Exercise - 2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a970afad",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ab916224",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .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>title</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Rising Son</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Thousand Plane Raid</td>\n",
       "      <td>1969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Crucea de piatra</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Country</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gaiking II</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230616</th>\n",
       "      <td>Nobody Waved Good-bye</td>\n",
       "      <td>1964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230617</th>\n",
       "      <td>E yue</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230618</th>\n",
       "      <td>Lakota Girls</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230619</th>\n",
       "      <td>Kroniki domowe</td>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230620</th>\n",
       "      <td>Death in the Valley of Good and Evil</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>230621 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       title  year\n",
       "0                             The Rising Son  1990\n",
       "1                    The Thousand Plane Raid  1969\n",
       "2                           Crucea de piatra  1993\n",
       "3                                    Country  2000\n",
       "4                                 Gaiking II  2011\n",
       "...                                      ...   ...\n",
       "230616                 Nobody Waved Good-bye  1964\n",
       "230617                                 E yue  2005\n",
       "230618                          Lakota Girls  2015\n",
       "230619                        Kroniki domowe  1997\n",
       "230620  Death in the Valley of Good and Evil  2018\n",
       "\n",
       "[230621 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titles = pd.read_csv(\"C:/Users/Sathya/Desktop/Top_mentor_projects_Datasets-main/Top_mentor_projects_Datasets-main/titles.csv\")\n",
    "titles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "befd41a1",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Closet Monster</td>\n",
       "      <td>2015</td>\n",
       "      <td>Buffy #1</td>\n",
       "      <td>actor</td>\n",
       "      <td>Buffy 4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Suuri illusioni</td>\n",
       "      <td>1985</td>\n",
       "      <td>Homo $</td>\n",
       "      <td>actor</td>\n",
       "      <td>Guests</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Battle of the Sexes</td>\n",
       "      <td>2017</td>\n",
       "      <td>$hutter</td>\n",
       "      <td>actor</td>\n",
       "      <td>Bobby Riggs Fan</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Secret in Their Eyes</td>\n",
       "      <td>2015</td>\n",
       "      <td>$hutter</td>\n",
       "      <td>actor</td>\n",
       "      <td>2002 Dodger Fan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Steve Jobs</td>\n",
       "      <td>2015</td>\n",
       "      <td>$hutter</td>\n",
       "      <td>actor</td>\n",
       "      <td>1988 Opera House Patron</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611207</th>\n",
       "      <td>Foxtrot</td>\n",
