373 - 37ms/epoch - 3ms/step\n",
      "Epoch 133/1000\n",
      "13/13 - 0s - loss: 0.0374 - 39ms/epoch - 3ms/step\n",
      "Epoch 134/1000\n",
      "13/13 - 0s - loss: 0.0372 - 57ms/epoch - 4ms/step\n",
      "Epoch 135/1000\n",
      "13/13 - 0s - loss: 0.0377 - 44ms/epoch - 3ms/step\n",
      "Epoch 136/1000\n",
      "13/13 - 0s - loss: 0.0372 - 48ms/epoch - 4ms/step\n",
      "Epoch 137/1000\n",
      "13/13 - 0s - loss: 0.0373 - 60ms/epoch - 5ms/step\n",
      "Epoch 138/1000\n",
      "13/13 - 0s - loss: 0.0372 - 59ms/epoch - 5ms/step\n",
      "Epoch 139/1000\n",
      "13/13 - 0s - loss: 0.0374 - 47ms/epoch - 4ms/step\n",
      "Epoch 140/1000\n",
      "13/13 - 0s - loss: 0.0372 - 49ms/epoch - 4ms/step\n",
      "Epoch 141/1000\n",
      "13/13 - 0s - loss: 0.0372 - 47ms/epoch - 4ms/step\n",
      "Epoch 142/1000\n",
      "13/13 - 0s - loss: 0.0373 - 54ms/epoch - 4ms/step\n",
      "Epoch 143/1000\n",
      "13/13 - 0s - loss: 0.0372 - 50ms/epoch - 4ms/step\n",
      "Epoch 144/1000\n",
      "13/13 - 0s - loss: 0.0372 - 46ms/epoch - 4ms/step\n",
      "Epoch 145/1000\n",
      "13/13 - 0s - loss: 0.0374 - 52ms/epoch - 4ms/step\n",
      "Epoch 146/1000\n",
      "13/13 - 0s - loss: 0.0375 - 75ms/epoch - 6ms/step\n",
      "Epoch 147/1000\n",
      "13/13 - 0s - loss: 0.0372 - 43ms/epoch - 3ms/step\n",
      "Epoch 148/1000\n",
      "13/13 - 0s - loss: 0.0372 - 55ms/epoch - 4ms/step\n",
      "Epoch 149/1000\n",
      "13/13 - 0s - loss: 0.0372 - 55ms/epoch - 4ms/step\n",
      "Epoch 150/1000\n",
      "13/13 - 0s - loss: 0.0372 - 45ms/epoch - 3ms/step\n",
      "Epoch 151/1000\n",
      "13/13 - 0s - loss: 0.0373 - 43ms/epoch - 3ms/step\n",
      "Epoch 152/1000\n",
      "13/13 - 0s - loss: 0.0373 - 44ms/epoch - 3ms/step\n",
      "Epoch 153/1000\n",
      "13/13 - 0s - loss: 0.0374 - 45ms/epoch - 3ms/step\n",
      "Epoch 154/1000\n",
      "13/13 - 0s - loss: 0.0373 - 78ms/epoch - 6ms/step\n",
      "Epoch 155/1000\n",
      "13/13 - 0s - loss: 0.0371 - 50ms/epoch - 4ms/step\n",
      "Epoch 156/1000\n",
      "13/13 - 0s - loss: 0.0372 - 45ms/epoch - 3ms/step\n",
      "Epoch 157/1000\n",
      "13/13 - 0s - loss: 0.0372 - 40ms/epoch - 3ms/step\n",
      "Epoch 158/1000\n",
      "13/13 - 0s - loss: 0.0372 - 49ms/epoch - 4ms/step\n",
      "Epoch 159/1000\n",
      "13/13 - 0s - loss: 0.0373 - 42ms/epoch - 3ms/step\n",
      "Epoch 160/1000\n",
      "13/13 - 0s - loss: 0.0371 - 38ms/epoch - 3ms/step\n",
      "Epoch 161/1000\n",
      "13/13 - 0s - loss: 0.0372 - 40ms/epoch - 3ms/step\n",
      "Epoch 162/1000\n",
      "13/13 - 0s - loss: 0.0371 - 37ms/epoch - 3ms/step\n",
      "Epoch 163/1000\n",
      "13/13 - 0s - loss: 0.0371 - 51ms/epoch - 4ms/step\n",
      "Epoch 164/1000\n",
      "13/13 - 0s - loss: 0.0371 - 39ms/epoch - 3ms/step\n",
      "Epoch 165/1000\n",
      "13/13 - 0s - loss: 0.0372 - 39ms/epoch - 3ms/step\n",
      "Epoch 166/1000\n",
      "13/13 - 0s - loss: 0.0372 - 37ms/epoch - 3ms/step\n",
      "Epoch 167/1000\n",
      "13/13 - 0s - loss: 0.0372 - 53ms/epoch - 4ms/step\n",
      "Epoch 168/1000\n",
      "13/13 - 0s - loss: 0.0371 - 41ms/epoch - 3ms/step\n",
      "Epoch 169/1000\n",
      "13/13 - 0s - loss: 0.0371 - 42ms/epoch - 3ms/step\n",
      "Epoch 170/1000\n",
      "13/13 - 0s - loss: 0.0372 - 46ms/epoch - 4ms/step\n",
      "Epoch 171/1000\n",
      "13/13 - 0s - loss: 0.0371 - 44ms/epoch - 3ms/step\n",
      "Epoch 172/1000\n",
      "13/13 - 0s - loss: 0.0371 - 58ms/epoch - 4ms/step\n",
      "Epoch 173/1000\n",
      "13/13 - 0s - loss: 0.0371 - 48ms/epoch - 4ms/step\n",
      "Epoch 174/1000\n",
      "13/13 - 0s - loss: 0.0372 - 42ms/epoch - 3ms/step\n",
      "Epoch 175/1000\n",
      "13/13 - 0s - loss: 0.0371 - 62ms/epoch - 5ms/step\n",
      "Epoch 176/1000\n",
      "13/13 - 0s - loss: 0.0373 - 57ms/epoch - 4ms/step\n",
      "Epoch 177/1000\n",
      "13/13 - 0s - loss: 0.0371 - 42ms/epoch - 3ms/step\n",
      "Epoch 178/1000\n",
      "13/13 - 0s - loss: 0.0371 - 46ms/epoch - 4ms/step\n",
      "Epoch 179/1000\n",
      "13/13 - 0s - loss: 0.0371 - 46ms/epoch - 4ms/step\n",
      "Epoch 180/1000\n",
      "13/13 - 0s - loss: 0.0372 - 35ms/epoch - 3ms/step\n",
      "Epoch 181/1000\n",
      "13/13 - 0s - loss: 0.0371 - 45ms/epoch - 3ms/step\n",
      "Epoch 182/1000\n",
      "13/13 - 0s - loss: 0.0371 - 47ms/epoch - 4ms/step\n",
      "Epoch 183/1000\n",
      "13/13 - 0s - loss: 0.0372 - 37ms/epoch - 3ms/step\n",
      "Epoch 184/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 185/1000\n",
      "13/13 - 0s - loss: 0.0371 - 50ms/epoch - 4ms/step\n",
      "Epoch 186/1000\n",
      "13/13 - 0s - loss: 0.0372 - 49ms/epoch - 4ms/step\n",
      "Epoch 187/1000\n",
      "13/13 - 0s - loss: 0.0371 - 46ms/epoch - 4ms/step\n",
      "Epoch 188/1000\n",
      "13/13 - 0s - loss: 0.0371 - 43ms/epoch - 3ms/step\n",
      "Epoch 189/1000\n",
      "13/13 - 0s - loss: 0.0371 - 42ms/epoch - 3ms/step\n",
      "Epoch 190/1000\n",
      "13/13 - 0s - loss: 0.0371 - 41ms/epoch - 3ms/step\n",
      "Epoch 191/1000\n",
      "13/13 - 0s - loss: 0.0372 - 42ms/epoch - 3ms/step\n",
      "Epoch 192/1000\n",
      "13/13 - 0s - loss: 0.0370 - 35ms/epoch - 3ms/step\n",
      "Epoch 193/1000\n",
      "13/13 - 0s - loss: 0.0371 - 46ms/epoch - 4ms/step\n",
      "Epoch 194/1000\n",
      "13/13 - 0s - loss: 0.0371 - 37ms/epoch - 3ms/step\n",
      "Epoch 195/1000\n",
      "13/13 - 0s - loss: 0.0372 - 60ms/epoch - 5ms/step\n",
      "Epoch 196/1000\n",
      "13/13 - 0s - loss: 0.0371 - 59ms/epoch - 5ms/step\n",
      "Epoch 197/1000\n",
      "13/13 - 0s - loss: 0.0370 - 47ms/epoch - 4ms/step\n",
      "Epoch 198/1000\n",
      "13/13 - 0s - loss: 0.0371 - 34ms/epoch - 3ms/step\n",
      "Epoch 199/1000\n",
      "13/13 - 0s - loss: 0.0372 - 43ms/epoch - 3ms/step\n",
      "Epoch 200/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 201/1000\n",
      "13/13 - 0s - loss: 0.0371 - 36ms/epoch - 3ms/step\n",
      "Epoch 202/1000\n",
      "13/13 - 0s - loss: 0.0371 - 37ms/epoch - 3ms/step\n",
      "Epoch 203/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 204/1000\n",
      "13/13 - 0s - loss: 0.0371 - 41ms/epoch - 3ms/step\n",
      "Epoch 205/1000\n",
      "13/13 - 0s - loss: 0.0371 - 40ms/epoch - 3ms/step\n",
      "Epoch 206/1000\n",
      "13/13 - 0s - loss: 0.0370 - 52ms/epoch - 4ms/step\n",
      "Epoch 207/1000\n",
      "13/13 - 0s - loss: 0.0371 - 50ms/epoch - 4ms/step\n",
      "Epoch 208/1000\n",
      "13/13 - 0s - loss: 0.0370 - 50ms/epoch - 4ms/step\n",
      "Epoch 209/1000\n",
      "13/13 - 0s - loss: 0.0371 - 42ms/epoch - 3ms/step\n",
      "Epoch 210/1000\n",
      "13/13 - 0s - loss: 0.0372 - 42ms/epoch - 3ms/step\n",
      "Epoch 211/1000\n",
      "13/13 - 0s - loss: 0.0371 - 40ms/epoch - 3ms/step\n",
      "Epoch 212/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 213/1000\n",
      "13/13 - 0s - loss: 0.0372 - 42ms/epoch - 3ms/step\n",
      "Epoch 214/1000\n",
      "13/13 - 0s - loss: 0.0371 - 36ms/epoch - 3ms/step\n",
      "Epoch 215/1000\n",
      "13/13 - 0s - loss: 0.0373 - 46ms/epoch - 4ms/step\n",
      "Epoch 216/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 217/1000\n",
      "13/13 - 0s - loss: 0.0371 - 39ms/epoch - 3ms/step\n",
      "Epoch 218/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 219/1000\n",
      "13/13 - 0s - loss: 0.0371 - 44ms/epoch - 3ms/step\n",
      "Epoch 220/1000\n",
      "13/13 - 0s - loss: 0.0373 - 31ms/epoch - 2ms/step\n",
      "Epoch 221/1000\n",
      "13/13 - 0s - loss: 0.0371 - 45ms/epoch - 3ms/step\n",
      "Epoch 222/1000\n",
      "13/13 - 0s - loss: 0.0370 - 67ms/epoch - 5ms/step\n",
      "Epoch 223/1000\n",
      "13/13 - 0s - loss: 0.0370 - 53ms/epoch - 4ms/step\n",
      "Epoch 224/1000\n",
      "13/13 - 0s - loss: 0.0371 - 65ms/epoch - 5ms/step\n",
      "Epoch 225/1000\n",
      "13/13 - 0s - loss: 0.0370 - 60ms/epoch - 5ms/step\n",
      "Epoch 226/1000\n",
      "13/13 - 0s - loss: 0.0371 - 39ms/epoch - 3ms/step\n",
      "Epoch 227/1000\n",
      "13/13 - 0s - loss: 0.0371 - 34ms/epoch - 3ms/step\n",
      "Epoch 228/1000\n",
      "13/13 - 0s - loss: 0.0370 - 41ms/epoch - 3ms/step\n",
      "Epoch 229/1000\n",
      "13/13 - 0s - loss: 0.0370 - 46ms/epoch - 4ms/step\n",
      "Epoch 230/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 231/1000\n",
      "13/13 - 0s - loss: 0.0370 - 56ms/epoch - 4ms/step\n",
      "Epoch 232/1000\n",
      "13/13 - 0s - loss: 0.0370 - 35ms/epoch - 3ms/step\n",
      "Epoch 233/1000\n",
      "13/13 - 0s - loss: 0.0374 - 43ms/epoch - 3ms/step\n",
      "Epoch 234/1000\n",
      "13/13 - 0s - loss: 0.0371 - 40ms/epoch - 3ms/step\n",
      "Epoch 235/1000\n",
      "13/13 - 0s - loss: 0.0370 - 50ms/epoch - 4ms/step\n",
      "Epoch 236/1000\n",
      "13/13 - 0s - loss: 0.0373 - 43ms/epoch - 3ms/step\n",
      "Epoch 237/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 238/1000\n",
      "13/13 - 0s - loss: 0.0370 - 48ms/epoch - 4ms/step\n",
      "Epoch 239/1000\n",
      "13/13 - 0s - loss: 0.0369 - 65ms/epoch - 5ms/step\n",
      "Epoch 240/1000\n",
      "13/13 - 0s - loss: 0.0371 - 44ms/epoch - 3ms/step\n",
      "Epoch 241/1000\n",
      "13/13 - 0s - loss: 0.0370 - 46ms/epoch - 4ms/step\n",
      "Epoch 242/1000\n",
      "13/13 - 0s - loss: 0.0370 - 45ms/epoch - 3ms/step\n",
      "Epoch 243/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 244/1000\n",
      "13/13 - 0s - loss: 0.0371 - 40ms/epoch - 3ms/step\n",
      "Epoch 245/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 246/1000\n",
      "13/13 - 0s - loss: 0.0370 - 45ms/epoch - 3ms/step\n",
      "Epoch 247/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 248/1000\n",
      "13/13 - 0s - loss: 0.0370 - 42ms/epoch - 3ms/step\n",
      "Epoch 249/1000\n",
      "13/13 - 0s - loss: 0.0370 - 47ms/epoch - 4ms/step\n",
      "Epoch 250/1000\n",
      "13/13 - 0s - loss: 0.0370 - 43ms/epoch - 3ms/step\n",
      "Epoch 251/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 252/1000\n",
      "13/13 - 0s - loss: 0.0370 - 46ms/epoch - 4ms/step\n",
      "Epoch 253/1000\n",
      "13/13 - 0s - loss: 0.0370 - 56ms/epoch - 4ms/step\n",
      "Epoch 254/1000\n",
      "13/13 - 0s - loss: 0.0369 - 62ms/epoch - 5ms/step\n",
      "Epoch 255/1000\n",
      "13/13 - 0s - loss: 0.0370 - 67ms/epoch - 5ms/step\n",
      "Epoch 256/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 257/1000\n",
      "13/13 - 0s - loss: 0.0369 - 56ms/epoch - 4ms/step\n",
      "Epoch 258/1000\n",
      "13/13 - 0s - loss: 0.0369 - 57ms/epoch - 4ms/step\n",
      "Epoch 259/1000\n",
      "13/13 - 0s - loss: 0.0369 - 48ms/epoch - 4ms/step\n",
      "Epoch 260/1000\n",
      "13/13 - 0s - loss: 0.0371 - 48ms/epoch - 4ms/step\n",
      "Epoch 261/1000\n",
      "13/13 - 0s - loss: 0.0370 - 43ms/epoch - 3ms/step\n",
      "Epoch 262/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 263/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 264/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 265/1000\n",
      "13/13 - 0s - loss: 0.0371 - 36ms/epoch - 3ms/step\n",
      "Epoch 266/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 267/1000\n",
      "13/13 - 0s - loss: 0.0370 - 35ms/epoch - 3ms/step\n",
      "Epoch 268/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 269/1000\n",
      "13/13 - 0s - loss: 0.0370 - 41ms/epoch - 3ms/step\n",
      "Epoch 270/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 271/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 272/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 273/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 274/1000\n",
      "13/13 - 0s - loss: 0.0369 - 59ms/epoch - 5ms/step\n",
      "Epoch 275/1000\n",
      "13/13 - 0s - loss: 0.0369 - 53ms/epoch - 4ms/step\n",
      "Epoch 276/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 277/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 278/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 279/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 280/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 281/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 282/1000\n",
      "13/13 - 0s - loss: 0.0369 - 51ms/epoch - 4ms/step\n",
      "Epoch 283/1000\n",
      "13/13 - 0s - loss: 0.0370 - 51ms/epoch - 4ms/step\n",
      "Epoch 284/1000\n",
      "13/13 - 0s - loss: 0.0369 - 48ms/epoch - 4ms/step\n",
      "Epoch 285/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 286/1000\n",
      "13/13 - 0s - loss: 0.0370 - 43ms/epoch - 3ms/step\n",
      "Epoch 287/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 288/1000\n",
      "13/13 - 0s - loss: 0.0370 - 37ms/epoch - 3ms/step\n",
      "Epoch 289/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 290/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 291/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 292/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 293/1000\n",
      "13/13 - 0s - loss: 0.0372 - 38ms/epoch - 3ms/step\n",
      "Epoch 294/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 295/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 296/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 297/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 298/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 299/1000\n",
      "13/13 - 0s - loss: 0.0370 - 41ms/epoch - 3ms/step\n",
      "Epoch 300/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 301/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 302/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 303/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 304/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 305/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 306/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 307/1000\n",
      "13/13 - 0s - loss: 0.0371 - 46ms/epoch - 4ms/step\n",
      "Epoch 308/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 309/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 310/1000\n",
      "13/13 - 0s - loss: 0.0370 - 39ms/epoch - 3ms/step\n",
      "Epoch 311/1000\n",
      "13/13 - 0s - loss: 0.0370 - 42ms/epoch - 3ms/step\n",
      "Epoch 312/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 313/1000\n",
      "13/13 - 0s - loss: 0.0370 - 36ms/epoch - 3ms/step\n",
      "Epoch 314/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 315/1000\n",
      "13/13 - 0s - loss: 0.0369 - 53ms/epoch - 4ms/step\n",
      "Epoch 316/1000\n",
      "13/13 - 0s - loss: 0.0369 - 52ms/epoch - 4ms/step\n",
      "Epoch 317/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 318/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 319/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 320/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 321/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 322/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 323/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 324/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 325/1000\n",
      "13/13 - 0s - loss: 0.0369 - 34ms/epoch - 3ms/step\n",
      "Epoch 326/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 327/1000\n",
      "13/13 - 0s - loss: 0.0372 - 38ms/epoch - 3ms/step\n",
      "Epoch 328/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 329/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 330/1000\n",
      "13/13 - 0s - loss: 0.0371 - 38ms/epoch - 3ms/step\n",
      "Epoch 331/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 332/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 333/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 334/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 335/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 336/1000\n",
      "13/13 - 0s - loss: 0.0371 - 39ms/epoch - 3ms/step\n",
      "Epoch 337/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 338/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 339/1000\n",
      "13/13 - 0s - loss: 0.0369 - 70ms/epoch - 5ms/step\n",
      "Epoch 340/1000\n",
      "13/13 - 0s - loss: 0.0368 - 74ms/epoch - 6ms/step\n",
      "Epoch 341/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 342/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 343/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 344/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 345/1000\n",
      "13/13 - 0s - loss: 0.0370 - 56ms/epoch - 4ms/step\n",
      "Epoch 346/1000\n",
      "13/13 - 0s - loss: 0.0369 - 53ms/epoch - 4ms/step\n",
      "Epoch 347/1000\n",
      "13/13 - 0s - loss: 0.0369 - 45ms/epoch - 3ms/step\n",
      "Epoch 348/1000\n",
      "13/13 - 0s - loss: 0.0369 - 51ms/epoch - 4ms/step\n",
      "Epoch 349/1000\n",
      "13/13 - 0s - loss: 0.0370 - 42ms/epoch - 3ms/step\n",
      "Epoch 350/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 351/1000\n",
      "13/13 - 0s - loss: 0.0369 - 57ms/epoch - 4ms/step\n",
      "Epoch 352/1000\n",
      "13/13 - 0s - loss: 0.0369 - 48ms/epoch - 4ms/step\n",
      "Epoch 353/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 354/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 355/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 356/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 357/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 358/1000\n",
      "13/13 - 0s - loss: 0.0369 - 31ms/epoch - 2ms/step\n",
      "Epoch 359/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 360/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 361/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 362/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 363/1000\n",
      "13/13 - 0s - loss: 0.0368 - 51ms/epoch - 4ms/step\n",
      "Epoch 364/1000\n",
      "13/13 - 0s - loss: 0.0370 - 50ms/epoch - 4ms/step\n",
      "Epoch 365/1000\n",
      "13/13 - 0s - loss: 0.0370 - 50ms/epoch - 4ms/step\n",
      "Epoch 366/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 367/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 368/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 369/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 370/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 371/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 372/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 373/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 374/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 375/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 376/1000\n",
      "13/13 - 0s - loss: 0.0370 - 39ms/epoch - 3ms/step\n",
      "Epoch 377/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 378/1000\n",
      "13/13 - 0s - loss: 0.0371 - 37ms/epoch - 3ms/step\n",
      "Epoch 379/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 380/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 381/1000\n",
      "13/13 - 0s - loss: 0.0370 - 56ms/epoch - 4ms/step\n",
      "Epoch 382/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 383/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 384/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 385/1000\n",
      "13/13 - 0s - loss: 0.0370 - 37ms/epoch - 3ms/step\n",
      "Epoch 386/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 387/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 388/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 389/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 390/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 391/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 392/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 393/1000\n",
      "13/13 - 0s - loss: 0.0368 - 33ms/epoch - 3ms/step\n",
      "Epoch 394/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 395/1000\n",
      "13/13 - 0s - loss: 0.0368 - 51ms/epoch - 4ms/step\n",