       "      <td>1988</td>\n",
       "      <td>Lilja ??risd?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>D?ra</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611208</th>\n",
       "      <td>Niceland (Population. 1.000.002)</td>\n",
       "      <td>2004</td>\n",
       "      <td>Sigr??ur J?na ??risd?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>Woman in Bus</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611209</th>\n",
       "      <td>Skammdegi</td>\n",
       "      <td>1985</td>\n",
       "      <td>Dalla ??r?ard?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>Hj?krunarkona</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611210</th>\n",
       "      <td>U.S.S.S.S...</td>\n",
       "      <td>2003</td>\n",
       "      <td>Krist?n Andrea ??r?ard?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>Afgr.dama ? bens?nst??</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611211</th>\n",
       "      <td>Bye Bye Blue Bird</td>\n",
       "      <td>1999</td>\n",
       "      <td>Rosa ? R?gvu</td>\n",
       "      <td>actress</td>\n",
       "      <td>Pensionatv?rtinde</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3611212 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    title  year                         name  \\\n",
       "0                          Closet Monster  2015                     Buffy #1   \n",
       "1                         Suuri illusioni  1985                       Homo $   \n",
       "2                     Battle of the Sexes  2017                      $hutter   \n",
       "3                    Secret in Their Eyes  2015                      $hutter   \n",
       "4                              Steve Jobs  2015                      $hutter   \n",
       "...                                   ...   ...                          ...   \n",
       "3611207                           Foxtrot  1988            Lilja ??risd?ttir   \n",
       "3611208  Niceland (Population. 1.000.002)  2004    Sigr??ur J?na ??risd?ttir   \n",
       "3611209                         Skammdegi  1985           Dalla ??r?ard?ttir   \n",
       "3611210                      U.S.S.S.S...  2003  Krist?n Andrea ??r?ard?ttir   \n",
       "3611211                 Bye Bye Blue Bird  1999                 Rosa ? R?gvu   \n",
       "\n",
       "            type                character     n  \n",
       "0          actor                  Buffy 4   NaN  \n",
       "1          actor                   Guests  22.0  \n",
       "2          actor          Bobby Riggs Fan  10.0  \n",
       "3          actor          2002 Dodger Fan   NaN  \n",
       "4          actor  1988 Opera House Patron   NaN  \n",
       "...          ...                      ...   ...  \n",
       "3611207  actress                     D?ra  24.0  \n",
       "3611208  actress             Woman in Bus  26.0  \n",
       "3611209  actress            Hj?krunarkona   9.0  \n",
       "3611210  actress   Afgr.dama ? bens?nst??  17.0  \n",
       "3611211  actress        Pensionatv?rtinde   NaN  \n",
       "\n",
       "[3611212 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"C:/Users/Sathya/Downloads/cast.csv\")\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "14d938a6",
   "metadata": {},
   "outputs": [],
   "source": [
    " d =data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e7a3aa3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "d = d.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f9f4fdb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title        0\n",