      "Epoch 396/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 397/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 398/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 399/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 400/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 401/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 402/1000\n",
      "13/13 - 0s - loss: 0.0368 - 34ms/epoch - 3ms/step\n",
      "Epoch 403/1000\n",
      "13/13 - 0s - loss: 0.0368 - 34ms/epoch - 3ms/step\n",
      "Epoch 404/1000\n",
      "13/13 - 0s - loss: 0.0369 - 52ms/epoch - 4ms/step\n",
      "Epoch 405/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 406/1000\n",
      "13/13 - 0s - loss: 0.0369 - 49ms/epoch - 4ms/step\n",
      "Epoch 407/1000\n",
      "13/13 - 0s - loss: 0.0368 - 88ms/epoch - 7ms/step\n",
      "Epoch 408/1000\n",
      "13/13 - 0s - loss: 0.0368 - 53ms/epoch - 4ms/step\n",
      "Epoch 409/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 410/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 411/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 412/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 413/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 414/1000\n",
      "13/13 - 0s - loss: 0.0369 - 47ms/epoch - 4ms/step\n",
      "Epoch 415/1000\n",
      "13/13 - 0s - loss: 0.0368 - 51ms/epoch - 4ms/step\n",
      "Epoch 416/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 417/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 418/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 419/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 420/1000\n",
      "13/13 - 0s - loss: 0.0370 - 37ms/epoch - 3ms/step\n",
      "Epoch 421/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 422/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 423/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 424/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 425/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 426/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 427/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 428/1000\n",
      "13/13 - 0s - loss: 0.0370 - 36ms/epoch - 3ms/step\n",
      "Epoch 429/1000\n",
      "13/13 - 0s - loss: 0.0370 - 36ms/epoch - 3ms/step\n",
      "Epoch 430/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 431/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 432/1000\n",
      "13/13 - 0s - loss: 0.0370 - 39ms/epoch - 3ms/step\n",
      "Epoch 433/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 434/1000\n",
      "13/13 - 0s - loss: 0.0371 - 45ms/epoch - 3ms/step\n",
      "Epoch 435/1000\n",
      "13/13 - 0s - loss: 0.0371 - 37ms/epoch - 3ms/step\n",
      "Epoch 436/1000\n",
      "13/13 - 0s - loss: 0.0369 - 58ms/epoch - 4ms/step\n",
      "Epoch 437/1000\n",
      "13/13 - 0s - loss: 0.0369 - 49ms/epoch - 4ms/step\n",
      "Epoch 438/1000\n",
      "13/13 - 0s - loss: 0.0371 - 59ms/epoch - 5ms/step\n",
      "Epoch 439/1000\n",
      "13/13 - 0s - loss: 0.0369 - 51ms/epoch - 4ms/step\n",
      "Epoch 440/1000\n",
      "13/13 - 0s - loss: 0.0369 - 61ms/epoch - 5ms/step\n",
      "Epoch 441/1000\n",
      "13/13 - 0s - loss: 0.0368 - 52ms/epoch - 4ms/step\n",
      "Epoch 442/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 443/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 444/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 445/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 446/1000\n",
      "13/13 - 0s - loss: 0.0370 - 42ms/epoch - 3ms/step\n",
      "Epoch 447/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 448/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 449/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 450/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 451/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 452/1000\n",
      "13/13 - 0s - loss: 0.0370 - 41ms/epoch - 3ms/step\n",
      "Epoch 453/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 454/1000\n",
      "13/13 - 0s - loss: 0.0369 - 55ms/epoch - 4ms/step\n",
      "Epoch 455/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 456/1000\n",
      "13/13 - 0s - loss: 0.0368 - 71ms/epoch - 5ms/step\n",
      "Epoch 457/1000\n",
      "13/13 - 0s - loss: 0.0369 - 68ms/epoch - 5ms/step\n",
      "Epoch 458/1000\n",
      "13/13 - 0s - loss: 0.0368 - 56ms/epoch - 4ms/step\n",
      "Epoch 459/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 460/1000\n",
      "13/13 - 0s - loss: 0.0368 - 56ms/epoch - 4ms/step\n",
      "Epoch 461/1000\n",
      "13/13 - 0s - loss: 0.0369 - 54ms/epoch - 4ms/step\n",
      "Epoch 462/1000\n",
      "13/13 - 0s - loss: 0.0369 - 51ms/epoch - 4ms/step\n",
      "Epoch 463/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 464/1000\n",
      "13/13 - 0s - loss: 0.0368 - 55ms/epoch - 4ms/step\n",
      "Epoch 465/1000\n",
      "13/13 - 0s - loss: 0.0369 - 49ms/epoch - 4ms/step\n",
      "Epoch 466/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 467/1000\n",
      "13/13 - 0s - loss: 0.0370 - 48ms/epoch - 4ms/step\n",
      "Epoch 468/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 469/1000\n",
      "13/13 - 0s - loss: 0.0368 - 54ms/epoch - 4ms/step\n",
      "Epoch 470/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 471/1000\n",
      "13/13 - 0s - loss: 0.0373 - 57ms/epoch - 4ms/step\n",
      "Epoch 472/1000\n",
      "13/13 - 0s - loss: 0.0369 - 69ms/epoch - 5ms/step\n",
      "Epoch 473/1000\n",
      "13/13 - 0s - loss: 0.0368 - 72ms/epoch - 6ms/step\n",
      "Epoch 474/1000\n",
      "13/13 - 0s - loss: 0.0370 - 71ms/epoch - 5ms/step\n",
      "Epoch 475/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 476/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 477/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 478/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 479/1000\n",
      "13/13 - 0s - loss: 0.0369 - 47ms/epoch - 4ms/step\n",
      "Epoch 480/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 481/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 482/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 483/1000\n",
      "13/13 - 0s - loss: 0.0372 - 41ms/epoch - 3ms/step\n",
      "Epoch 484/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 485/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 486/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 487/1000\n",
      "13/13 - 0s - loss: 0.0368 - 55ms/epoch - 4ms/step\n",
      "Epoch 488/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 489/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 490/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 491/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 492/1000\n",
      "13/13 - 0s - loss: 0.0370 - 45ms/epoch - 3ms/step\n",
      "Epoch 493/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 494/1000\n",
      "13/13 - 0s - loss: 0.0371 - 50ms/epoch - 4ms/step\n",
      "Epoch 495/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 496/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 497/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 498/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 499/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 500/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 501/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 502/1000\n",
      "13/13 - 0s - loss: 0.0368 - 32ms/epoch - 2ms/step\n",
      "Epoch 503/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 504/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 505/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 506/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 507/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 508/1000\n",
      "13/13 - 0s - loss: 0.0369 - 62ms/epoch - 5ms/step\n",
      "Epoch 509/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 510/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 511/1000\n",
      "13/13 - 0s - loss: 0.0369 - 33ms/epoch - 3ms/step\n",
      "Epoch 512/1000\n",
      "13/13 - 0s - loss: 0.0371 - 50ms/epoch - 4ms/step\n",
      "Epoch 513/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 514/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 515/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 516/1000\n",
      "13/13 - 0s - loss: 0.0371 - 43ms/epoch - 3ms/step\n",
      "Epoch 517/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 518/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 519/1000\n",
      "13/13 - 0s - loss: 0.0368 - 34ms/epoch - 3ms/step\n",
      "Epoch 520/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 521/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 522/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 523/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 524/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 525/1000\n",
      "13/13 - 0s - loss: 0.0369 - 47ms/epoch - 4ms/step\n",
      "Epoch 526/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 527/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 528/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 529/1000\n",
      "13/13 - 0s - loss: 0.0369 - 48ms/epoch - 4ms/step\n",
      "Epoch 530/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 531/1000\n",
      "13/13 - 0s - loss: 0.0368 - 62ms/epoch - 5ms/step\n",
      "Epoch 532/1000\n",
      "13/13 - 0s - loss: 0.0371 - 50ms/epoch - 4ms/step\n",
      "Epoch 533/1000\n",
      "13/13 - 0s - loss: 0.0369 - 54ms/epoch - 4ms/step\n",
      "Epoch 534/1000\n",
      "13/13 - 0s - loss: 0.0368 - 58ms/epoch - 4ms/step\n",
      "Epoch 535/1000\n",
      "13/13 - 0s - loss: 0.0368 - 57ms/epoch - 4ms/step\n",
      "Epoch 536/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 537/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 538/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 539/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 540/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 541/1000\n",
      "13/13 - 0s - loss: 0.0370 - 52ms/epoch - 4ms/step\n",
      "Epoch 542/1000\n",
      "13/13 - 0s - loss: 0.0368 - 52ms/epoch - 4ms/step\n",
      "Epoch 543/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 544/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 545/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 546/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 547/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 548/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 549/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 550/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 551/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 552/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 553/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 554/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 555/1000\n",
      "13/13 - 0s - loss: 0.0368 - 51ms/epoch - 4ms/step\n",
      "Epoch 556/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 557/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 558/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 559/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 560/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 561/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 562/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 563/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 564/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 565/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 566/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 567/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 568/1000\n",
      "13/13 - 0s - loss: 0.0368 - 54ms/epoch - 4ms/step\n",
      "Epoch 569/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 570/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 571/1000\n",
      "13/13 - 0s - loss: 0.0369 - 45ms/epoch - 3ms/step\n",
      "Epoch 572/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 573/1000\n",
      "13/13 - 0s - loss: 0.0370 - 75ms/epoch - 6ms/step\n",
      "Epoch 574/1000\n",
      "13/13 - 0s - loss: 0.0370 - 52ms/epoch - 4ms/step\n",
      "Epoch 575/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 576/1000\n",
      "13/13 - 0s - loss: 0.0370 - 51ms/epoch - 4ms/step\n",
      "Epoch 577/1000\n",
      "13/13 - 0s - loss: 0.0373 - 46ms/epoch - 4ms/step\n",
      "Epoch 578/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 579/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 580/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 581/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 582/1000\n",
      "13/13 - 0s - loss: 0.0369 - 34ms/epoch - 3ms/step\n",
      "Epoch 583/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 584/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 585/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 586/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 587/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 588/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 589/1000\n",
      "13/13 - 0s - loss: 0.0371 - 38ms/epoch - 3ms/step\n",
      "Epoch 590/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 591/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 592/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 593/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 594/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 595/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 596/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 597/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 598/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 599/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 600/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 601/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 602/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 603/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 604/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 605/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 606/1000\n",
      "13/13 - 0s - loss: 0.0369 - 47ms/epoch - 4ms/step\n",
      "Epoch 607/1000\n",
      "13/13 - 0s - loss: 0.0368 - 53ms/epoch - 4ms/step\n",
      "Epoch 608/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 609/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 610/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 611/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 612/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 613/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 614/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 615/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 616/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 617/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 618/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 619/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 620/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 621/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 622/1000\n",
      "13/13 - 0s - loss: 0.0371 - 46ms/epoch - 4ms/step\n",
      "Epoch 623/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 624/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 625/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 626/1000\n",
      "13/13 - 0s - loss: 0.0368 - 56ms/epoch - 4ms/step\n",
      "Epoch 627/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 628/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 629/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 630/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 631/1000\n",
      "13/13 - 0s - loss: 0.0369 - 49ms/epoch - 4ms/step\n",
      "Epoch 632/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 633/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 634/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 635/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 636/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 637/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 638/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 639/1000\n",
      "13/13 - 0s - loss: 0.0368 - 64ms/epoch - 5ms/step\n",
      "Epoch 640/1000\n",
      "13/13 - 0s - loss: 0.0369 - 54ms/epoch - 4ms/step\n",
      "Epoch 641/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 642/1000\n",
      "13/13 - 0s - loss: 0.0368 - 32ms/epoch - 2ms/step\n",
      "Epoch 643/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 644/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 645/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 646/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 647/1000\n",
      "13/13 - 0s - loss: 0.0368 - 33ms/epoch - 3ms/step\n",
      "Epoch 648/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 649/1000\n",
      "13/13 - 0s - loss: 0.0369 - 34ms/epoch - 3ms/step\n",
      "Epoch 650/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 651/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 652/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 653/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 654/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 655/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 656/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 657/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 658/1000\n",
      "13/13 - 0s - loss: 0.0368 - 55ms/epoch - 4ms/step\n",
      "Epoch 659/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 660/1000\n",
      "13/13 - 0s - loss: 0.0368 - 54ms/epoch - 4ms/step\n",
      "Epoch 661/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 662/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 663/1000\n",
      "13/13 - 0s - loss: 0.0369 - 76ms/epoch - 6ms/step\n",
      "Epoch 664/1000\n",
      "13/13 - 0s - loss: 0.0369 - 57ms/epoch - 4ms/step\n",
      "Epoch 665/1000\n",
      "13/13 - 0s - loss: 0.0368 - 52ms/epoch - 4ms/step\n",
      "Epoch 666/1000\n",
      "13/13 - 0s - loss: 0.0371 - 54ms/epoch - 4ms/step\n",
      "Epoch 667/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 668/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 669/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 670/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 671/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 672/1000\n",
      "13/13 - 0s - loss: 0.0368 - 55ms/epoch - 4ms/step\n",
      "Epoch 673/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 674/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 675/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 676/1000\n",
      "13/13 - 0s - loss: 0.0368 - 52ms/epoch - 4ms/step\n",
      "Epoch 677/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 678/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 679/1000\n",
      "13/13 - 0s - loss: 0.0369 - 49ms/epoch - 4ms/step\n",
      "Epoch 680/1000\n",
      "13/13 - 0s - loss: 0.0369 - 51ms/epoch - 4ms/step\n",
      "Epoch 681/1000\n",
      "13/13 - 0s - loss: 0.0368 - 52ms/epoch - 4ms/step\n",
      "Epoch 682/1000\n",
      "13/13 - 0s - loss: 0.0368 - 72ms/epoch - 6ms/step\n",
      "Epoch 683/1000\n",
      "13/13 - 0s - loss: 0.0369 - 53ms/epoch - 4ms/step\n",
      "Epoch 684/1000\n",
      "13/13 - 0s - loss: 0.0369 - 54ms/epoch - 4ms/step\n",
      "Epoch 685/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 686/1000\n",
      "13/13 - 0s - loss: 0.0371 - 44ms/epoch - 3ms/step\n",
      "Epoch 687/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 688/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 689/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 690/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 691/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 692/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 693/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 694/1000\n",