       "year         0\n",
       "name         0\n",
       "type         0\n",
       "character    0\n",
       "n            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "42456990",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Closet Monster</td>\n",
       "      <td>2015</td>\n",
       "      <td>Buffy #1</td>\n",
       "      <td>actor</td>\n",
       "      <td>Buffy 4</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Suuri illusioni</td>\n",
       "      <td>1985</td>\n",
       "      <td>Homo $</td>\n",
       "      <td>actor</td>\n",
       "      <td>Guests</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Battle of the Sexes</td>\n",
       "      <td>2017</td>\n",
       "      <td>$hutter</td>\n",
       "      <td>actor</td>\n",
       "      <td>Bobby Riggs Fan</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Secret in Their Eyes</td>\n",
       "      <td>2015</td>\n",
       "      <td>$hutter</td>\n",
       "      <td>actor</td>\n",
       "      <td>2002 Dodger Fan</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Steve Jobs</td>\n",
       "      <td>2015</td>\n",
       "      <td>$hutter</td>\n",
       "      <td>actor</td>\n",
       "      <td>1988 Opera House Patron</td>\n",
       "      <td>0.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611207</th>\n",
       "      <td>Foxtrot</td>\n",
       "      <td>1988</td>\n",
       "      <td>Lilja ??risd?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>D?ra</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611208</th>\n",
       "      <td>Niceland (Population. 1.000.002)</td>\n",
       "      <td>2004</td>\n",
       "      <td>Sigr??ur J?na ??risd?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>Woman in Bus</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611209</th>\n",
       "      <td>Skammdegi</td>\n",
       "      <td>1985</td>\n",
       "      <td>Dalla ??r?ard?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>Hj?krunarkona</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611210</th>\n",
       "      <td>U.S.S.S.S...</td>\n",
       "      <td>2003</td>\n",
       "      <td>Krist?n Andrea ??r?ard?ttir</td>\n",
       "      <td>actress</td>\n",
       "      <td>Afgr.dama ? bens?nst??</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611211</th>\n",
       "      <td>Bye Bye Blue Bird</td>\n",
       "      <td>1999</td>\n",
       "      <td>Rosa ? R?gvu</td>\n",
       "      <td>actress</td>\n",
       "      <td>Pensionatv?rtinde</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3611212 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    title  year                         name  \\\n",
       "0                          Closet Monster  2015                     Buffy #1   \n",
       "1                         Suuri illusioni  1985                       Homo $   \n",
       "2                     Battle of the Sexes  2017                      $hutter   \n",
       "3                    Secret in Their Eyes  2015                      $hutter   \n",
       "4                              Steve Jobs  2015                      $hutter   \n",
       "...                                   ...   ...                          ...   \n",
       "3611207                           Foxtrot  1988            Lilja ??risd?ttir   \n",