      "13/13 - 0s - loss: 0.0369 - 34ms/epoch - 3ms/step\n",
      "Epoch 695/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 696/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 697/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 698/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 699/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 700/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 701/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 702/1000\n",
      "13/13 - 0s - loss: 0.0369 - 56ms/epoch - 4ms/step\n",
      "Epoch 703/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 704/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 705/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 706/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 707/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 708/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 709/1000\n",
      "13/13 - 0s - loss: 0.0371 - 39ms/epoch - 3ms/step\n",
      "Epoch 710/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 711/1000\n",
      "13/13 - 0s - loss: 0.0368 - 54ms/epoch - 4ms/step\n",
      "Epoch 712/1000\n",
      "13/13 - 0s - loss: 0.0369 - 47ms/epoch - 4ms/step\n",
      "Epoch 713/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 714/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 715/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 716/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 717/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 718/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 719/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 720/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 721/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 722/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 723/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 724/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 725/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 726/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 727/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 728/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 729/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 730/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 731/1000\n",
      "13/13 - 0s - loss: 0.0368 - 49ms/epoch - 4ms/step\n",
      "Epoch 732/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 733/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 734/1000\n",
      "13/13 - 0s - loss: 0.0368 - 57ms/epoch - 4ms/step\n",
      "Epoch 735/1000\n",
      "13/13 - 0s - loss: 0.0368 - 50ms/epoch - 4ms/step\n",
      "Epoch 736/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 737/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 738/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 739/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 740/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 741/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 742/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 743/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 744/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 745/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 746/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 747/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 748/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 749/1000\n",
      "13/13 - 0s - loss: 0.0372 - 42ms/epoch - 3ms/step\n",
      "Epoch 750/1000\n",
      "13/13 - 0s - loss: 0.0370 - 33ms/epoch - 3ms/step\n",
      "Epoch 751/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 752/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 753/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 754/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 755/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 756/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 757/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 758/1000\n",
      "13/13 - 0s - loss: 0.0370 - 38ms/epoch - 3ms/step\n",
      "Epoch 759/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 760/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 761/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 762/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 763/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 764/1000\n",
      "13/13 - 0s - loss: 0.0370 - 48ms/epoch - 4ms/step\n",
      "Epoch 765/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 766/1000\n",
      "13/13 - 0s - loss: 0.0370 - 34ms/epoch - 3ms/step\n",
      "Epoch 767/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 768/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 769/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 770/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 771/1000\n",
      "13/13 - 0s - loss: 0.0370 - 37ms/epoch - 3ms/step\n",
      "Epoch 772/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 773/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 774/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 775/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 776/1000\n",
      "13/13 - 0s - loss: 0.0370 - 36ms/epoch - 3ms/step\n",
      "Epoch 777/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 778/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 779/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 780/1000\n",
      "13/13 - 0s - loss: 0.0371 - 36ms/epoch - 3ms/step\n",
      "Epoch 781/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 782/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 783/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 784/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 785/1000\n",
      "13/13 - 0s - loss: 0.0368 - 32ms/epoch - 2ms/step\n",
      "Epoch 786/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 787/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 788/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 789/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 790/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 791/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 792/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 793/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 794/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 795/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 796/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 797/1000\n",
      "13/13 - 0s - loss: 0.0368 - 52ms/epoch - 4ms/step\n",
      "Epoch 798/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 799/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 800/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 801/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 802/1000\n",
      "13/13 - 0s - loss: 0.0372 - 39ms/epoch - 3ms/step\n",
      "Epoch 803/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 804/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 805/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 806/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 807/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 808/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 809/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 810/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 811/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 812/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 813/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 814/1000\n",
      "13/13 - 0s - loss: 0.0370 - 42ms/epoch - 3ms/step\n",
      "Epoch 815/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 816/1000\n",
      "13/13 - 0s - loss: 0.0372 - 42ms/epoch - 3ms/step\n",
      "Epoch 817/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 818/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 819/1000\n",
      "13/13 - 0s - loss: 0.0372 - 35ms/epoch - 3ms/step\n",
      "Epoch 820/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 821/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 822/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 823/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 824/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 825/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 826/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 827/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 828/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 829/1000\n",
      "13/13 - 0s - loss: 0.0367 - 42ms/epoch - 3ms/step\n",
      "Epoch 830/1000\n",
      "13/13 - 0s - loss: 0.0369 - 58ms/epoch - 4ms/step\n",
      "Epoch 831/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 832/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 833/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 834/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 835/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 836/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 837/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 838/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 839/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 840/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 841/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 842/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 843/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 844/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 845/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 846/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 847/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 848/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 849/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 850/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 851/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 852/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 853/1000\n",
      "13/13 - 0s - loss: 0.0369 - 47ms/epoch - 4ms/step\n",
      "Epoch 854/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 855/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 856/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 857/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 858/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 859/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 860/1000\n",
      "13/13 - 0s - loss: 0.0369 - 55ms/epoch - 4ms/step\n",
      "Epoch 861/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 862/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 863/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 864/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 865/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 866/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 867/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 868/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 869/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 870/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 871/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 872/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 873/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 874/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 875/1000\n",
      "13/13 - 0s - loss: 0.0369 - 50ms/epoch - 4ms/step\n",
      "Epoch 876/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 877/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 878/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 879/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 880/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 881/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 882/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 883/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 884/1000\n",
      "13/13 - 0s - loss: 0.0369 - 48ms/epoch - 4ms/step\n",
      "Epoch 885/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 886/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 887/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 888/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 889/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 890/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 891/1000\n",
      "13/13 - 0s - loss: 0.0369 - 39ms/epoch - 3ms/step\n",
      "Epoch 892/1000\n",
      "13/13 - 0s - loss: 0.0368 - 34ms/epoch - 3ms/step\n",
      "Epoch 893/1000\n",
      "13/13 - 0s - loss: 0.0368 - 72ms/epoch - 6ms/step\n",
      "Epoch 894/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 895/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 896/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 897/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 898/1000\n",
      "13/13 - 0s - loss: 0.0368 - 54ms/epoch - 4ms/step\n",
      "Epoch 899/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 900/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 901/1000\n",
      "13/13 - 0s - loss: 0.0373 - 35ms/epoch - 3ms/step\n",
      "Epoch 902/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 903/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 904/1000\n",
      "13/13 - 0s - loss: 0.0368 - 25ms/epoch - 2ms/step\n",
      "Epoch 905/1000\n",
      "13/13 - 0s - loss: 0.0370 - 37ms/epoch - 3ms/step\n",
      "Epoch 906/1000\n",
      "13/13 - 0s - loss: 0.0368 - 35ms/epoch - 3ms/step\n",
      "Epoch 907/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 908/1000\n",
      "13/13 - 0s - loss: 0.0369 - 35ms/epoch - 3ms/step\n",
      "Epoch 909/1000\n",
      "13/13 - 0s - loss: 0.0367 - 35ms/epoch - 3ms/step\n",
      "Epoch 910/1000\n",
      "13/13 - 0s - loss: 0.0368 - 33ms/epoch - 3ms/step\n",
      "Epoch 911/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 912/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 913/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 914/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 915/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 916/1000\n",
      "13/13 - 0s - loss: 0.0369 - 47ms/epoch - 4ms/step\n",
      "Epoch 917/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 918/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 919/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 920/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 921/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 922/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 923/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 924/1000\n",
      "13/13 - 0s - loss: 0.0369 - 46ms/epoch - 4ms/step\n",
      "Epoch 925/1000\n",
      "13/13 - 0s - loss: 0.0369 - 66ms/epoch - 5ms/step\n",
      "Epoch 926/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 927/1000\n",
      "13/13 - 0s - loss: 0.0370 - 40ms/epoch - 3ms/step\n",
      "Epoch 928/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 929/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 930/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 931/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 932/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 933/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 934/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 935/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 936/1000\n",
      "13/13 - 0s - loss: 0.0372 - 49ms/epoch - 4ms/step\n",
      "Epoch 937/1000\n",
      "13/13 - 0s - loss: 0.0367 - 46ms/epoch - 4ms/step\n",
      "Epoch 938/1000\n",
      "13/13 - 0s - loss: 0.0370 - 44ms/epoch - 3ms/step\n",
      "Epoch 939/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 940/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 941/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 942/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 943/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 944/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 945/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 946/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 947/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 948/1000\n",
      "13/13 - 0s - loss: 0.0370 - 43ms/epoch - 3ms/step\n",
      "Epoch 949/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 950/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 951/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 952/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 953/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 954/1000\n",
      "13/13 - 0s - loss: 0.0368 - 34ms/epoch - 3ms/step\n",
      "Epoch 955/1000\n",
      "13/13 - 0s - loss: 0.0368 - 51ms/epoch - 4ms/step\n",
      "Epoch 956/1000\n",
      "13/13 - 0s - loss: 0.0368 - 54ms/epoch - 4ms/step\n",
      "Epoch 957/1000\n",
      "13/13 - 0s - loss: 0.0369 - 37ms/epoch - 3ms/step\n",
      "Epoch 958/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 959/1000\n",
      "13/13 - 0s - loss: 0.0369 - 44ms/epoch - 3ms/step\n",
      "Epoch 960/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 961/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 962/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 963/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 964/1000\n",
      "13/13 - 0s - loss: 0.0368 - 46ms/epoch - 4ms/step\n",
      "Epoch 965/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 966/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 967/1000\n",
      "13/13 - 0s - loss: 0.0368 - 48ms/epoch - 4ms/step\n",
      "Epoch 968/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 969/1000\n",
      "13/13 - 0s - loss: 0.0368 - 36ms/epoch - 3ms/step\n",
      "Epoch 970/1000\n",
      "13/13 - 0s - loss: 0.0370 - 37ms/epoch - 3ms/step\n",
      "Epoch 971/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 972/1000\n",
      "13/13 - 0s - loss: 0.0368 - 38ms/epoch - 3ms/step\n",
      "Epoch 973/1000\n",
      "13/13 - 0s - loss: 0.0369 - 33ms/epoch - 3ms/step\n",
      "Epoch 974/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 975/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 976/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 977/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 978/1000\n",
      "13/13 - 0s - loss: 0.0368 - 47ms/epoch - 4ms/step\n",
      "Epoch 979/1000\n",
      "13/13 - 0s - loss: 0.0369 - 38ms/epoch - 3ms/step\n",
      "Epoch 980/1000\n",
      "13/13 - 0s - loss: 0.0369 - 41ms/epoch - 3ms/step\n",
      "Epoch 981/1000\n",
      "13/13 - 0s - loss: 0.0368 - 37ms/epoch - 3ms/step\n",
      "Epoch 982/1000\n",
      "13/13 - 0s - loss: 0.0369 - 36ms/epoch - 3ms/step\n",
      "Epoch 983/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n",
      "Epoch 984/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 985/1000\n",
      "13/13 - 0s - loss: 0.0369 - 40ms/epoch - 3ms/step\n",
      "Epoch 986/1000\n",
      "13/13 - 0s - loss: 0.0368 - 40ms/epoch - 3ms/step\n",
      "Epoch 987/1000\n",
      "13/13 - 0s - loss: 0.0369 - 42ms/epoch - 3ms/step\n",
      "Epoch 988/1000\n",
      "13/13 - 0s - loss: 0.0368 - 63ms/epoch - 5ms/step\n",
      "Epoch 989/1000\n",
      "13/13 - 0s - loss: 0.0369 - 54ms/epoch - 4ms/step\n",
      "Epoch 990/1000\n",
      "13/13 - 0s - loss: 0.0370 - 48ms/epoch - 4ms/step\n",
      "Epoch 991/1000\n",
      "13/13 - 0s - loss: 0.0368 - 45ms/epoch - 3ms/step\n",
      "Epoch 992/1000\n",
      "13/13 - 0s - loss: 0.0369 - 45ms/epoch - 3ms/step\n",
      "Epoch 993/1000\n",
      "13/13 - 0s - loss: 0.0368 - 42ms/epoch - 3ms/step\n",
      "Epoch 994/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 995/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 996/1000\n",
      "13/13 - 0s - loss: 0.0369 - 43ms/epoch - 3ms/step\n",
      "Epoch 997/1000\n",
      "13/13 - 0s - loss: 0.0368 - 39ms/epoch - 3ms/step\n",
      "Epoch 998/1000\n",
      "13/13 - 0s - loss: 0.0368 - 41ms/epoch - 3ms/step\n",
      "Epoch 999/1000\n",
      "13/13 - 0s - loss: 0.0368 - 44ms/epoch - 3ms/step\n",
      "Epoch 1000/1000\n",
      "13/13 - 0s - loss: 0.0368 - 43ms/epoch - 3ms/step\n"
     ]
    }
   ],
   "source": [
    "# LSTM modelini oluşturun\n",
    "model = Sequential()\n",
    "model.add(LSTM(4, input_shape=(1, look_back)))\n",
    "model.add(Dense(1))\n",
    "model.compile(loss='mean_squared_error', optimizer='adam')\n",
    "history = model.fit(trainX, trainY, epochs=1000, batch_size=1, verbose=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 1s 1s/step\n",
      "1/1 [==============================] - 0s 39ms/step\n"
     ]
    }
   ],
   "source": [
    "# Tahmin yapın\n",
    "trainPredict = model.predict(trainX)\n",
    "testPredict = model.predict(testX)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tahminleri ters ölçeklendirin\n",
    "trainPredict = scaler.inverse_transform(trainPredict)\n",
    "trainY = scaler.inverse_transform([trainY])\n",
    "testPredict = scaler.inverse_transform(testPredict)\n",
    "testY = scaler.inverse_transform([testY])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 1s 1s/step\n",
      "2022 tahmini deprem sayısı: 28\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# 2022 ve 2023 için tahmin yapın\n",
    "last_data = np.array([testPredict[-1]])\n",
    "next_year = model.predict(np.reshape(last_data, (1, 1, 1)))\n",
    "next_year = scaler.inverse_transform(next_year)\n",
    "print(\"2022 tahmini deprem sayısı:\", int(next_year[0][0]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 38ms/step\n",
      "2023 tahmini deprem sayısı: 30\n"
     ]
    }
   ],
   "source": [
    "next_next_year = model.predict(np.reshape(np.array([next_year]), (1, 1, 1)))\n",
    "next_next_year = scaler.inverse_transform(next_next_year)\n",
    "print(\"2023 tahmini deprem sayısı:\", int(next_next_year[0][0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 43ms/step\n",
      "2024 tahmini deprem sayısı: 30\n"
     ]
    }
   ],
   "source": [
    "# 2024 için tahmin yapın\n",
    "next_next_next_year = model.predict(np.reshape(np.array([next_next_year]), (1, 1, 1)))\n",
    "next_next_next_year = scaler.inverse_transform(next_next_next_year)\n",
    "print(\"2024 tahmini deprem sayısı:\", int(next_next_next_year[0][0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'], label='Eğitim Loss')\n",
    "plt.xlabel('Epok')\n",
    "plt.ylabel('Loss')\n",
    "plt.legend()\n",
    "plt.title('LSTM Modeli Loss Değeri')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Other datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(78, 7)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time‡</th>\n",
       "      <th>Place</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Mag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10 September 1509</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Constantinople</td>\n",
       "      <td>40.9</td>\n",
       "      <td>28.7</td>\n",
       "      <td>10,000</td>\n",
       "      <td>7.2 Mw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23 February 1653</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Smyrna</td>\n",
       "      <td>38.2</td>\n",
       "      <td>28.2</td>\n",
       "      <td>2,500</td>\n",
       "      <td>7.5 Mw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17 August 1668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anatolia</td>\n",
       "      <td>40.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>8,000</td>\n",
       "      <td>8M w</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10 July 1688</td>\n",
       "      <td>11:45</td>\n",
       "      <td>Smyrna</td>\n",
       "      <td>38.4</td>\n",
       "      <td>26.9</td>\n",
       "      <td>16,000</td>\n",
       "      <td>7.0 Mw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22 May 1766</td>\n",
       "      <td>05:10</td>\n",
       "      <td>Istanbul</td>\n",
       "      <td>40.8</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4,000</td>\n",
       "      <td>7.1 Mw</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Date  Time‡           Place   Lat  Long  Deaths     Mag\n",
       "0  10 September 1509    NaN  Constantinople  40.9  28.7  10,000  7.2 Mw\n",
       "1   23 February 1653    NaN          Smyrna  38.2  28.2   2,500  7.5 Mw\n",
       "2     17 August 1668    NaN        Anatolia  40.0  36.0   8,000    8M w\n",
       "3       10 July 1688  11:45          Smyrna  38.4  26.9  16,000  7.0 Mw\n",
       "4        22 May 1766  05:10        Istanbul  40.8  29.0   4,000  7.1 Mw"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr = pd.read_csv('Turkey_earthquakes.csv')\n",
    "print (tr.shape)\n",
    "tr.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Erzincan         3\n",
       "Smyrna           3\n",
       "Bingöl           3\n",
       "Ayvalık          2\n",
       "Van              2\n",
       "                ..\n",
       "Kahramanmaraş    1\n",
       "Yenice           1\n",
       "Fethiye          1\n",
       "Chios            1\n",
       "Erbaa            1\n",
       "Name: Place, Length: 65, dtype: int64"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr.Place.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count           78\n",
       "unique          65\n",
       "top       Erzincan\n",
       "freq             3\n",
       "Name: Place, dtype: object"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr.Place.describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time‡</th>\n",
       "      <th>Place</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Mag</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10 September 1509</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Constantinople</td>\n",
       "      <td>40.9</td>\n",
       "      <td>28.7</td>\n",
       "      <td>10,000</td>\n",
       "      <td>7.2 Mw</td>\n",
       "      <td>POINT (28.7 40.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23 February 1653</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Smyrna</td>\n",
       "      <td>38.2</td>\n",
       "      <td>28.2</td>\n",
       "      <td>2,500</td>\n",
       "      <td>7.5 Mw</td>\n",
       "      <td>POINT (28.2 38.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17 August 1668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anatolia</td>\n",
       "      <td>40.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>8,000</td>\n",
       "      <td>8M w</td>\n",
       "      <td>POINT (36 40)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10 July 1688</td>\n",
       "      <td>11:45</td>\n",
       "      <td>Smyrna</td>\n",
       "      <td>38.4</td>\n",
       "      <td>26.9</td>\n",
       "      <td>16,000</td>\n",
       "      <td>7.0 Mw</td>\n",
       "      <td>POINT (26.9 38.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22 May 1766</td>\n",
       "      <td>05:10</td>\n",
       "      <td>Istanbul</td>\n",
       "      <td>40.8</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4,000</td>\n",
       "      <td>7.1 Mw</td>\n",
       "      <td>POINT (29 40.8)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Date  Time‡           Place   Lat  Long  Deaths     Mag  \\\n",
       "0  10 September 1509    NaN  Constantinople  40.9  28.7  10,000  7.2 Mw   \n",
       "1   23 February 1653    NaN          Smyrna  38.2  28.2   2,500  7.5 Mw   \n",
       "2     17 August 1668    NaN        Anatolia  40.0  36.0   8,000    8M w   \n",
       "3       10 July 1688  11:45          Smyrna  38.4  26.9  16,000  7.0 Mw   \n",
       "4        22 May 1766  05:10        Istanbul  40.8  29.0   4,000  7.1 Mw   \n",
       "\n",
       "            geometry  \n",
       "0  POINT (28.7 40.9)  \n",
       "1  POINT (28.2 38.2)  \n",
       "2      POINT (36 40)  \n",
       "3  POINT (26.9 38.4)  \n",
       "4    POINT (29 40.8)  "
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr['geometry'] = tr.apply(lambda row:  Point(row[\"Long\"], row[\"Lat\"]), axis=1)\n",
    "tr.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 78 entries, 0 to 77\n",
      "Data columns (total 8 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   Date      78 non-null     object \n",
      " 1   Time‡     71 non-null     object \n",
      " 2   Place     78 non-null     object \n",
      " 3   Lat       78 non-null     float64\n",
      " 4   Long      78 non-null     float64\n",
      " 5   Deaths    78 non-null     object \n",
      " 6   Mag       77 non-null     object \n",
      " 7   geometry  78 non-null     object \n",
      "dtypes: float64(2), object(6)\n",
      "memory usage: 5.0+ KB\n"
     ]
    }
   ],
   "source": [
    "tr.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time‡</th>\n",
       "      <th>Place</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Mag</th>\n",
       "      <th>geometry</th>\n",
       "      <th>parsed_Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10 September 1509</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Constantinople</td>\n",
       "      <td>40.9</td>\n",
       "      <td>28.7</td>\n",
       "      <td>10,000</td>\n",
       "      <td>7.2 Mw</td>\n",
       "      <td>POINT (28.7 40.9)</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23 February 1653</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Smyrna</td>\n",
       "      <td>38.2</td>\n",
       "      <td>28.2</td>\n",
       "      <td>2,500</td>\n",
       "      <td>7.5 Mw</td>\n",
       "      <td>POINT (28.2 38.2)</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17 August 1668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anatolia</td>\n",
       "      <td>40.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>8,000</td>\n",
       "      <td>8M w</td>\n",
       "      <td>POINT (36 40)</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10 July 1688</td>\n",
       "      <td>11:45</td>\n",
       "      <td>Smyrna</td>\n",
       "      <td>38.4</td>\n",
       "      <td>26.9</td>\n",
       "      <td>16,000</td>\n",
       "      <td>7.0 Mw</td>\n",
       "      <td>POINT (26.9 38.4)</td>\n",
       "      <td>1688-07-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22 May 1766</td>\n",
       "      <td>05:10</td>\n",
       "      <td>Istanbul</td>\n",
       "      <td>40.8</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4,000</td>\n",
       "      <td>7.1 Mw</td>\n",
       "      <td>POINT (29 40.8)</td>\n",
       "      <td>1766-05-22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Date  Time‡           Place   Lat  Long  Deaths     Mag  \\\n",
       "0  10 September 1509    NaN  Constantinople  40.9  28.7  10,000  7.2 Mw   \n",
       "1   23 February 1653    NaN          Smyrna  38.2  28.2   2,500  7.5 Mw   \n",
       "2     17 August 1668    NaN        Anatolia  40.0  36.0   8,000    8M w   \n",
       "3       10 July 1688  11:45          Smyrna  38.4  26.9  16,000  7.0 Mw   \n",
       "4        22 May 1766  05:10        Istanbul  40.8  29.0   4,000  7.1 Mw   \n",
       "\n",
       "            geometry parsed_Date  \n",
       "0  POINT (28.7 40.9)         NaT  \n",
       "1  POINT (28.2 38.2)         NaT  \n",
       "2      POINT (36 40)         NaT  \n",
       "3  POINT (26.9 38.4)  1688-07-10  \n",
       "4    POINT (29 40.8)  1766-05-22  "
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr[\"parsed_Date\"] = pd.to_datetime(tr[\"Date\"], format=\"%d %B %Y\", errors = 'coerce')\n",
    "tr.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1584x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tr['year'] = tr['parsed_Date'].dt.year\n",
    "labels_turkey = tr.year.value_counts().index\n",
    "plt.figure(figsize=(22,6))\n",
    "pal = sns.cubehelix_palette(len(tr.year.value_counts().index), start=.5, rot=-.75)\n",
    "sns.barplot(x=np.sort(tr.year.value_counts().index) ,y = tr.year.value_counts().values,palette =pal )\n",
    "plt.xticks(rotation=90 , color ='black')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(78, 10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time‡</th>\n",
       "      <th>Place</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Mag</th>\n",
       "      <th>geometry</th>\n",
       "      <th>parsed_Date</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>14 June 2020</td>\n",
       "      <td>16:24 local time</td>\n",
       "      <td>Bingöl</td>\n",
       "      <td>39.4200</td>\n",
       "      <td>40.6700</td>\n",
       "      <td>1</td>\n",
       "      <td>5.9 Mw</td>\n",
       "      <td>POINT (40.67000 39.42000)</td>\n",
       "      <td>2020-06-14</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>30 October 2020</td>\n",
       "      <td>14:51 local time</td>\n",
       "      <td>\\tAegean Sea</td>\n",
       "      <td>37.9180</td>\n",
       "      <td>26.7900</td>\n",
       "      <td>117</td>\n",
       "      <td>7.0 Mw</td>\n",
       "      <td>POINT (26.79000 37.91800)</td>\n",
       "      <td>2020-10-30</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>23 November 2022</td>\n",
       "      <td>04:08 local time</td>\n",
       "      <td>Düzce</td>\n",
       "      <td>40.8470</td>\n",
       "      <td>30.9670</td>\n",
       "      <td>2</td>\n",
       "      <td>6.1 Mw</td>\n",
       "      <td>POINT (30.96700 40.84700)</td>\n",
       "      <td>2022-11-23</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>6 February 2023</td>\n",
       "      <td>04:17 local time</td>\n",
       "      <td>Gaziantep</td>\n",
       "      <td>37.1123</td>\n",
       "      <td>37.1195</td>\n",
       "      <td>29,600</td>\n",
       "      <td>7.8 Mw</td>\n",
       "      <td>POINT (37.11950 37.11230)</td>\n",
       "      <td>2023-02-06</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>6 February 2023</td>\n",
       "      <td>13:24 local time</td>\n",
       "      <td>Kahramanmaraş</td>\n",
       "      <td>38.0357</td>\n",
       "      <td>37.2287</td>\n",
       "      <td>29,600</td>\n",
       "      <td>7.7 Mw</td>\n",
       "      <td>POINT (37.22870 38.03570)</td>\n",
       "      <td>2023-02-06</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Date             Time‡          Place      Lat     Long  \\\n",
       "73      14 June 2020  16:24 local time         Bingöl  39.4200  40.6700   \n",
       "74   30 October 2020  14:51 local time   \\tAegean Sea  37.9180  26.7900   \n",
       "75  23 November 2022  04:08 local time          Düzce  40.8470  30.9670   \n",
       "76   6 February 2023  04:17 local time      Gaziantep  37.1123  37.1195   \n",
       "77   6 February 2023  13:24 local time  Kahramanmaraş  38.0357  37.2287   \n",
       "\n",
       "    Deaths     Mag                   geometry parsed_Date    year  \n",
       "73       1  5.9 Mw  POINT (40.67000 39.42000)  2020-06-14  2020.0  \n",
       "74     117  7.0 Mw  POINT (26.79000 37.91800)  2020-10-30  2020.0  \n",
       "75       2  6.1 Mw  POINT (30.96700 40.84700)  2022-11-23  2022.0  \n",
       "76  29,600  7.8 Mw  POINT (37.11950 37.11230)  2023-02-06  2023.0  \n",
       "77  29,600  7.7 Mw  POINT (37.22870 38.03570)  2023-02-06  2023.0  "
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_earthquakes = gpd.GeoDataFrame(tr, geometry=tr.geometry )\n",
    "print(gdf_earthquakes.shape)\n",
    "gdf_earthquakes.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))\n",
    "world.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = world[world.name=='Turkey'].plot(figsize=(10, 10), color='none', edgecolor='gainsboro')\n",
    "gdf_earthquakes.plot(ax=ax, color ='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_1623657bc1ed67f62e947c58134a4116 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_1623657bc1ed67f62e947c58134a4116&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_1623657bc1ed67f62e947c58134a4116 = L.map(\n",
       "                &quot;map_1623657bc1ed67f62e947c58134a4116&quot;,\n",
       "                {\n",
       "                    center: [39.0618, 33.75],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 10,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                    titles: &quot;cartodbpositron&quot;,\n",
       "                    zooms: 5,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_5d1f9ca4f907ffd5915b1f92ebe9cf70 = L.tileLayer(\n",
       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "            var marker_9ba1a79c05a3ba7e782cbb2e48800e81 = L.marker(\n",
       "                [40.9, 28.7],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_eafb237e73c94c08d93b0586e9188763 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_e1bad5625e888eb055ae62473aa94ce5 = $(`&lt;div id=&quot;html_e1bad5625e888eb055ae62473aa94ce5&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 10,000  Magnitude : 7.2 Mw  Date : 10 September 1509&lt;/div&gt;`)[0];\n",
       "                popup_eafb237e73c94c08d93b0586e9188763.setContent(html_e1bad5625e888eb055ae62473aa94ce5);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_9ba1a79c05a3ba7e782cbb2e48800e81.bindPopup(popup_eafb237e73c94c08d93b0586e9188763)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_137bc96522a0ad8e1930fdf440210667 = L.marker(\n",
       "                [38.2, 28.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_76a0cc81d4f9145e46a409554d201b4b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_8b80f42e59cfa0c5d65177a91646875d = $(`&lt;div id=&quot;html_8b80f42e59cfa0c5d65177a91646875d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2,500  Magnitude : 7.5 Mw  Date : 23 February 1653&lt;/div&gt;`)[0];\n",
       "                popup_76a0cc81d4f9145e46a409554d201b4b.setContent(html_8b80f42e59cfa0c5d65177a91646875d);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_137bc96522a0ad8e1930fdf440210667.bindPopup(popup_76a0cc81d4f9145e46a409554d201b4b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_f0737cf800815fa96a793b191d843b18 = L.marker(\n",
       "                [40.0, 36.0],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_5006e2cf028674a3f539472779377e6f = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_18749e1c1015835052fd473774cdc750 = $(`&lt;div id=&quot;html_18749e1c1015835052fd473774cdc750&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 8,000  Magnitude : 8M w  Date : 17 August 1668&lt;/div&gt;`)[0];\n",
       "                popup_5006e2cf028674a3f539472779377e6f.setContent(html_18749e1c1015835052fd473774cdc750);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_f0737cf800815fa96a793b191d843b18.bindPopup(popup_5006e2cf028674a3f539472779377e6f)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_e95ee84acbe094d34b51d34fc9cad6a9 = L.marker(\n",
       "                [38.4, 26.9],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_98cf117c11f8a4818d874788e36bd809 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_6d8b6430f21fac2dff1f56acd5e998cf = $(`&lt;div id=&quot;html_6d8b6430f21fac2dff1f56acd5e998cf&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 16,000  Magnitude : 7.0 Mw  Date : 10 July 1688&lt;/div&gt;`)[0];\n",
       "                popup_98cf117c11f8a4818d874788e36bd809.setContent(html_6d8b6430f21fac2dff1f56acd5e998cf);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_e95ee84acbe094d34b51d34fc9cad6a9.bindPopup(popup_98cf117c11f8a4818d874788e36bd809)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_f63954754387913ce733b8beb58a2837 = L.marker(\n",