       "3611208  Niceland (Population. 1.000.002)  2004    Sigr??ur J?na ??risd?ttir   \n",
       "3611209                         Skammdegi  1985           Dalla ??r?ard?ttir   \n",
       "3611210                      U.S.S.S.S...  2003  Krist?n Andrea ??r?ard?ttir   \n",
       "3611211                 Bye Bye Blue Bird  1999                 Rosa ? R?gvu   \n",
       "\n",
       "            type                character  rank  \n",
       "0          actor                  Buffy 4   0.0  \n",
       "1          actor                   Guests  22.0  \n",
       "2          actor          Bobby Riggs Fan  10.0  \n",
       "3          actor          2002 Dodger Fan   0.0  \n",
       "4          actor  1988 Opera House Patron   0.0  \n",
       "...          ...                      ...   ...  \n",
       "3611207  actress                     D?ra  24.0  \n",
       "3611208  actress             Woman in Bus  26.0  \n",
       "3611209  actress            Hj?krunarkona   9.0  \n",
       "3611210  actress   Afgr.dama ? bens?nst??  17.0  \n",
       "3611211  actress        Pensionatv?rtinde   0.0  \n",
       "\n",
       "[3611212 rows x 6 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d=d.rename(columns={'n':'rank'})\n",
    "d"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a427d8e8",
   "metadata": {},
   "source": [
    "What are the ten most common movie names of all time?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "92956303",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Around the World in Eighty Days       1298\n",
       "7 cajas                                689\n",
       "Thelma                                 580\n",
       "The Ten Commandments                   533\n",
       "The Eschatrilogy: Book of the Dead     517\n",
       "                                      ... \n",
       "Ang hari at ang Alas                     1\n",
       "Final Showdown                           1\n",
       "Pinoy Boxer                              1\n",
       "Snake Dragon Connection                  1\n",
       "Allahaismarladik                         1\n",
       "Name: title, Length: 172294, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = d.title.value_counts()\n",
    "x "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "140b6f72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Around the World in Eighty Days       1298\n",
       "7 cajas                                689\n",
       "Thelma                                 580\n",
       "The Ten Commandments                   533\n",
       "The Eschatrilogy: Book of the Dead     517\n",
       "                                      ... \n",
       "Cab Hustle                               1\n",
       "Nasreddin Hoca ve Timurlenk              1\n",
       "Mga mumunting lihim                      1\n",
       "HIV: Si Heidi, Si Ivy at Si V            1\n",
       "Allahaismarladik                         1\n",
       "Name: title, Length: 172294, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "15b3c773",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Around the World in Eighty Days       1298\n",
       "7 cajas                                689\n",
       "Thelma                                 580\n",
       "The Ten Commandments                   533\n",
       "The Eschatrilogy: Book of the Dead     517\n",
       "Catching Faith                         493\n",