       "                [40.8, 29.0],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_729c7d691a3b48a270d25213eaf4c502 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_90b1d861dd0155509718481c61e62105 = $(`&lt;div id=&quot;html_90b1d861dd0155509718481c61e62105&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 4,000  Magnitude : 7.1 Mw  Date : 22 May 1766&lt;/div&gt;`)[0];\n",
       "                popup_729c7d691a3b48a270d25213eaf4c502.setContent(html_90b1d861dd0155509718481c61e62105);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_f63954754387913ce733b8beb58a2837.bindPopup(popup_729c7d691a3b48a270d25213eaf4c502)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_ae63e59daae549d40112e7d7a06eb729 = L.marker(\n",
       "                [39.5, 40.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_6790232806e9da6777cd2dfdc2e655d1 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_1d5feffaf9b529da57f365424ae2e652 = $(`&lt;div id=&quot;html_1d5feffaf9b529da57f365424ae2e652&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 7500  Magnitude : 7.6 Mw  Date : 23 July 1784&lt;/div&gt;`)[0];\n",
       "                popup_6790232806e9da6777cd2dfdc2e655d1.setContent(html_1d5feffaf9b529da57f365424ae2e652);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_ae63e59daae549d40112e7d7a06eb729.bindPopup(popup_6790232806e9da6777cd2dfdc2e655d1)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_f87c50f323471a066869345c818e40ec = L.marker(\n",
       "                [39.6, 44.1],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_cf3999d6871602db07b33779c801c586 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_105dfc518846265118e01d336f8213c7 = $(`&lt;div id=&quot;html_105dfc518846265118e01d336f8213c7&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 10,000  Magnitude : 7.4 Mw  Date : 2 July 1840&lt;/div&gt;`)[0];\n",
       "                popup_cf3999d6871602db07b33779c801c586.setContent(html_105dfc518846265118e01d336f8213c7);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_f87c50f323471a066869345c818e40ec.bindPopup(popup_cf3999d6871602db07b33779c801c586)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_164095d80bc979d6597af6c799785f08 = L.marker(\n",
       "                [40.2, 29.1],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_d80597b6f6f50c17f530a1724e289098 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_8ccdee579f7ae807a3a86fb743adfa41 = $(`&lt;div id=&quot;html_8ccdee579f7ae807a3a86fb743adfa41&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1,900  Magnitude : 6.7 Mw  Date : 28 February 1855&lt;/div&gt;`)[0];\n",
       "                popup_d80597b6f6f50c17f530a1724e289098.setContent(html_8ccdee579f7ae807a3a86fb743adfa41);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_164095d80bc979d6597af6c799785f08.bindPopup(popup_d80597b6f6f50c17f530a1724e289098)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_925c82177fdba3142eff072e359f927a = L.marker(\n",
       "                [39.9, 41.3],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_29aa73cc4b54fc623589fe0a8c9f19ab = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_2b8eaf2fc0b1ed0d968dc33998d3d08b = $(`&lt;div id=&quot;html_2b8eaf2fc0b1ed0d968dc33998d3d08b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 15,000  Magnitude : 6.1 Mw  Date : 2 June 1859&lt;/div&gt;`)[0];\n",
       "                popup_29aa73cc4b54fc623589fe0a8c9f19ab.setContent(html_2b8eaf2fc0b1ed0d968dc33998d3d08b);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_925c82177fdba3142eff072e359f927a.bindPopup(popup_29aa73cc4b54fc623589fe0a8c9f19ab)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_902650a8798c4f1f31423c300479d677 = L.marker(\n",
       "                [36.4, 36.4],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_41d7297525399a5cad8c370f65c75198 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_7ce18936b1b6ad00c40389057d841825 = $(`&lt;div id=&quot;html_7ce18936b1b6ad00c40389057d841825&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1,800  Magnitude : 7.2 Mw  Date : 3 April 1872&lt;/div&gt;`)[0];\n",
       "                popup_41d7297525399a5cad8c370f65c75198.setContent(html_7ce18936b1b6ad00c40389057d841825);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_902650a8798c4f1f31423c300479d677.bindPopup(popup_41d7297525399a5cad8c370f65c75198)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_079c11f2d460b284a5d09eb082962481 = L.marker(\n",
       "                [38.25, 26.25],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_34cc56476bc968b2a91397797b01f293 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_7684cfb0cbe603f36a6854742be98a3e = $(`&lt;div id=&quot;html_7684cfb0cbe603f36a6854742be98a3e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 7,866  Magnitude : 7.3 Mw  Date : 3 April 1881&lt;/div&gt;`)[0];\n",
       "                popup_34cc56476bc968b2a91397797b01f293.setContent(html_7684cfb0cbe603f36a6854742be98a3e);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_079c11f2d460b284a5d09eb082962481.bindPopup(popup_34cc56476bc968b2a91397797b01f293)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_0bf5b900563698c824001ac06ca52177 = L.marker(\n",
       "                [38.25, 26.25],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_044446f09640e2da07d46ccef9639f47 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_047f441bdd8f34f2707f792dda156e7c = $(`&lt;div id=&quot;html_047f441bdd8f34f2707f792dda156e7c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 7,866  Magnitude : 7.3 Mw  Date : 3 April 1881&lt;/div&gt;`)[0];\n",
       "                popup_044446f09640e2da07d46ccef9639f47.setContent(html_047f441bdd8f34f2707f792dda156e7c);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_0bf5b900563698c824001ac06ca52177.bindPopup(popup_044446f09640e2da07d46ccef9639f47)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_079212505165875791cdc1e012915f8d = L.marker(\n",
       "                [38.25, 26.25],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_8cbc9275717b134fc0e559ca18e9d36a = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_44620367ad7c7417294f0b75abab9465 = $(`&lt;div id=&quot;html_44620367ad7c7417294f0b75abab9465&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 7,866  Magnitude : 7.3 Mw  Date : 3 April 1881&lt;/div&gt;`)[0];\n",
       "                popup_8cbc9275717b134fc0e559ca18e9d36a.setContent(html_44620367ad7c7417294f0b75abab9465);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_079212505165875791cdc1e012915f8d.bindPopup(popup_8cbc9275717b134fc0e559ca18e9d36a)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_805515e2a7b10402f8cefa5ea272ce2b = L.marker(\n",
       "                [38.3, 26.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_01321e99fcb570cf034a7a373a128422 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_a707c6ef2824421132ff3c9a33b22d5d = $(`&lt;div id=&quot;html_a707c6ef2824421132ff3c9a33b22d5d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 120  Magnitude : 7.3 Mw  Date : 10 October 1883&lt;/div&gt;`)[0];\n",
       "                popup_01321e99fcb570cf034a7a373a128422.setContent(html_a707c6ef2824421132ff3c9a33b22d5d);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_805515e2a7b10402f8cefa5ea272ce2b.bindPopup(popup_01321e99fcb570cf034a7a373a128422)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_8a35e6d93a4fcb70205fd1b0beda07bc = L.marker(\n",
       "                [38.3, 26.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_870e79cc78114206e3e690d4d6d61785 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_d512681ac31dc3b8f8dd2d073dfc28ab = $(`&lt;div id=&quot;html_d512681ac31dc3b8f8dd2d073dfc28ab&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 120  Magnitude : 7.3 Mw  Date : 10 October 1883&lt;/div&gt;`)[0];\n",
       "                popup_870e79cc78114206e3e690d4d6d61785.setContent(html_d512681ac31dc3b8f8dd2d073dfc28ab);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_8a35e6d93a4fcb70205fd1b0beda07bc.bindPopup(popup_870e79cc78114206e3e690d4d6d61785)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_b1c9080b5ab35144464b39fa194e75ca = L.marker(\n",
       "                [38.3, 26.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_58ede13a700263361ebaddca79d151ff = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_3ec2bf02ee8e0ac93826121f8d1e2853 = $(`&lt;div id=&quot;html_3ec2bf02ee8e0ac93826121f8d1e2853&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 120  Magnitude : 7.3 Mw  Date : 10 October 1883&lt;/div&gt;`)[0];\n",
       "                popup_58ede13a700263361ebaddca79d151ff.setContent(html_3ec2bf02ee8e0ac93826121f8d1e2853);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_b1c9080b5ab35144464b39fa194e75ca.bindPopup(popup_58ede13a700263361ebaddca79d151ff)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_bfb5416d6c358085698324016fc38358 = L.marker(\n",
       "                [40.73, 29.25],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_d5760bc21260ac870003f57aa599c673 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_97d74ff2b8841e963a88ad74adcb9abe = $(`&lt;div id=&quot;html_97d74ff2b8841e963a88ad74adcb9abe&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1,300  Magnitude : 7.0 Mw  Date : 10 July 1894&lt;/div&gt;`)[0];\n",
       "                popup_d5760bc21260ac870003f57aa599c673.setContent(html_97d74ff2b8841e963a88ad74adcb9abe);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_bfb5416d6c358085698324016fc38358.bindPopup(popup_d5760bc21260ac870003f57aa599c673)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_c68f41e87acaf18845adc8eb19f5b569 = L.marker(\n",
       "                [37.9, 28.1],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_f47157a94d87691eb13c32ad86bcf972 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_58030d3a84df604f66c41c0c2f15f1d3 = $(`&lt;div id=&quot;html_58030d3a84df604f66c41c0c2f15f1d3&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1,470  Magnitude : 7.1 Mw  Date : 20 September 1899&lt;/div&gt;`)[0];\n",
       "                popup_f47157a94d87691eb13c32ad86bcf972.setContent(html_58030d3a84df604f66c41c0c2f15f1d3);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_c68f41e87acaf18845adc8eb19f5b569.bindPopup(popup_f47157a94d87691eb13c32ad86bcf972)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_7552ed19beae4c7a4d8ff82515751dd8 = L.marker(\n",
       "                [39.14, 42.65],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_95c6ca6890f9dd852fbe4993ec30f414 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_dfe6b7ce2bf96f497f981ca86bf116f3 = $(`&lt;div id=&quot;html_dfe6b7ce2bf96f497f981ca86bf116f3&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 600  Magnitude : 6.7 Mw  Date : 29 April 1903&lt;/div&gt;`)[0];\n",
       "                popup_95c6ca6890f9dd852fbe4993ec30f414.setContent(html_dfe6b7ce2bf96f497f981ca86bf116f3);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_7552ed19beae4c7a4d8ff82515751dd8.bindPopup(popup_95c6ca6890f9dd852fbe4993ec30f414)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_6235d7ba6e23fc0e77f844d8f3f38682 = L.marker(\n",
       "                [40.75, 27.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_388c034c7fa8fd349c443d4c4f21ff67 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_48b7921fca97f6ecdf71fcf44cde2e48 = $(`&lt;div id=&quot;html_48b7921fca97f6ecdf71fcf44cde2e48&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : \t216\t  Magnitude : 7.3 Mw  Date : 9 August 1912&lt;/div&gt;`)[0];\n",
       "                popup_388c034c7fa8fd349c443d4c4f21ff67.setContent(html_48b7921fca97f6ecdf71fcf44cde2e48);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_6235d7ba6e23fc0e77f844d8f3f38682.bindPopup(popup_388c034c7fa8fd349c443d4c4f21ff67)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_59983f258d1fd2d52e51de881dd0261c = L.marker(\n",
       "                [37.82, 30.27],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_f2199e89dba92d4415be1340ea9235c9 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_d8a999461f2b040f991d0f4feea1884b = $(`&lt;div id=&quot;html_d8a999461f2b040f991d0f4feea1884b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2,344  Magnitude : 6.9 Mw  Date : 4 October 1914&lt;/div&gt;`)[0];\n",
       "                popup_f2199e89dba92d4415be1340ea9235c9.setContent(html_d8a999461f2b040f991d0f4feea1884b);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_59983f258d1fd2d52e51de881dd0261c.bindPopup(popup_f2199e89dba92d4415be1340ea9235c9)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_101a029109d2e18fcadcd9ddd46226d4 = L.marker(\n",
       "                [39.18, 27.65],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_87a734648c20f4e7ee3d840b41901d68 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_5eb30d40c215e1aaf0c2e83c4b912efb = $(`&lt;div id=&quot;html_5eb30d40c215e1aaf0c2e83c4b912efb&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 3,000  Magnitude : 7.0 Mw  Date : 18 November 1919&lt;/div&gt;`)[0];\n",
       "                popup_87a734648c20f4e7ee3d840b41901d68.setContent(html_5eb30d40c215e1aaf0c2e83c4b912efb);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_101a029109d2e18fcadcd9ddd46226d4.bindPopup(popup_87a734648c20f4e7ee3d840b41901d68)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_ac3461a7b394a11e65de3245dcc32cc1 = L.marker(\n",
       "                [40.0, 42.1],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_a74fd7e0ac064f0676ab89087f292211 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_32449c8b929eec9d90fbcec0542a92cc = $(`&lt;div id=&quot;html_32449c8b929eec9d90fbcec0542a92cc&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 60  Magnitude : 6.8 Mw  Date : 13 September 1924&lt;/div&gt;`)[0];\n",
       "                popup_a74fd7e0ac064f0676ab89087f292211.setContent(html_32449c8b929eec9d90fbcec0542a92cc);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_ac3461a7b394a11e65de3245dcc32cc1.bindPopup(popup_a74fd7e0ac064f0676ab89087f292211)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_70360b503733c68e648b2798ec6a8fc4 = L.marker(\n",
       "                [40.7, 43.7],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_a2061fe3955bf01b42532257a1b449ee = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_9752d5ffbc6614f3b227ee7ee3f09d15 = $(`&lt;div id=&quot;html_9752d5ffbc6614f3b227ee7ee3f09d15&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 360\t  Magnitude : 6.0 Mw  Date : 22 October 1926&lt;/div&gt;`)[0];\n",
       "                popup_a2061fe3955bf01b42532257a1b449ee.setContent(html_9752d5ffbc6614f3b227ee7ee3f09d15);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_70360b503733c68e648b2798ec6a8fc4.bindPopup(popup_a2061fe3955bf01b42532257a1b449ee)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_6269b1e1580e19c512f4f6965356800c = L.marker(\n",
       "                [38.5, 28.0],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_8359fccfb9e70a18e370829914c1204e = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_98decb5655af9ca4f069df92cf7d32d2 = $(`&lt;div id=&quot;html_98decb5655af9ca4f069df92cf7d32d2&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 50  Magnitude : 6.5 Mw  Date : 31 March 1928&lt;/div&gt;`)[0];\n",
       "                popup_8359fccfb9e70a18e370829914c1204e.setContent(html_98decb5655af9ca4f069df92cf7d32d2);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_6269b1e1580e19c512f4f6965356800c.bindPopup(popup_8359fccfb9e70a18e370829914c1204e)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_83666230f83738fea8f76ea536dcd9ab = L.marker(\n",
       "                [40.2, 37.9],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_a199153f6c22950f589fdc25752dacd1 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_f8ee82c7e33a407de1f01a44e15f6e72 = $(`&lt;div id=&quot;html_f8ee82c7e33a407de1f01a44e15f6e72&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 64  Magnitude : 6.1 Mw  Date : 18 May 1929&lt;/div&gt;`)[0];\n",
       "                popup_a199153f6c22950f589fdc25752dacd1.setContent(html_f8ee82c7e33a407de1f01a44e15f6e72);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_83666230f83738fea8f76ea536dcd9ab.bindPopup(popup_a199153f6c22950f589fdc25752dacd1)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_e30e16ed7a4cf75766070fededc70a1a = L.marker(\n",
       "                [38.1, 44.7],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_a8d494f9db4fd6736168610d452199a9 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_d9d716e02cf83fa3658fd6f547e9fb33 = $(`&lt;div id=&quot;html_d9d716e02cf83fa3658fd6f547e9fb33&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2,514  Magnitude : 7.5 Mw  Date : 7 May 1930&lt;/div&gt;`)[0];\n",
       "                popup_a8d494f9db4fd6736168610d452199a9.setContent(html_d9d716e02cf83fa3658fd6f547e9fb33);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_e30e16ed7a4cf75766070fededc70a1a.bindPopup(popup_a8d494f9db4fd6736168610d452199a9)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_1fff8664c290b9e0f4007bb7710d56ec = L.marker(\n",
       "                [40.4, 27.5],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_d1df0b15618e13e8f88fbda32d5015e0 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_e6441f5c8862633d9947bd72d23ad4d6 = $(`&lt;div id=&quot;html_e6441f5c8862633d9947bd72d23ad4d6&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 5  Magnitude : 6.4 Mw  Date : 4 January 1935&lt;/div&gt;`)[0];\n",
       "                popup_d1df0b15618e13e8f88fbda32d5015e0.setContent(html_e6441f5c8862633d9947bd72d23ad4d6);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_1fff8664c290b9e0f4007bb7710d56ec.bindPopup(popup_d1df0b15618e13e8f88fbda32d5015e0)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_e943b3a7127ff4bcd3db883151ace80e = L.marker(\n",
       "                [39.1, 34.0],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_14762ae9158427fba2c3249e2d2cff5d = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_4bcd1808cba82a67a8ab90c11924f2b0 = $(`&lt;div id=&quot;html_4bcd1808cba82a67a8ab90c11924f2b0&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 160  Magnitude : 6.6 Mw  Date : 19 April 1938&lt;/div&gt;`)[0];\n",
       "                popup_14762ae9158427fba2c3249e2d2cff5d.setContent(html_4bcd1808cba82a67a8ab90c11924f2b0);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_e943b3a7127ff4bcd3db883151ace80e.bindPopup(popup_14762ae9158427fba2c3249e2d2cff5d)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_90dfe57f021f8b801f8be00b6514c74c = L.marker(\n",
       "                [39.1, 26.8],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_2905e30f421966933bcac0b707ae0156 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_6cf805d703db4d9e838d58714cf7862d = $(`&lt;div id=&quot;html_6cf805d703db4d9e838d58714cf7862d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 60  Magnitude : 6.6 Mw  Date : 22 September 1939&lt;/div&gt;`)[0];\n",
       "                popup_2905e30f421966933bcac0b707ae0156.setContent(html_6cf805d703db4d9e838d58714cf7862d);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_90dfe57f021f8b801f8be00b6514c74c.bindPopup(popup_2905e30f421966933bcac0b707ae0156)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_e85a0f5bf15fe3fe4fdca30e4f1db681 = L.marker(\n",
       "                [39.77, 39.53],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_4ce1171b74aaea9307deb126023694e5 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_b7be3cf5ad49145be1fd2265041ca6f0 = $(`&lt;div id=&quot;html_b7be3cf5ad49145be1fd2265041ca6f0&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 32,700  Magnitude : 7.8 Mw  Date : 26 December 1939&lt;/div&gt;`)[0];\n",
       "                popup_4ce1171b74aaea9307deb126023694e5.setContent(html_b7be3cf5ad49145be1fd2265041ca6f0);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_e85a0f5bf15fe3fe4fdca30e4f1db681.bindPopup(popup_4ce1171b74aaea9307deb126023694e5)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_9d86833d43c4ad4d278e080a99aae154 = L.marker(\n",
       "                [39.2, 28.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_8b324381cd179a604f4553f40ec93c46 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_b4ef0e7a22f6e8d3859e8fb4540c5c5a = $(`&lt;div id=&quot;html_b4ef0e7a22f6e8d3859e8fb4540c5c5a&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 16  Magnitude : 6.1 Mw  Date : 15 November 1942&lt;/div&gt;`)[0];\n",
       "                popup_8b324381cd179a604f4553f40ec93c46.setContent(html_b4ef0e7a22f6e8d3859e8fb4540c5c5a);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_9d86833d43c4ad4d278e080a99aae154.bindPopup(popup_8b324381cd179a604f4553f40ec93c46)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_49f9dde66196c722c1ea5920a7ded121 = L.marker(\n",
       "                [40.87, 36.47],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_d5247964d9819c5523cea21f3169495d = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_5a2accc7b93a51796fafeb177bb43c2e = $(`&lt;div id=&quot;html_5a2accc7b93a51796fafeb177bb43c2e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 3,000  Magnitude : 7.0 Mw  Date : 20 December 1942&lt;/div&gt;`)[0];\n",
       "                popup_d5247964d9819c5523cea21f3169495d.setContent(html_5a2accc7b93a51796fafeb177bb43c2e);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_49f9dde66196c722c1ea5920a7ded121.bindPopup(popup_d5247964d9819c5523cea21f3169495d)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_290b2e8419d6b36d43aaaf518fce3113 = L.marker(\n",
       "                [40.6, 30.5],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_b9764035d133c55f34e801f0d8ce5655 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_1605624819c9da7fe3933fd985a8084a = $(`&lt;div id=&quot;html_1605624819c9da7fe3933fd985a8084a&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 336  Magnitude : 6.6 Mw  Date : 20 June 1943&lt;/div&gt;`)[0];\n",
       "                popup_b9764035d133c55f34e801f0d8ce5655.setContent(html_1605624819c9da7fe3933fd985a8084a);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_290b2e8419d6b36d43aaaf518fce3113.bindPopup(popup_b9764035d133c55f34e801f0d8ce5655)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_59353aa1ea41aa15e06658da1e156e9d = L.marker(\n",
       "                [40.87, 33.65],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_244f2f4c08b09211e816f42d88186400 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_94647d82dd5a43f47a82fff03a27beef = $(`&lt;div id=&quot;html_94647d82dd5a43f47a82fff03a27beef&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 5,000  Magnitude : 7.5 Mw  Date : 26 November 1943&lt;/div&gt;`)[0];\n",
       "                popup_244f2f4c08b09211e816f42d88186400.setContent(html_94647d82dd5a43f47a82fff03a27beef);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_59353aa1ea41aa15e06658da1e156e9d.bindPopup(popup_244f2f4c08b09211e816f42d88186400)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_feddd23d81b86ef008f7afa69271dfde = L.marker(\n",
       "                [40.8, 32.2],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_a1dd082e5f88eabebf0000c1d7ad0d79 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_aabfd7f1cc01d4e7bc9f23770e288ee9 = $(`&lt;div id=&quot;html_aabfd7f1cc01d4e7bc9f23770e288ee9&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : \t3,959  Magnitude : 7.5 Mw  Date : 1 February 1944&lt;/div&gt;`)[0];\n",
       "                popup_a1dd082e5f88eabebf0000c1d7ad0d79.setContent(html_aabfd7f1cc01d4e7bc9f23770e288ee9);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_feddd23d81b86ef008f7afa69271dfde.bindPopup(popup_a1dd082e5f88eabebf0000c1d7ad0d79)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_e536a9dddf59015f5299bc0b5961cf6f = L.marker(\n",
       "                [39.37, 26.53],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_1e3182c23d9ffaa5a7b4fc7140894993 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_86b1ea62e5ce64762a4a1b8bc213d2ae = $(`&lt;div id=&quot;html_86b1ea62e5ce64762a4a1b8bc213d2ae&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : \t30  Magnitude : 6.8 Mw  Date : 6 October 1944&lt;/div&gt;`)[0];\n",
       "                popup_1e3182c23d9ffaa5a7b4fc7140894993.setContent(html_86b1ea62e5ce64762a4a1b8bc213d2ae);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_e536a9dddf59015f5299bc0b5961cf6f.bindPopup(popup_1e3182c23d9ffaa5a7b4fc7140894993)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_d834a0e15d57cc9a1a554616c01da784 = L.marker(\n",
       "                [39.54, 40.57],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_87e9ed04fd89ea198cb7c84ff4b4c260 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_9eb6e0114ed9da7e018a8a943d25a8da = $(`&lt;div id=&quot;html_9eb6e0114ed9da7e018a8a943d25a8da&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 450  Magnitude : 6.8 Mw  Date : 17 August 1949&lt;/div&gt;`)[0];\n",
       "                popup_87e9ed04fd89ea198cb7c84ff4b4c260.setContent(html_9eb6e0114ed9da7e018a8a943d25a8da);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_d834a0e15d57cc9a1a554616c01da784.bindPopup(popup_87e9ed04fd89ea198cb7c84ff4b4c260)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_fe859140d2dcb04c153788dfd704f6eb = L.marker(\n",
       "                [40.88, 32.87],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_2268167c7e634108effefbf8d5cf983e = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_72ff94024e1e2564459155026fddb92c = $(`&lt;div id=&quot;html_72ff94024e1e2564459155026fddb92c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 50  Magnitude : 6.9 Mw  Date : 13 August 1951&lt;/div&gt;`)[0];\n",
       "                popup_2268167c7e634108effefbf8d5cf983e.setContent(html_72ff94024e1e2564459155026fddb92c);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_fe859140d2dcb04c153788dfd704f6eb.bindPopup(popup_2268167c7e634108effefbf8d5cf983e)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_5dbc6cbf59cf5b0ace07a8eea8ca9754 = L.marker(\n",
       "                [39.9, 41.7],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_36fe9726cc6c2b4f71654256bec97efa = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_521886348edbaa15682ed1207e3f332f = $(`&lt;div id=&quot;html_521886348edbaa15682ed1207e3f332f&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 41  Magnitude : 5.8 Mw  Date : 3 January 1952&lt;/div&gt;`)[0];\n",
       "                popup_36fe9726cc6c2b4f71654256bec97efa.setContent(html_521886348edbaa15682ed1207e3f332f);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_5dbc6cbf59cf5b0ace07a8eea8ca9754.bindPopup(popup_36fe9726cc6c2b4f71654256bec97efa)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_f4d312661ebbfb4b7eef808be717edd0 = L.marker(\n",
       "                [40.02, 27.53],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_c747177f3cdd610eaa27e4db3b052be5 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_4b8294a3e6598cff16fe1fc08fd9e4c5 = $(`&lt;div id=&quot;html_4b8294a3e6598cff16fe1fc08fd9e4c5&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 265  Magnitude : 7.2 Mw  Date : 18 March 1953&lt;/div&gt;`)[0];\n",
       "                popup_c747177f3cdd610eaa27e4db3b052be5.setContent(html_4b8294a3e6598cff16fe1fc08fd9e4c5);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_f4d312661ebbfb4b7eef808be717edd0.bindPopup(popup_c747177f3cdd610eaa27e4db3b052be5)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_07c30b8eb8bef2c40e54b213414e673c = L.marker(\n",
       "                [37.55, 27.05],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_4c9d532b4657bc4b3ad603407ff9e260 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_ff7190f761e9efd133fd43515944ca69 = $(`&lt;div id=&quot;html_ff7190f761e9efd133fd43515944ca69&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 23  Magnitude : 6.8 Mw  Date : 16 July 1955&lt;/div&gt;`)[0];\n",
       "                popup_4c9d532b4657bc4b3ad603407ff9e260.setContent(html_ff7190f761e9efd133fd43515944ca69);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_07c30b8eb8bef2c40e54b213414e673c.bindPopup(popup_4c9d532b4657bc4b3ad603407ff9e260)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_bc19d8f936fa7c21ca0b797b7ee9c930 = L.marker(\n",
       "                [39.89, 30.49],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_bf63906526d68be53259a718d42bf5f3 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_65efe01c21c3f5eeda828deccb91276e = $(`&lt;div id=&quot;html_65efe01c21c3f5eeda828deccb91276e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1  Magnitude : 6.4 Mw  Date : 22 February 1956&lt;/div&gt;`)[0];\n",
       "                popup_bf63906526d68be53259a718d42bf5f3.setContent(html_65efe01c21c3f5eeda828deccb91276e);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_bc19d8f936fa7c21ca0b797b7ee9c930.bindPopup(popup_bf63906526d68be53259a718d42bf5f3)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_841f3cc02542f641a1c12fda744722e4 = L.marker(\n",
       "                [36.5, 28.6],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_a50d0ac85b300aecb64b1144d83aeeab = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_b187d4ef7271f052dc50f39d61713db7 = $(`&lt;div id=&quot;html_b187d4ef7271f052dc50f39d61713db7&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 67  Magnitude : 7.1 Mw  Date : 25 April 1957&lt;/div&gt;`)[0];\n",
       "                popup_a50d0ac85b300aecb64b1144d83aeeab.setContent(html_b187d4ef7271f052dc50f39d61713db7);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_841f3cc02542f641a1c12fda744722e4.bindPopup(popup_a50d0ac85b300aecb64b1144d83aeeab)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_2bc8155fb98b21698242e32d3ef843b7 = L.marker(\n",
       "                [40.67, 31.0],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_dd0772634fe18ce0dbf7ddcc74811218 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_7fa62bf1bdaa2910fea97e6313c13d80 = $(`&lt;div id=&quot;html_7fa62bf1bdaa2910fea97e6313c13d80&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 52  Magnitude : 7.1 Mw  Date : 26 May 1957&lt;/div&gt;`)[0];\n",
       "                popup_dd0772634fe18ce0dbf7ddcc74811218.setContent(html_7fa62bf1bdaa2910fea97e6313c13d80);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_2bc8155fb98b21698242e32d3ef843b7.bindPopup(popup_dd0772634fe18ce0dbf7ddcc74811218)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_7f781d83e5e24f385580913960399be8 = L.marker(\n",
       "                [40.1, 27.93],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_c26e9bf3999e965e25228ccb5954df32 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_b7aa4e5bcaad91d3b5cabc288ae4c9ef = $(`&lt;div id=&quot;html_b7aa4e5bcaad91d3b5cabc288ae4c9ef&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 23  Magnitude : 7.0 Mw  Date : 6 October 1964&lt;/div&gt;`)[0];\n",
       "                popup_c26e9bf3999e965e25228ccb5954df32.setContent(html_b7aa4e5bcaad91d3b5cabc288ae4c9ef);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_7f781d83e5e24f385580913960399be8.bindPopup(popup_c26e9bf3999e965e25228ccb5954df32)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_354be70a23f0af8a294764b7800d8bdd = L.marker(\n",
       "                [39.17, 41.56],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_f2ab51ee1c968055b39336f6f23a321a = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_296d5a4e35c95895eb61a0e8c44a2833 = $(`&lt;div id=&quot;html_296d5a4e35c95895eb61a0e8c44a2833&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2,394  Magnitude : 6.8 Mw  Date : 19 August 1966&lt;/div&gt;`)[0];\n",
       "                popup_f2ab51ee1c968055b39336f6f23a321a.setContent(html_296d5a4e35c95895eb61a0e8c44a2833);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_354be70a23f0af8a294764b7800d8bdd.bindPopup(popup_f2ab51ee1c968055b39336f6f23a321a)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_a8d9bd5a66d52b8e44e3d996c2cd6e99 = L.marker(\n",
       "                [40.67, 30.69],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_95a17e59ccbe71b50379a1e0c63c7a56 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_9a563743e16ffe44194709f3ab6b15e8 = $(`&lt;div id=&quot;html_9a563743e16ffe44194709f3ab6b15e8&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 89  Magnitude : 7.2 Mw  Date : 22 July 1967&lt;/div&gt;`)[0];\n",
       "                popup_95a17e59ccbe71b50379a1e0c63c7a56.setContent(html_9a563743e16ffe44194709f3ab6b15e8);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_a8d9bd5a66d52b8e44e3d996c2cd6e99.bindPopup(popup_95a17e59ccbe71b50379a1e0c63c7a56)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_b85fee9f6976aa5ea88e0981ef25f479 = L.marker(\n",
       "                [41.79, 32.31],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_1ef2f6ca9b920153477d507329c5996d = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_a0a39d776e51ca510d28fe330b9223fa = $(`&lt;div id=&quot;html_a0a39d776e51ca510d28fe330b9223fa&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 29  Magnitude : 6.5 Mw  Date : 3 September 1968&lt;/div&gt;`)[0];\n",
       "                popup_1ef2f6ca9b920153477d507329c5996d.setContent(html_a0a39d776e51ca510d28fe330b9223fa);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_b85fee9f6976aa5ea88e0981ef25f479.bindPopup(popup_1ef2f6ca9b920153477d507329c5996d)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_eaf1c490565ca75c247c04ad974606be = L.marker(\n",
       "                [38.5, 28.4],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_2450e7f72bd92991c5a2237127c92315 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_d5bae8280132dc7cc86ed1fa9a437c9e = $(`&lt;div id=&quot;html_d5bae8280132dc7cc86ed1fa9a437c9e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 53  Magnitude : 6.5 Mw  Date : 28 March 1969&lt;/div&gt;`)[0];\n",
       "                popup_2450e7f72bd92991c5a2237127c92315.setContent(html_d5bae8280132dc7cc86ed1fa9a437c9e);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_eaf1c490565ca75c247c04ad974606be.bindPopup(popup_2450e7f72bd92991c5a2237127c92315)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_77d0dadeb463c3d284ee6712998545b6 = L.marker(\n",
       "                [39.2, 29.5],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_6553a81771d0e29222355fc1ce57282f = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_e26a4f5614e8754e4e1c5e772035fa2c = $(`&lt;div id=&quot;html_e26a4f5614e8754e4e1c5e772035fa2c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1,086  Magnitude : 7.2 Mw  Date : 28 March 1970&lt;/div&gt;`)[0];\n",
       "                popup_6553a81771d0e29222355fc1ce57282f.setContent(html_e26a4f5614e8754e4e1c5e772035fa2c);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_77d0dadeb463c3d284ee6712998545b6.bindPopup(popup_6553a81771d0e29222355fc1ce57282f)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_0052db4c3ed88cd755bc8d44a8a09b80 = L.marker(\n",
       "                [38.83, 40.52],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_6cacafe73bf73b3b5f6a15a8ba75736b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_670921bcdc3735afce7c90e3470779be = $(`&lt;div id=&quot;html_670921bcdc3735afce7c90e3470779be&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 755  Magnitude : 6.9 Mw  Date : 22 May 1971&lt;/div&gt;`)[0];\n",
       "                popup_6cacafe73bf73b3b5f6a15a8ba75736b.setContent(html_670921bcdc3735afce7c90e3470779be);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_0052db4c3ed88cd755bc8d44a8a09b80.bindPopup(popup_6cacafe73bf73b3b5f6a15a8ba75736b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_33e64f3e5d8be8763e42baa1023f3088 = L.marker(\n",
       "                [38.5, 40.7],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_25a5bdbd3beaedb5ca95f26bb3b6e5fd = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_bdabf4568a26fb1a27e6af9536b0796d = $(`&lt;div id=&quot;html_bdabf4568a26fb1a27e6af9536b0796d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2,311  Magnitude : 6.6 Mw  Date : 6 September 1975&lt;/div&gt;`)[0];\n",
       "                popup_25a5bdbd3beaedb5ca95f26bb3b6e5fd.setContent(html_bdabf4568a26fb1a27e6af9536b0796d);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_33e64f3e5d8be8763e42baa1023f3088.bindPopup(popup_25a5bdbd3beaedb5ca95f26bb3b6e5fd)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_9b974c37f3bcac68716b514e7ffc58d2 = L.marker(\n",
       "                [39.12, 44.03],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_99f8a9ba0ad880c6e976920e09465b23 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_644cad71a3efd9546ce41c222534d8e0 = $(`&lt;div id=&quot;html_644cad71a3efd9546ce41c222534d8e0&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 4,000  Magnitude : 7.5 Mw  Date : 24 November 1976&lt;/div&gt;`)[0];\n",
       "                popup_99f8a9ba0ad880c6e976920e09465b23.setContent(html_644cad71a3efd9546ce41c222534d8e0);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_9b974c37f3bcac68716b514e7ffc58d2.bindPopup(popup_99f8a9ba0ad880c6e976920e09465b23)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_1c6905cc6551ad2b6383e76725bdfbea = L.marker(\n",
       "                [40.33, 42.19],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_9eebe6d06961c3a7a66b80faa92bd3e8 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_e123928e29d95a2b3286cd95216925b1 = $(`&lt;div id=&quot;html_e123928e29d95a2b3286cd95216925b1&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1,342  Magnitude : 6.9 Mw  Date : 30 October 1983&lt;/div&gt;`)[0];\n",
       "                popup_9eebe6d06961c3a7a66b80faa92bd3e8.setContent(html_e123928e29d95a2b3286cd95216925b1);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_1c6905cc6551ad2b6383e76725bdfbea.bindPopup(popup_9eebe6d06961c3a7a66b80faa92bd3e8)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_a9f1cc5d967cbc03779893f114eba75e = L.marker(\n",
       "                [39.7, 39.69],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_e4c5ea9826873bbadd64cf8a22dda9af = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_9daf4c3cd4f0b6356833afcc4baf5c58 = $(`&lt;div id=&quot;html_9daf4c3cd4f0b6356833afcc4baf5c58&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 498  Magnitude : 6.7 Mw  Date : 13 March 1992\t&lt;/div&gt;`)[0];\n",
       "                popup_e4c5ea9826873bbadd64cf8a22dda9af.setContent(html_9daf4c3cd4f0b6356833afcc4baf5c58);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_a9f1cc5d967cbc03779893f114eba75e.bindPopup(popup_e4c5ea9826873bbadd64cf8a22dda9af)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_d23403f855bf92d33deb78fa66c44bf9 = L.marker(\n",
       "                [38.06, 30.13],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_3ea6c719c9a4a54ea15536d73cc2e8d7 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_9630191f49cbfccd9a990e259b7a43ae = $(`&lt;div id=&quot;html_9630191f49cbfccd9a990e259b7a43ae&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 90  Magnitude : 6.1 Mw  Date : 1 October 1995&lt;/div&gt;`)[0];\n",
       "                popup_3ea6c719c9a4a54ea15536d73cc2e8d7.setContent(html_9630191f49cbfccd9a990e259b7a43ae);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_d23403f855bf92d33deb78fa66c44bf9.bindPopup(popup_3ea6c719c9a4a54ea15536d73cc2e8d7)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_ee756be53fb82158d5102e44ace81501 = L.marker(\n",
       "                [36.88, 35.31],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_f3a5932994f2624e62d7722aa06eeb22 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_1c8da8f6cd3006bd0368279464b5789e = $(`&lt;div id=&quot;html_1c8da8f6cd3006bd0368279464b5789e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 146  Magnitude : 6.3 Mw  Date : 27 June 1998&lt;/div&gt;`)[0];\n",