       "The Dark Knight Rises                  452\n",
       "Welcome to Essex                       448\n",
       "Cockneys vs Zombies                    437\n",
       "The Buccaneer                          436\n",
       "Name: title, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce9ce667",
   "metadata": {},
   "source": [
    "Which three years of the 1930s saw the most films released?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6d212ea4",
   "metadata": {},
   "outputs": [],
   "source": [
    "d['de'] = d['year']/10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c82fa06d",
   "metadata": {},
   "outputs": [],
   "source": [
    "d['de']=d['de'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ec53e4a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "d['de']=d['de']*10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c3533b38",
   "metadata": {},
   "outputs": [],
   "source": [
    "d1=d.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bc6c1b64",
   "metadata": {},
   "outputs": [],
   "source": [
    "a=d[d.de==1930]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "fd4eaea2",
   "metadata": {},
   "outputs": [],
   "source": [
    "a=a.year.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "aae226dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1937    27437\n",
       "1936    25794\n",
       "1938    25205\n",
       "1939    24469\n",
       "1935    23868\n",
       "1934    20577\n",
       "1933    15399\n",
       "1932    14678\n",
       "1931    11745\n",
       "1930     9688\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5d463fa1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1937    27437\n",
       "1936    25794\n",
       "1938    25205\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0342b07",
   "metadata": {},
   "source": [
    "Plot the number of films that have been released each decade over the history of cinema."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "32be98e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='de'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "d.groupby('de').title.count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ce3813fd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "36de6fe9",
   "metadata": {},
   "source": [
    "Plot the number of \"Hamlet\" films made each decade."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8b5c3664",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1615</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>1996</td>\n",
       "      <td>Riz Abbasi</td>\n",
       "      <td>actor</td>\n",
       "      <td>Attendant to Claudius</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7438</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>1921</td>\n",
       "      <td>Fritz Achterberg</td>\n",
       "      <td>actor</td>\n",
       "      <td>Fortinbras,</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11242</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>2009</td>\n",
       "      <td>Hayden Adams</td>\n",
       "      <td>actor</td>\n",
       "      <td>Laertes</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11243</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>2009</td>\n",
       "      <td>Hayden Adams</td>\n",
       "      <td>actor</td>\n",
       "      <td>Player</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13907</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>1913</td>\n",