       "                popup_f3a5932994f2624e62d7722aa06eeb22.setContent(html_1c8da8f6cd3006bd0368279464b5789e);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_ee756be53fb82158d5102e44ace81501.bindPopup(popup_f3a5932994f2624e62d7722aa06eeb22)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_150bee03b07847cc9695ada372208e85 = L.marker(\n",
       "                [40.77, 30.0],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_30968e143e7910a2ab7a91e6212ad6f9 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_05c81eb1061ace4046ec99612a32ecba = $(`&lt;div id=&quot;html_05c81eb1061ace4046ec99612a32ecba&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 17,127  Magnitude : 7.6 Mw  Date : 17 August 1999&lt;/div&gt;`)[0];\n",
       "                popup_30968e143e7910a2ab7a91e6212ad6f9.setContent(html_05c81eb1061ace4046ec99612a32ecba);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_150bee03b07847cc9695ada372208e85.bindPopup(popup_30968e143e7910a2ab7a91e6212ad6f9)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_0108bede6e8df9ddd417d7cddead0f47 = L.marker(\n",
       "                [40.75, 31.16],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_32540f1748db7712dc3d252922142319 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_7cdd87ed172f895d6eebeb43b7f0496b = $(`&lt;div id=&quot;html_7cdd87ed172f895d6eebeb43b7f0496b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 894  Magnitude : 7.2 Mw  Date : 12 November 1999&lt;/div&gt;`)[0];\n",
       "                popup_32540f1748db7712dc3d252922142319.setContent(html_7cdd87ed172f895d6eebeb43b7f0496b);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_0108bede6e8df9ddd417d7cddead0f47.bindPopup(popup_32540f1748db7712dc3d252922142319)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_444017fd001f0d2a910f93ca05aaec9a = L.marker(\n",
       "                [38.573, 31.271],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_533001364f0ef9126430135190f55059 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_c8153b20da1399b8df3e65290ef820a1 = $(`&lt;div id=&quot;html_c8153b20da1399b8df3e65290ef820a1&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 44  Magnitude : 6.5 Mw  Date : 3 February 2002&lt;/div&gt;`)[0];\n",
       "                popup_533001364f0ef9126430135190f55059.setContent(html_c8153b20da1399b8df3e65290ef820a1);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_444017fd001f0d2a910f93ca05aaec9a.bindPopup(popup_533001364f0ef9126430135190f55059)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_cdb11d95b8f28e02584390adc99c50b9 = L.marker(\n",
       "                [39.46, 39.79],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_a60a6304ba1912d47efbb8c16cd01bc3 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_617ca571a4ec03aa1aad26d07d57ee4d = $(`&lt;div id=&quot;html_617ca571a4ec03aa1aad26d07d57ee4d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1  Magnitude : 6.1 Mw  Date : 27 January 2003&lt;/div&gt;`)[0];\n",
       "                popup_a60a6304ba1912d47efbb8c16cd01bc3.setContent(html_617ca571a4ec03aa1aad26d07d57ee4d);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_cdb11d95b8f28e02584390adc99c50b9.bindPopup(popup_a60a6304ba1912d47efbb8c16cd01bc3)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_7aca30456ac596afae49c50cd9d26355 = L.marker(\n",
       "                [39.01, 40.46],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_e962d88947fd03ca13c2aa42961d1847 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_8b7e8994d6ef471de62f2c5624f06526 = $(`&lt;div id=&quot;html_8b7e8994d6ef471de62f2c5624f06526&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 177\t  Magnitude : 6.4 Mw  Date : 1 May 2003&lt;/div&gt;`)[0];\n",
       "                popup_e962d88947fd03ca13c2aa42961d1847.setContent(html_8b7e8994d6ef471de62f2c5624f06526);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_7aca30456ac596afae49c50cd9d26355.bindPopup(popup_e962d88947fd03ca13c2aa42961d1847)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_e1671573af6d132f384cad8b95e5d7ce = L.marker(\n",
       "                [39.71, 44.02],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_800553cd3d99738a693715e7a1908939 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_953684014293ed78f0cc0a1aa987de16 = $(`&lt;div id=&quot;html_953684014293ed78f0cc0a1aa987de16&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 18  Magnitude : 5.1 Mw  Date : 2 July 2004&lt;/div&gt;`)[0];\n",
       "                popup_800553cd3d99738a693715e7a1908939.setContent(html_953684014293ed78f0cc0a1aa987de16);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_e1671573af6d132f384cad8b95e5d7ce.bindPopup(popup_800553cd3d99738a693715e7a1908939)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_7ece70fa5087f19b0061df406a364681 = L.marker(\n",
       "                [38.79, 40.03],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_0823f7a15c8db2a6188a10291f67fefd = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_daf1e52f893d66ab65444361afc6f702 = $(`&lt;div id=&quot;html_daf1e52f893d66ab65444361afc6f702&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 41  Magnitude : 6.1 Mw  Date : 8 March 2010&lt;/div&gt;`)[0];\n",
       "                popup_0823f7a15c8db2a6188a10291f67fefd.setContent(html_daf1e52f893d66ab65444361afc6f702);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_7ece70fa5087f19b0061df406a364681.bindPopup(popup_0823f7a15c8db2a6188a10291f67fefd)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_0c8be50b440ca1bd6a1fc257095a979f = L.marker(\n",
       "                [39.14, 29.07],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_bf2d81e462daf0a33e45b66a7981d14e = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_fb546f1345f015ff708ce04e0a73765c = $(`&lt;div id=&quot;html_fb546f1345f015ff708ce04e0a73765c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2  Magnitude : 5.8 Mw  Date : 19 May 2011&lt;/div&gt;`)[0];\n",
       "                popup_bf2d81e462daf0a33e45b66a7981d14e.setContent(html_fb546f1345f015ff708ce04e0a73765c);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_0c8be50b440ca1bd6a1fc257095a979f.bindPopup(popup_bf2d81e462daf0a33e45b66a7981d14e)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_cf8c7788cf2b2b106f0711ee6cb7a8ba = L.marker(\n",
       "                [38.63, 43.49],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_43310a9ba3db887f1f2f056984d02e24 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_d890512fde789ecad0ec4b21914658be = $(`&lt;div id=&quot;html_d890512fde789ecad0ec4b21914658be&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 604  Magnitude : 7.2 Mw  Date : 23 October 2011&lt;/div&gt;`)[0];\n",
       "                popup_43310a9ba3db887f1f2f056984d02e24.setContent(html_d890512fde789ecad0ec4b21914658be);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_cf8c7788cf2b2b106f0711ee6cb7a8ba.bindPopup(popup_43310a9ba3db887f1f2f056984d02e24)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_3b9c9632d61cbbdf31d749c6047d7020 = L.marker(\n",
       "                [38.42, 43.22],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_ac3a61f890ad7ca2c1c6a728791730a5 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_55c383a6476de888d6236fab93f3f1d6 = $(`&lt;div id=&quot;html_55c383a6476de888d6236fab93f3f1d6&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 40  Magnitude : 5.6 Mw  Date : 9 November 2011&lt;/div&gt;`)[0];\n",
       "                popup_ac3a61f890ad7ca2c1c6a728791730a5.setContent(html_55c383a6476de888d6236fab93f3f1d6);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_3b9c9632d61cbbdf31d749c6047d7020.bindPopup(popup_ac3a61f890ad7ca2c1c6a728791730a5)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_dfb4bc9b17279f854150378071ca8ca6 = L.marker(\n",
       "                [40.31, 25.45],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_c1d8c3b59a9e88cf425110111bec7148 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_71327f743efae548879e5bf070b51e0d = $(`&lt;div id=&quot;html_71327f743efae548879e5bf070b51e0d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 0  Magnitude : 6.9 Mw  Date : 24 May 2014&lt;/div&gt;`)[0];\n",
       "                popup_c1d8c3b59a9e88cf425110111bec7148.setContent(html_71327f743efae548879e5bf070b51e0d);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_dfb4bc9b17279f854150378071ca8ca6.bindPopup(popup_c1d8c3b59a9e88cf425110111bec7148)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_54ac6f39359db09691f066a175b43c3c = L.marker(\n",
       "                [36.92, 27.41],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_9af23cbdd8d12351c4f389bbae4f249a = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_89be2bcae5de2bccf5d56cbda3e8e6da = $(`&lt;div id=&quot;html_89be2bcae5de2bccf5d56cbda3e8e6da&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2   Magnitude : nan  Date : 21 July 2017&lt;/div&gt;`)[0];\n",
       "                popup_9af23cbdd8d12351c4f389bbae4f249a.setContent(html_89be2bcae5de2bccf5d56cbda3e8e6da);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_54ac6f39359db09691f066a175b43c3c.bindPopup(popup_9af23cbdd8d12351c4f389bbae4f249a)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_2d439109ffc623b6af2821c7243b04e0 = L.marker(\n",
       "                [40.89, 28.17],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_e697de3f883b37e50edfd54c4bf9d1cd = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_2afd887a4edb6057f1b6f18dc43d0094 = $(`&lt;div id=&quot;html_2afd887a4edb6057f1b6f18dc43d0094&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1  Magnitude : 5.7 Mw  Date : 26 September 2019&lt;/div&gt;`)[0];\n",
       "                popup_e697de3f883b37e50edfd54c4bf9d1cd.setContent(html_2afd887a4edb6057f1b6f18dc43d0094);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_2d439109ffc623b6af2821c7243b04e0.bindPopup(popup_e697de3f883b37e50edfd54c4bf9d1cd)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_d73ea9526c536803f03427b68e5b0282 = L.marker(\n",
       "                [38.39, 39.081],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_0c459b116db28e43eaca32c3b807cde3 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_d24aa348b94f14ce7f88fdbc9c1a7a0b = $(`&lt;div id=&quot;html_d24aa348b94f14ce7f88fdbc9c1a7a0b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 41  Magnitude : 6.7 Mw  Date : 24 January 2020&lt;/div&gt;`)[0];\n",
       "                popup_0c459b116db28e43eaca32c3b807cde3.setContent(html_d24aa348b94f14ce7f88fdbc9c1a7a0b);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_d73ea9526c536803f03427b68e5b0282.bindPopup(popup_0c459b116db28e43eaca32c3b807cde3)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_2bacc3fdbf67110f86a8d99893f37e7b = L.marker(\n",
       "                [38.39, 39.081],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_8d1bc1f452d72c1762450fe80fe7c38b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_36a5165385c68041e07f1e7cbd0f799e = $(`&lt;div id=&quot;html_36a5165385c68041e07f1e7cbd0f799e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 41  Magnitude : 6.7 Mw  Date : 24 January 2020&lt;/div&gt;`)[0];\n",
       "                popup_8d1bc1f452d72c1762450fe80fe7c38b.setContent(html_36a5165385c68041e07f1e7cbd0f799e);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_2bacc3fdbf67110f86a8d99893f37e7b.bindPopup(popup_8d1bc1f452d72c1762450fe80fe7c38b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_bded08c0c41165883fefdb27df687c01 = L.marker(\n",
       "                [39.42, 40.67],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_d3b5f330ccfcc8dd5b6ca6781046e606 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_e7c429de573712e11321a71672b6d611 = $(`&lt;div id=&quot;html_e7c429de573712e11321a71672b6d611&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 1  Magnitude : 5.9 Mw  Date : 14 June 2020&lt;/div&gt;`)[0];\n",
       "                popup_d3b5f330ccfcc8dd5b6ca6781046e606.setContent(html_e7c429de573712e11321a71672b6d611);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_bded08c0c41165883fefdb27df687c01.bindPopup(popup_d3b5f330ccfcc8dd5b6ca6781046e606)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_21ccc000b15315b3547bf61436208c22 = L.marker(\n",
       "                [37.918, 26.79],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_d9886f4870ba9034a4ae23ddb988494a = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_460b7efc9a7d13242b688d5a104fa41c = $(`&lt;div id=&quot;html_460b7efc9a7d13242b688d5a104fa41c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 117  Magnitude : 7.0 Mw  Date : 30 October 2020&lt;/div&gt;`)[0];\n",
       "                popup_d9886f4870ba9034a4ae23ddb988494a.setContent(html_460b7efc9a7d13242b688d5a104fa41c);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_21ccc000b15315b3547bf61436208c22.bindPopup(popup_d9886f4870ba9034a4ae23ddb988494a)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_6dec43b05a458c03ef554608512ae416 = L.marker(\n",
       "                [40.847, 30.967],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_b81684194d53895032f055a45fe92957 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_5c80dbee926d4009308e477c08673480 = $(`&lt;div id=&quot;html_5c80dbee926d4009308e477c08673480&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 2  Magnitude : 6.1 Mw  Date : 23 November 2022&lt;/div&gt;`)[0];\n",
       "                popup_b81684194d53895032f055a45fe92957.setContent(html_5c80dbee926d4009308e477c08673480);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_6dec43b05a458c03ef554608512ae416.bindPopup(popup_b81684194d53895032f055a45fe92957)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_70467f742a9ff7acfb33d2ed3546ba47 = L.marker(\n",
       "                [37.1123, 37.1195],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_fd593be8ccdf5838f80b8129448ac19c = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_2681fcd0b61d6a4df4aef62e2e04bc22 = $(`&lt;div id=&quot;html_2681fcd0b61d6a4df4aef62e2e04bc22&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 29,600  Magnitude : 7.8 Mw  Date : 6 February 2023&lt;/div&gt;`)[0];\n",
       "                popup_fd593be8ccdf5838f80b8129448ac19c.setContent(html_2681fcd0b61d6a4df4aef62e2e04bc22);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_70467f742a9ff7acfb33d2ed3546ba47.bindPopup(popup_fd593be8ccdf5838f80b8129448ac19c)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_f278c5b6adbdbcd8a8f627376d2bd196 = L.marker(\n",
       "                [38.0357, 37.2287],\n",
       "                {}\n",
       "            ).addTo(map_1623657bc1ed67f62e947c58134a4116);\n",
       "        \n",
       "    \n",
       "        var popup_80885e225ae381212b320dad8f13016a = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_7a62ccd8e08ff9c0191e9412af57b7ef = $(`&lt;div id=&quot;html_7a62ccd8e08ff9c0191e9412af57b7ef&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;number of Deaths : 29,600  Magnitude : 7.7 Mw  Date : 6 February 2023&lt;/div&gt;`)[0];\n",
       "                popup_80885e225ae381212b320dad8f13016a.setContent(html_7a62ccd8e08ff9c0191e9412af57b7ef);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_f278c5b6adbdbcd8a8f627376d2bd196.bindPopup(popup_80885e225ae381212b320dad8f13016a)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x23b26cc2400>"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_1 = folium.Map(location=(TURK_LAT, TURK_LNG), titles='cartodbpositron', zooms=5)\n",
    "for i, row in gdf_earthquakes.iterrows():\n",
    "    popup_text = \"number of Deaths : \" + str(row.Deaths) + \"\\n Magnitude : \"+ str(row.Mag) + \"\\n Date : \" + str(row.Date)\n",
    "    Marker([row.geometry.y, row.geometry.x], popup=popup_text).add_to(m_1)\n",
    "m_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Cleaning Deaths column\n",
    "gdf_earthquakes.Deaths = gdf_earthquakes.Deaths.str.strip()\n",
    "gdf_earthquakes.Deaths = gdf_earthquakes.Deaths.map(lambda s: s.replace(',', ''))\n",
    "gdf_earthquakes.Deaths = gdf_earthquakes.Deaths.astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.9000</td>\n",
       "      <td>28.7000</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>38.2000</td>\n",
       "      <td>28.2000</td>\n",
       "      <td>2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.0000</td>\n",
       "      <td>36.0000</td>\n",
       "      <td>8000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>38.4000</td>\n",
       "      <td>26.9000</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.8000</td>\n",
       "      <td>29.0000</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>39.4200</td>\n",
       "      <td>40.6700</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>37.9180</td>\n",
       "      <td>26.7900</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>40.8470</td>\n",
       "      <td>30.9670</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>37.1123</td>\n",
       "      <td>37.1195</td>\n",
       "      <td>29600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>38.0357</td>\n",
       "      <td>37.2287</td>\n",
       "      <td>29600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Lat     Long  Deaths\n",
       "0   40.9000  28.7000   10000\n",
       "1   38.2000  28.2000    2500\n",
       "2   40.0000  36.0000    8000\n",
       "3   38.4000  26.9000   16000\n",
       "4   40.8000  29.0000    4000\n",
       "..      ...      ...     ...\n",
       "73  39.4200  40.6700       1\n",
       "74  37.9180  26.7900     117\n",
       "75  40.8470  30.9670       2\n",
       "76  37.1123  37.1195   29600\n",
       "77  38.0357  37.2287   29600\n",
       "\n",
       "[78 rows x 3 columns]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_earthquakes.loc[:, ['Lat', 'Long', 'Deaths']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_83fed41a060ba0fe5b2ec010e19e9f0f {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium@main/folium/templates/leaflet_heat.min.js&quot;&gt;&lt;/script&gt;\n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_83fed41a060ba0fe5b2ec010e19e9f0f&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_83fed41a060ba0fe5b2ec010e19e9f0f = L.map(\n",
       "                &quot;map_83fed41a060ba0fe5b2ec010e19e9f0f&quot;,\n",
       "                {\n",
       "                    center: [39.0618, 33.75],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 10,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                    zooms: 15,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_435eec5b1b19a3c99676b0af8372cbca = L.tileLayer(\n",
       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_83fed41a060ba0fe5b2ec010e19e9f0f);\n",
       "        \n",
       "    \n",
       "            var heat_map_702248cfc4e0b18b5bd4c396b51f0258 = L.heatLayer(\n",