       "      <td>Eric Adeney</td>\n",
       "      <td>actor</td>\n",
       "      <td>Reynaldo</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1910</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>3505738</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>1969</td>\n",
       "      <td>Jennifer Tudor</td>\n",
       "      <td>actress</td>\n",
       "      <td>Court lady</td>\n",
       "      <td>23.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3528322</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>2000</td>\n",
       "      <td>Diane Venora</td>\n",
       "      <td>actress</td>\n",
       "      <td>Gertrude</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3557773</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>1996</td>\n",
       "      <td>Perdita Weeks</td>\n",
       "      <td>actress</td>\n",
       "      <td>Second Player</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3562331</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>2015</td>\n",
       "      <td>Katie (II) West</td>\n",
       "      <td>actress</td>\n",
       "      <td>Ophelia</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3578802</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>1996</td>\n",
       "      <td>Kate Winslet</td>\n",
       "      <td>actress</td>\n",
       "      <td>Ophelia</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>313 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          title  year              name     type              character  rank  \\\n",
       "1615     Hamlet  1996        Riz Abbasi    actor  Attendant to Claudius   1.0   \n",
       "7438     Hamlet  1921  Fritz Achterberg    actor            Fortinbras,   9.0   \n",
       "11242    Hamlet  2009      Hayden Adams    actor                Laertes   7.0   \n",
       "11243    Hamlet  2009      Hayden Adams    actor                 Player   7.0   \n",
       "13907    Hamlet  1913       Eric Adeney    actor               Reynaldo  14.0   \n",
       "...         ...   ...               ...      ...                    ...   ...   \n",
       "3505738  Hamlet  1969    Jennifer Tudor  actress             Court lady  23.0   \n",
       "3528322  Hamlet  2000      Diane Venora  actress               Gertrude   3.0   \n",
       "3557773  Hamlet  1996     Perdita Weeks  actress          Second Player  44.0   \n",
       "3562331  Hamlet  2015   Katie (II) West  actress                Ophelia   7.0   \n",
       "3578802  Hamlet  1996      Kate Winslet  actress                Ophelia  46.0   \n",
       "\n",
       "           de  \n",
       "1615     1990  \n",
       "7438     1920  \n",
       "11242    2000  \n",
       "11243    2000  \n",
       "13907    1910  \n",
       "...       ...  \n",
       "3505738  1960  \n",
       "3528322  2000  \n",
       "3557773  1990  \n",
       "3562331  2010  \n",
       "3578802  1990  \n",
       "\n",
       "[313 rows x 7 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = d[d['title']==\"Hamlet\"]\n",