       "                [[40.9, 28.7, 10000.0], [38.2, 28.2, 2500.0], [40.0, 36.0, 8000.0], [38.4, 26.9, 16000.0], [40.8, 29.0, 4000.0], [39.5, 40.2, 7500.0], [39.6, 44.1, 10000.0], [40.2, 29.1, 1900.0], [39.9, 41.3, 15000.0], [36.4, 36.4, 1800.0], [38.25, 26.25, 7866.0], [38.25, 26.25, 7866.0], [38.25, 26.25, 7866.0], [38.3, 26.2, 120.0], [38.3, 26.2, 120.0], [38.3, 26.2, 120.0], [40.73, 29.25, 1300.0], [37.9, 28.1, 1470.0], [39.14, 42.65, 600.0], [40.75, 27.2, 216.0], [37.82, 30.27, 2344.0], [39.18, 27.65, 3000.0], [40.0, 42.1, 60.0], [40.7, 43.7, 360.0], [38.5, 28.0, 50.0], [40.2, 37.9, 64.0], [38.1, 44.7, 2514.0], [40.4, 27.5, 5.0], [39.1, 34.0, 160.0], [39.1, 26.8, 60.0], [39.77, 39.53, 32700.0], [39.2, 28.2, 16.0], [40.87, 36.47, 3000.0], [40.6, 30.5, 336.0], [40.87, 33.65, 5000.0], [40.8, 32.2, 3959.0], [39.37, 26.53, 30.0], [39.54, 40.57, 450.0], [40.88, 32.87, 50.0], [39.9, 41.7, 41.0], [40.02, 27.53, 265.0], [37.55, 27.05, 23.0], [39.89, 30.49, 1.0], [36.5, 28.6, 67.0], [40.67, 31.0, 52.0], [40.1, 27.93, 23.0], [39.17, 41.56, 2394.0], [40.67, 30.69, 89.0], [41.79, 32.31, 29.0], [38.5, 28.4, 53.0], [39.2, 29.5, 1086.0], [38.83, 40.52, 755.0], [38.5, 40.7, 2311.0], [39.12, 44.03, 4000.0], [40.33, 42.19, 1342.0], [39.7, 39.69, 498.0], [38.06, 30.13, 90.0], [36.88, 35.31, 146.0], [40.77, 30.0, 17127.0], [40.75, 31.16, 894.0], [38.573, 31.271, 44.0], [39.46, 39.79, 1.0], [39.01, 40.46, 177.0], [39.71, 44.02, 18.0], [38.79, 40.03, 41.0], [39.14, 29.07, 2.0], [38.63, 43.49, 604.0], [38.42, 43.22, 40.0], [40.31, 25.45, 0.0], [36.92, 27.41, 2.0], [40.89, 28.17, 1.0], [38.39, 39.081, 41.0], [38.39, 39.081, 41.0], [39.42, 40.67, 1.0], [37.918, 26.79, 117.0], [40.847, 30.967, 2.0], [37.1123, 37.1195, 29600.0], [38.0357, 37.2287, 29600.0]],\n",
       "                {&quot;blur&quot;: 15, &quot;gradient&quot;: {&quot;0.4&quot;: &quot;blue&quot;, &quot;0.65&quot;: &quot;lime&quot;, &quot;1&quot;: &quot;red&quot;}, &quot;maxZoom&quot;: 18, &quot;minOpacity&quot;: 0.5, &quot;radius&quot;: 25}\n",
       "            ).addTo(map_83fed41a060ba0fe5b2ec010e19e9f0f);\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x23b29566c40>"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_3 = folium.Map(location=(TURK_LAT, TURK_LNG),zooms=15)\n",
    "HeatMap(gdf_earthquakes.loc[:, ['Lat', 'Long', 'Deaths']], gradient={0.4: 'blue', 0.65: 'lime', 1: 'red'}).add_to(m_3)\n",
    "m_3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "customdata": [
          [
           "7.2 Mw",
           null
          ],
          [
           "7.5 Mw",
           null
          ],
          [
           "8M w",
           null
          ],
          [
           "7.0 Mw",
           "1688-07-10T00:00:00"
          ],
          [
           "7.1 Mw",
           "1766-05-22T00:00:00"
          ],
          [
           "7.6 Mw",
           "1784-07-23T00:00:00"
          ],
          [
           "7.4 Mw",
           "1840-07-02T00:00:00"
          ],
          [
           "6.7 Mw",
           "1855-02-28T00:00:00"
          ],
          [
           "6.1 Mw",
           "1859-06-02T00:00:00"
          ],
          [
           "7.2 Mw",
           "1872-04-03T00:00:00"
          ],
          [
           "7.3 Mw",
           "1881-04-03T00:00:00"
          ],
          [
           "7.3 Mw",
           "1881-04-03T00:00:00"
          ],
          [
           "7.3 Mw",
           "1881-04-03T00:00:00"
          ],
          [
           "7.3 Mw",
           "1883-10-10T00:00:00"
          ],
          [
           "7.3 Mw",
           "1883-10-10T00:00:00"
          ],
          [
           "7.3 Mw",
           "1883-10-10T00:00:00"
          ],
          [
           "7.0 Mw",
           "1894-07-10T00:00:00"
          ],
          [
           "7.1 Mw",
           "1899-09-20T00:00:00"
          ],
          [
           "6.7 Mw",
           "1903-04-29T00:00:00"
          ],
          [
           "7.3 Mw",
           "1912-08-09T00:00:00"
          ],
          [
           "6.9 Mw",
           "1914-10-04T00:00:00"
          ],
          [
           "7.0 Mw",
           "1919-11-18T00:00:00"
          ],
          [
           "6.8 Mw",
           "1924-09-13T00:00:00"
          ],
          [
           "6.0 Mw",
           "1926-10-22T00:00:00"
          ],
          [
           "6.5 Mw",
           "1928-03-31T00:00:00"
          ],
          [
           "6.1 Mw",
           "1929-05-18T00:00:00"
          ],
          [
           "7.5 Mw",
           "1930-05-07T00:00:00"
          ],
          [
           "6.4 Mw",
           "1935-01-04T00:00:00"
          ],
          [
           "6.6 Mw",
           "1938-04-19T00:00:00"
          ],
          [
           "6.6 Mw",
           "1939-09-22T00:00:00"
          ],
          [
           "7.8 Mw",
           "1939-12-26T00:00:00"
          ],
          [
           "6.1 Mw",
           "1942-11-15T00:00:00"
          ],
          [
           "7.0 Mw",
           "1942-12-20T00:00:00"
          ],
          [
           "6.6 Mw",
           "1943-06-20T00:00:00"
          ],
          [
           "7.5 Mw",
           "1943-11-26T00:00:00"
          ],
          [
           "7.5 Mw",
           "1944-02-01T00:00:00"
          ],
          [
           "6.8 Mw",
           "1944-10-06T00:00:00"
          ],
          [
           "6.8 Mw",
           "1949-08-17T00:00:00"
          ],
          [
           "6.9 Mw",
           "1951-08-13T00:00:00"
          ],
          [
           "5.8 Mw",
           "1952-01-03T00:00:00"
          ],
          [
           "7.2 Mw",
           "1953-03-18T00:00:00"
          ],
          [
           "6.8 Mw",
           "1955-07-16T00:00:00"
          ],
          [
           "6.4 Mw",
           "1956-02-22T00:00:00"
          ],
          [
           "7.1 Mw",
           "1957-04-25T00:00:00"
          ],
          [
           "7.1 Mw",
           "1957-05-26T00:00:00"
          ],
          [
           "7.0 Mw",
           "1964-10-06T00:00:00"
          ],
          [
           "6.8 Mw",
           "1966-08-19T00:00:00"
          ],
          [
           "7.2 Mw",
           "1967-07-22T00:00:00"
          ],
          [
           "6.5 Mw",
           "1968-09-03T00:00:00"
          ],
          [
           "6.5 Mw",
           "1969-03-28T00:00:00"
          ],
          [
           "7.2 Mw",
           "1970-03-28T00:00:00"
          ],
          [
           "6.9 Mw",
           "1971-05-22T00:00:00"
          ],
          [
           "6.6 Mw",
           "1975-09-06T00:00:00"
          ],
          [
           "7.5 Mw",
           "1976-11-24T00:00:00"
          ],
          [
           "6.9 Mw",
           "1983-10-30T00:00:00"
          ],
          [
           "6.7 Mw",
           null
          ],
          [
           "6.1 Mw",
           "1995-10-01T00:00:00"
          ],
          [
           "6.3 Mw",
           "1998-06-27T00:00:00"
          ],
          [
           "7.6 Mw",
           "1999-08-17T00:00:00"
          ],
          [
           "7.2 Mw",
           "1999-11-12T00:00:00"
          ],
          [
           "6.5 Mw",
           "2002-02-03T00:00:00"
          ],
          [
           "6.1 Mw",
           "2003-01-27T00:00:00"
          ],
          [
           "6.4 Mw",
           "2003-05-01T00:00:00"
          ],
          [
           "5.1 Mw",
           "2004-07-02T00:00:00"
          ],
          [
           "6.1 Mw",
           "2010-03-08T00:00:00"
          ],
          [
           "5.8 Mw",
           "2011-05-19T00:00:00"
          ],
          [
           "7.2 Mw",
           "2011-10-23T00:00:00"
          ],
          [
           "5.6 Mw",
           "2011-11-09T00:00:00"
          ],
          [
           "6.9 Mw",
           "2014-05-24T00:00:00"
          ],
          [
           null,
           "2017-07-21T00:00:00"
          ],
          [
           "5.7 Mw",
           "2019-09-26T00:00:00"
          ],
          [
           "6.7 Mw",
           "2020-01-24T00:00:00"
          ],
          [
           "6.7 Mw",
           "2020-01-24T00:00:00"
          ],
          [
           "5.9 Mw",
           "2020-06-14T00:00:00"
          ],
          [
           "7.0 Mw",
           "2020-10-30T00:00:00"
          ],
          [
           "6.1 Mw",
           "2022-11-23T00:00:00"
          ],
          [
           "7.8 Mw",
           "2023-02-06T00:00:00"
          ],
          [
           "7.7 Mw",
           "2023-02-06T00:00:00"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>Lat=%{lat}<br>Long=%{lon}<br>Mag=%{customdata[0]}<br>parsed_Date=%{customdata[1]}<extra></extra>",
         "hovertext": [
          "Constantinople",
          "Smyrna",
          "Anatolia",
          "Smyrna",
          "Istanbul",
          "Erzincan",
          "Ağrı",
          "Bursa",
          "Erzurum",
          "Hatay",
          "Chios",
          "Çeşme",
          "Alaçatı",
          "Çeşme",
          "Ayvalık",
          "Izmir",
          "Gulf of İzmit",
          "Büyük Menderes Graben",
          "Malazgirt",
          "Mürefte",
          "\tBurdur",
          "Balıkesir",
          "Horasan",
          "Kars",
          "Smyrna",
          "\tSuşehri",
          "Hakkâri",
          "Erdek",
          "Kırşehir",
          "Dikili",
          "Erzincan",
          "Bigadiç",
          "Erbaa",
          "Hendek",
          "Ladik",
          "Gerede",
          "Ayvalık",
          "Karlıova",
          "Kurşunlu",
          "Hasankale",
          "Yenice",
          "Söke",
          "Eskişehir",
          "Fethiye",
          "Abant",
          "Manyas",
          "\tVarto",
          "Mudurnu",
          "Bartın",
          "Alaşehir",
          "Gediz",
          "Bingöl",
          "Lice",
          "Muradiye",
          "Erzurum",
          "Erzincan",
          "Dinar",
          "Ceyhan",
          "\tİzmit",
          "Düzce",
          "Afyon",
          "Pülümür",
          "Bingöl",
          "Ağrı",
          "Elazığ",
          "Kütahya",
          "Van",
          "Van",
          "\tImbros",
          "Bodrum",
          "Marmara Region",
          "Elazığ",
          "Malatya",
          "Bingöl",
          "\tAegean Sea",
          "Düzce",
          "Gaziantep",
          "Kahramanmaraş"
         ],
         "lat": [
          40.9,
          38.2,
          40,
          38.4,
          40.8,
          39.5,
          39.6,
          40.2,
          39.9,
          36.4,
          38.25,
          38.25,
          38.25,
          38.3,
          38.3,
          38.3,
          40.73,
          37.9,
          39.14,
          40.75,
          37.82,
          39.18,
          40,
          40.7,
          38.5,
          40.2,
          38.1,
          40.4,
          39.1,
          39.1,
          39.77,
          39.2,
          40.87,
          40.6,
          40.87,
          40.8,
          39.37,
          39.54,
          40.88,
          39.9,
          40.02,
          37.55,
          39.89,
          36.5,
          40.67,
          40.1,
          39.17,
          40.67,
          41.79,
          38.5,
          39.2,
          38.83,
          38.5,
          39.12,
          40.33,
          39.7,
          38.06,
          36.88,
          40.77,
          40.75,
          38.573,
          39.46,
          39.01,
          39.71,
          38.79,
          39.14,
          38.63,
          38.42,
          40.31,
          36.92,
          40.89,
          38.39,
          38.39,
          39.42,
          37.918,
          40.847,
          37.1123,
          38.0357
         ],
         "legendgroup": "",
         "lon": [
          28.7,
          28.2,
          36,
          26.9,
          29,
          40.2,
          44.1,
          29.1,
          41.3,
          36.4,
          26.25,
          26.25,
          26.25,
          26.2,
          26.2,
          26.2,
          29.25,
          28.1,
          42.65,
          27.2,
          30.27,
          27.65,
          42.1,
          43.7,
          28,
          37.9,
          44.7,
          27.5,
          34,
          26.8,
          39.53,
          28.2,
          36.47,
          30.5,
          33.65,
          32.2,
          26.53,
          40.57,
          32.87,
          41.7,
          27.53,
          27.05,
          30.49,
          28.6,
          31,
          27.93,
          41.56,
          30.69,
          32.31,
          28.4,
          29.5,
          40.52,
          40.7,
          44.03,
          42.19,
          39.69,
          30.13,
          35.31,
          30,
          31.16,
          31.271,
          39.79,
          40.46,
          44.02,
          40.03,
          29.07,
          43.49,
          43.22,
          25.45,
          27.41,
          28.17,
          39.081,
          39.081,
          40.67,
          26.79,
          30.967,
          37.1195,
          37.2287
         ],
         "marker": {
          "color": "light green"
         },
         "mode": "markers",
         "name": "",
         "showlegend": false,
         "subplot": "mapbox",
         "type": "scattermapbox"
        }
       ],
       "layout": {
        "height": 300,
        "legend": {
         "tracegroupgap": 0
        },
        "mapbox": {
         "center": {
          "lat": 39.28123076923076,
          "lon": 33.60766923076923
         },
         "domain": {
          "x": [
           0,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "style": "open-street-map",
         "zoom": 5
        },
        "margin": {
         "b": 0,
         "l": 0,
         "r": 0,
         "t": 0
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.scatter_mapbox(gdf_earthquakes, lat=\"Lat\", lon=\"Long\", hover_name=\"Place\", hover_data=[\"Mag\", \"parsed_Date\"],\n",
    "                        color_discrete_sequence=[\"light green\"], zoom=5, height=300)\n",
    "fig.update_layout(mapbox_style=\"open-street-map\")\n",
    "fig.update_layout(margin={\"r\":0,\"t\":0,\"l\":0,\"b\":0})\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf_earthquakes.dropna(subset=['year'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time‡</th>\n",
       "      <th>Place</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Mag</th>\n",
       "      <th>geometry</th>\n",
       "      <th>parsed_Date</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10 July 1688</td>\n",
       "      <td>11:45</td>\n",
       "      <td>Smyrna</td>\n",
       "      <td>38.4000</td>\n",
       "      <td>26.9000</td>\n",
       "      <td>16000</td>\n",
       "      <td>7.0</td>\n",
       "      <td>POINT (26.90000 38.40000)</td>\n",
       "      <td>1688-07-10</td>\n",
       "      <td>1688.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22 May 1766</td>\n",
       "      <td>05:10</td>\n",
       "      <td>Istanbul</td>\n",
       "      <td>40.8000</td>\n",
       "      <td>29.0000</td>\n",
       "      <td>4000</td>\n",
       "      <td>7.1</td>\n",
       "      <td>POINT (29.00000 40.80000)</td>\n",
       "      <td>1766-05-22</td>\n",
       "      <td>1766.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>23 July 1784</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Erzincan</td>\n",
       "      <td>39.5000</td>\n",
       "      <td>40.2000</td>\n",
       "      <td>7500</td>\n",
       "      <td>7.6</td>\n",
       "      <td>POINT (40.20000 39.50000)</td>\n",
       "      <td>1784-07-23</td>\n",
       "      <td>1784.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2 July 1840</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ağrı</td>\n",
       "      <td>39.6000</td>\n",
       "      <td>44.1000</td>\n",
       "      <td>10000</td>\n",
       "      <td>7.4</td>\n",
       "      <td>POINT (44.10000 39.60000)</td>\n",
       "      <td>1840-07-02</td>\n",
       "      <td>1840.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>28 February 1855</td>\n",
       "      <td>01:00</td>\n",
       "      <td>Bursa</td>\n",
       "      <td>40.2000</td>\n",
       "      <td>29.1000</td>\n",
       "      <td>1900</td>\n",
       "      <td>6.7</td>\n",
       "      <td>POINT (29.10000 40.20000)</td>\n",
       "      <td>1855-02-28</td>\n",
       "      <td>1855.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>14 June 2020</td>\n",
       "      <td>16:24 local time</td>\n",
       "      <td>Bingöl</td>\n",
       "      <td>39.4200</td>\n",
       "      <td>40.6700</td>\n",
       "      <td>1</td>\n",
       "      <td>5.9</td>\n",
       "      <td>POINT (40.67000 39.42000)</td>\n",
       "      <td>2020-06-14</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>30 October 2020</td>\n",
       "      <td>14:51 local time</td>\n",
       "      <td>\\tAegean Sea</td>\n",
       "      <td>37.9180</td>\n",
       "      <td>26.7900</td>\n",
       "      <td>117</td>\n",
       "      <td>7.0</td>\n",
       "      <td>POINT (26.79000 37.91800)</td>\n",
       "      <td>2020-10-30</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>23 November 2022</td>\n",
       "      <td>04:08 local time</td>\n",
       "      <td>Düzce</td>\n",
       "      <td>40.8470</td>\n",
       "      <td>30.9670</td>\n",
       "      <td>2</td>\n",
       "      <td>6.1</td>\n",
       "      <td>POINT (30.96700 40.84700)</td>\n",
       "      <td>2022-11-23</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>6 February 2023</td>\n",
       "      <td>04:17 local time</td>\n",
       "      <td>Gaziantep</td>\n",
       "      <td>37.1123</td>\n",
       "      <td>37.1195</td>\n",
       "      <td>29600</td>\n",
       "      <td>7.8</td>\n",
       "      <td>POINT (37.11950 37.11230)</td>\n",
       "      <td>2023-02-06</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>6 February 2023</td>\n",
       "      <td>13:24 local time</td>\n",
       "      <td>Kahramanmaraş</td>\n",
       "      <td>38.0357</td>\n",
       "      <td>37.2287</td>\n",
       "      <td>29600</td>\n",
       "      <td>7.7</td>\n",
       "      <td>POINT (37.22870 38.03570)</td>\n",
       "      <td>2023-02-06</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>74 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Date             Time‡          Place      Lat     Long  \\\n",
       "3       10 July 1688             11:45         Smyrna  38.4000  26.9000   \n",
       "4        22 May 1766             05:10       Istanbul  40.8000  29.0000   \n",
       "5       23 July 1784               NaN       Erzincan  39.5000  40.2000   \n",
       "6        2 July 1840               NaN           Ağrı  39.6000  44.1000   \n",
       "7   28 February 1855             01:00          Bursa  40.2000  29.1000   \n",
       "..               ...               ...            ...      ...      ...   \n",
       "73      14 June 2020  16:24 local time         Bingöl  39.4200  40.6700   \n",
       "74   30 October 2020  14:51 local time   \\tAegean Sea  37.9180  26.7900   \n",
       "75  23 November 2022  04:08 local time          Düzce  40.8470  30.9670   \n",
       "76   6 February 2023  04:17 local time      Gaziantep  37.1123  37.1195   \n",
       "77   6 February 2023  13:24 local time  Kahramanmaraş  38.0357  37.2287   \n",
       "\n",
       "    Deaths  Mag                   geometry parsed_Date    year  \n",
       "3    16000  7.0  POINT (26.90000 38.40000)  1688-07-10  1688.0  \n",
       "4     4000  7.1  POINT (29.00000 40.80000)  1766-05-22  1766.0  \n",
       "5     7500  7.6  POINT (40.20000 39.50000)  1784-07-23  1784.0  \n",
       "6    10000  7.4  POINT (44.10000 39.60000)  1840-07-02  1840.0  \n",
       "7     1900  6.7  POINT (29.10000 40.20000)  1855-02-28  1855.0  \n",
       "..     ...  ...                        ...         ...     ...  \n",
       "73       1  5.9  POINT (40.67000 39.42000)  2020-06-14  2020.0  \n",
       "74     117  7.0  POINT (26.79000 37.91800)  2020-10-30  2020.0  \n",
       "75       2  6.1  POINT (30.96700 40.84700)  2022-11-23  2022.0  \n",
       "76   29600  7.8  POINT (37.11950 37.11230)  2023-02-06  2023.0  \n",
       "77   29600  7.7  POINT (37.22870 38.03570)  2023-02-06  2023.0  \n",
       "\n",
       "[74 rows x 10 columns]"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_earthquakes['Mag'] = gdf_earthquakes['Mag'].str.split(' ', n=1, expand=True)[0]\n",
    "gdf_earthquakes['Mag'] = gdf_earthquakes['Mag'].astype(float)\n",
    "gdf_earthquakes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}