    "q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ace68489",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='de'>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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Z+gy3RfEDAAAAADXokxUpqrAsXd831u4oOE5UeKC+urOfzm3XUE/M2aIHvtmk0nKGPsP9UPwAAAAAQA0pLXfok5UpGtw6QnENguyOg/8R5O+jN6/voQlDWujTlaka+94K5Rxh6DPcyykVP8aYMGPMl8aYbcaYrcaYeGNMPWPML8aYnVU/GU0PAAAAAMf5KXG/sgpKND4+zu4o+BNeXkb3DW+rl6/qqnWpuRo1Zal2HiiwOxZQbU51xc8rkuZaltVWUhdJWyXdL2meZVmtJM2r+h0AAAAAUGV6QpJi6gVqcOsIu6PgJEZ3a6rPbuurwtIKXTZ1meZvz7Q7ElAtTlr8GGNCJA2S9J4kWZZVallWrqRRkqZV3WyapNE1ExEAAAAAXE9iep5WJeVoXHysvLzYwt0VdI8J1+y7+iu6XqBu/nCV3l28h6HPcHmnsuKnuaQsSR8YY9YZY941xgRJamhZVoYkVf2MrMGcAAAAAOBSZiQkK8DXS1f2iLY7Ck5Dk7A6+vLOeJ3fvpGe+n6r7v+Koc9wbadS/PhI6i7pDcuyukk6otM4rcsYc5sxZrUxZnVWVtYZxgQAAAAA15FXWKZv16dpdNemCg30tTsOTlOgn4+mXtddfxnaUp+vTtX1767QocMldscCzsipFD/7JO2zLGtF1e9fqrIIOmCMaSxJVT//8ARIy7Letiyrp2VZPSMiOK8VAAAAgPv7Yk2qisscGhvPFu6uysvLaNL5bfTK1V21fl/l0Oft+xn6DNdz0uLHsqz9klKNMW2qLhomaYuk2ZLGV102XtKsGkkIAAAAAC7E4bA0PSFZveLC1aFJqN1xcJZGdW2qmbfHq6TcocumLtVv2w7YHQk4Lae6q9dfJH1sjNkoqaukpyU9K+k8Y8xOSedV/Q4AAAAAHm3hjiylZBdqLFu4u42u0WGafVd/NYsI0s3TVuvtRbsZ+gyX4XMqN7Isa72knn9w1bBqTQMAAAAALm56QpIigv01vEMju6OgGjUOraMvbu+nSV+s19M/bNPOA4f11KUd5e/jbXc04IROdcUPAAAAAOAkkg4e0YIdWbq2d4z8fPi45W7q+Hnr9Wu666/DWumLNft0/bsrdJChz3ByvBIBAAAAQDX5aHmyvI3RtX1i7I6CGuLlZXTPea312jXdtHFfnka9vlTb9ufbHQv4UxQ/AAAA/8PhYG4DgNNXVFqhmatTdUHHRmoYEmB3HNSwS7o00Rd3xKvc4dDlU5fp1y0MfYZzovgBAAA4ToXD0jXvLNf491eqpLzC7jgAXMis9WnKLy7XeIY6e4zOUWGaNXGAWkTW1a0zVuvNhQx9hvOh+AEAADjOpytTtGJvthbuyNKkmRtY/QPglFiWpWkJyWrbKFi94sLtjoNa1Cg0QJ/fFq8RnRrr2R+3adIXG/jiAE6F4gcAAKDKocMleuGn7erXor7uv7Ct5mzM0DM/brU7FgAXsDo5R1sz8jUuPk7GGLvjoJbV8fPWa9d009/Pba2v16bpmreXK6uAoc9wDhQ/AAAAVZ6fu11HSsr1+MgOun1Qc42Pj9U7i/fq/SV77Y4GwMlNT0hWcICPRndrYncU2MQYo7vPbaUp13bXlox8jZ6yVFvSGfoM+1H8AAAASFqbkqPPV6fq5gHN1KphsIwxeuSSDrqgQ0M9+f0W/bApw+6IAJxUZn6xftyUoTE9oxXo52N3HNhsROfG+uL2fqpwWLrizWX6KXG/3ZHg4Sh+AACAx6twWHr4281qFBKgvwxrdexyby+jV67uph4x4frb5+u1cm+2jSkBOKtPVqao3GFpbN9Yu6PASXSKCtXsu/qrVWRd3T5jjabM38XQZ9iG4gcAAHi8T1YkKzE9Xw9d3E51/f/72/oAX2+9M66nosLr6Nbpq7Urs8CmlACcUVmFQ5+sSNHg1hGKaxBkdxw4kciQAH1+e7xGdmmiF37arps+XKXU7EK7Y8EDUfwAAACPdrBqoHP/lvU1olPjP7xNeJCfpt3YW77eXhr//iodyC+u5ZQAnNVPifuVWVCi8f1Y7YP/L8DXW69c3VWPXNxeK/Zm6/z/LNLbi3arrMJhdzR4EIofAADg0Z77cZuKyir0+MiOJ9yJJ7peoD68sZdyC0t1wwerVFBcVospATir6cuSFVMvUINbR9odBU7KGKObBjTTL/cMVv+W9fX0D9t0yWtLtDYlx+5o8BAUPwAAwGOtSc7WF2v26eYBzdUysu5Jb9+xaaimXt9DOw8U6M6P1qq0nG9sAU+2JT1fK5OyNbZvrLy92MIdJ9Y0rI7eGddTb17fQ7mFZbr8jWV6+NvNyueLBNQwih8AAOCRKgc6J6pxaID+MrTlKd9vcOsIPXNZJy3ZdVD3f7WRYZ2AB5uxPEn+Pl66smeU3VHgIowxGt6xkX6dNFg39IvTxyuSNeylhZqzMZ2/T1BjKH4AAIBH+nhFsrZk5Ovhi9sryP/0tl++sme0Jp3XWl+vS9OLP2+voYQAnFleYZm+XZeu0V2bKizQz+44cDF1/X306CUdNGviADUM8dddn6zTjQx/Rg2h+AEAAB7n6EDnga0a6MKOjc7oMe4a2lLX9I7RlPm79dHy5GpOCMDZfbEmVUVlFRobz1BnnLlOUaH6dkJ/PXJxe63am63z/rNQbyxg+DOqF8UPAADwOM/+uE3FZRV6bGSHEw50PhFjjJ4c1UHD2kbqkVmb9XPi/mpOCcBZORyWZixPVs/YcHVsGmp3HLg4H28v3TSgmX6dNFiDW0foubnbdPGrS7QmmeHPqB4UPwAAwKOsTsrWl2v26ZaBzdUi4uQDnU/Ex9tLr13bTZ2iwvTXz9axQwvgIRbuzFLyoUJW+6BaNQ6to7fG9tTbY3uooLhy+PMD32xSXiHDn3F2KH4AAIDHKK9w6OFZiWpymgOdTyTQz0fvje+phiEBuvnDVdqTdbhaHheA85qRkKwGdf11YcfGdkeBGzq/QyP9cs9g3TKgmT5bmaJhkxdq1vo0hj/jjFH8AAAAj/HR8mRtrRroHOh3egOdT6RBXX9Nu7G3vIzR+A9WKqugpNoeG4BzST50RPO3Z+raPjHy8+HjFGpGkL+PHrq4vWbfNUBNwgJ092frNe79lUo+dMTuaHBBvFIBAACPkFVQopd+3qGBrRpo+BkOdD6RuAZBeu+GXsoqKNHN01bpSEl5tT8HAPt9tDxZ3sbouj4xdkeBB+jYNFTfTOivx0d20LqUXJ3/n0WaMn+XSssZ/oxTR/EDAAA8wjM/blVxeYUeP4uBzifTNTpMU67trs1pebrrk7UqZ1cWwK0UlVbo81WpuqBDIzUMCbA7DjyEt5fR+H5x+vWewRraNlIv/LRdI15drFVJ2XZHg4ug+AEAAG5v5d5sfb02TbcNaq7mZznQ+WSGtWuop0Z30vztWXrwm83MZADcyOwNacovLtc4hjrDBo1CA/TG9T303vieKiyt0JVvJuj+rzYqt7DU7mhwctV3cjsAAIATKq9w6JFZm9U0rI4mnlM9A51P5to+McrIK9Jrv+1S47AA/e3c1rXyvABqjmVZmrYsWW0bBat3s3p2x4EHG9auoeJb1NfLv+7Ue0v26pctB/Twxe01qmuTGlvRCtfGih8AAODWpicka9v+gmof6Hwy95zXWlf0iNLLv+7UzFWptfa8AGrGmuQcbcnI17j4OD5cw3aBfj564KJ2+u6uAYquF6i/fb5eY99bqb0HGf6M/4/iBwAAuK3MgmL955cdGtw6Qhd0aFirz22M0TOXddKg1hH61zebNH97Zq0+P4DqNS0hWcEBPhrdrYndUYBj2jcJ0Vd39tOTozpoQ2quLnh5kV6bt1Ml5RV2R4MTofgBAABu69kftqmk3KHHanCg84n4entp6nXd1bZRsCZ+vFYb9+XWegYAZy8zv1g/bsrQlT2ia3XlIHAqvL2MxsbH6ddJg3Ve+4Z66ZcduuiVxVqx55Dd0eAkKH4AAIBbWrHnkL5el6bbBzdXswZBtuWo6++jD27opfBAP9304SqlHCq0LQuAM/PpylSVOyyNZagznFjDkABNuba7Prixl0rKHbrq7eW678sNyjnC8GdPR/EDAADcTlmFQ4/MSlTTsDqaMKR2BjqfSGRIgKbd1FvlDkvjP1ipbN6EAy6jrMKhj1cka1DrCFtLZOBUndMmUr/8fbDuGNxCX69N07DJC/XVmn3sMunBKH4AAIDbmZ6QrO0HCvTIJe1Vx8/b7jiSpJaRdfXuuJ5Kzy3SzdNWqaiU+QuAK/g58YAyC0o0ntU+cCF1/Lx1/4VtNeevAxRXP1CTvtiga99ZoT1Zh+2OBhtQ/AAAALeSmV850HlImwid3752BzqfTM+4enrl6m5an5qrv362ThUOvn0FnN20hCRF16ujIW0i7Y4CnLa2jUL05R399O9LO2pzep6Gv7xYL/+6g+HPHobiBwAAuJWnf9iq0nKHHrvEnoHOJzO8YyM9dkkH/bLlgB6bncjSe8CJbc3I18q92RrbN1beXs73egKcCi8vo+v6xGrepMEa3rGRXv51py58ZbESdjP82VNQ/AAAALexfM8hfbs+XXcMbq44J57FMb5fnG4f1FwzlifrjYW77Y4D4E9MT0iWv4+XxvSMtjsKcNYigwP06jXdNO2m3iqrcOiad5Zr0swNzJ3zABQ/AADALVQOdN6sqPA6utMJBjqfzD+Ht9XILk30/Nzt+nrtPrvjAPgfeUVl+nZdmkZ1baKwQD+74wDVZnDrCP38t8GaMKSFZq1P07CXFmjm6lRWoLoxih8AAOAWpi1L0o4Dh/XoJR2cZqDziXh5Gb1wZWfFN6+v+77cqCU7D9odCcBxvlyzT0VlFRoXH2d3FKDa1fHz1n3D2+qHuweqRURd3fflRl399nLtymT4szui+AEAAC7vQNVA56FtI3VuO9cZwOrv4623xvVQy8i6uuOjNdqSnm93JACSHA5LMxKS1CM2XB2bhtodB6gxrRsGa+bt8Xrmsk7ampGvC19ZpMk/b1dxGcOf3QnFDwAAcHn//n6ryhyWHr2kvVMOdD6RkABffXBjLwUH+OjGD1cqLbfI7kiAx1u0M0tJhwo1ji3c4QG8vIyu6R2jeZOGaESnxnr1t1268JXFWrqLlajuguIHAAC4tGW7D2r2hnTdObiFYus770DnE2kcWkcf3thbhaUVGv/+SuUVltkdCfBoMxKS1aCuvy7s2NjuKECtiQj218tXd9OMm3vLsixd9+4K/f3z9Tp4uMTuaDhLFD8AAMBllVU49OisREXXq6M7h7SwO85ZadMoWG+P7amUQ4W6dfpqltkDNkk5VKjftmfq2t7R8vPh4xI8z8BWEZr7t0H6y9CWmrMxXcNeWqjPV6XI4WD4s6vilQwAALisD5cmaWfmYT12SQcF+Dr/QOeTiW9RXy+O6aKVSdmaNHMDb7IBG3y0IllexujaPpzmBc8V4OutSee30Y93D1SbhsH651ebdNXbCdp5oMDuaDgDFD8AAMAl7c8r1su/7tCwtpEa1q6h3XGqzcguTfTgRe30/aYMPfX9VrvjAB6lqLRCn69K1QUdGqpRaIDdcQDbtYwM1me39dXzl3fWzszDuujVxXrxJ4Y/uxqKHwAA4JL+/cPRgc4d7I5S7W4Z2Ew39o/T+0v36t3Fe+yOA3iM7zakK6+ojC3cgeN4eRmN6RWtefcM1iVdmuj1+bt0wcuLtGhHlt3RcIoofgAAgMtZtuugvtuQrglDWiimfqDdcaqdMUYPj2ivizo10lPfb9Wcjel2RwLcnmVZ+nBZkto0DFafZvXsjgM4nfp1/TV5TFd9cksfeRmjce+v1N2frVNWAcOfnR3FDwAAcCml5Q49MjtRMfUCdcdg1x7ofCJeXkaTx3RVr7hw3fP5Bi3fc8juSIBbW5uSoy0Z+RrXL1bGGLvjAE6rX8sG+vHugbp7WCv9uGm/hr20QJ+sYPizM6P4AQAALuWDpXu1K/OwHhvZ3i0GOp9IgK+33hnXUzH1A3Xb9NXawVBNoMZMW5asYH8fje7a1O4ogNML8PXW389rrR/uHqh2jUP0wDebdOVbCdq+n7+nnBHFDwAAcBkZeUV6Zd5OnduuoYa2dZ+BzicSFuinD2/spQBfb41/f6X25xXbHQlwO5kFxfpxc4au6BmlIH8fu+MALqNlZF19dltfvXhlF+3JOqwRry7Wc3O3qaiU4c/OhOIHAAC4jKe+36oKh6VHL2lvd5RaFRUeqA9u7KWC4nLd8MFK5ReX2R0JcCufrUxVWYWlsX3Zwh04XcYYXdEjSvMmDdHobk31xoLdOv/lhVqwPdPuaKhC8QMAAFzCkp0H9f3GDE08p6Wi67nfQOeT6dAkVG9c3127Mg/rzo/WqLTcYXckwC2UVTj08YpkDWodoeYRde2OA7isekF+evHKLvr01r7y9fbSDR+s0l2frFVmPitV7UbxAwAAnF7lQOfNiq0fqNsGNbc7jm0GtorQ81d01tJdh3TflxsYpAlUg1+2HNCB/BKNY7UPUC3iW9TXj3cP1N/Pba2ftxzQsMkLNWN5Mn9n2YjiBwAAOL33luzVnqwjemxkB7cf6Hwyl3WP0j8uaKNv16fr+Z+22x0HcHnTliUpKryOzmkbaXcUwG34+3jr7nNbae7dA9Wpaage/nazLn9zmbZm5NsdzSNR/AAAAKeWnluk137bqfPbN9Q5bfhgJkkThrTQdX1i9ObC3ZqekGR3HMBlbdufrxV7szW2b6y8vdjCHahuzSPq6uNb+mjymC5KPlSoi19bomd+2KrC0nK7o3mUUy5+jDHexph1xpg5Vb/XM8b8YozZWfUzvOZiAgAAT/Xv77fKYVl6+GLPGuh8IsYYPTGqo85t11CPzk7U3M377Y4EuKTpCcny9/HSmJ7RdkcB3JYxRpd1j9K8ewbriu5RemvRHp03eZHmb2P4c205nRU/d0vaetzv90uaZ1lWK0nzqn4HAACoNot3Zun7TRmaOMQzBzqfiLeX0WvXdFPX6DDd/dk6rUnOtjsS4FLyisr0zdo0jezSROFBfnbHAdxeeJCfnruis2beHq86ft668cNVmvDxGh1g+HONO6XixxgTJWmEpHePu3iUpGlVf54maXS1JgMAAB6tpLxCj85KVFz9QN3qwQOdT6SOn7feG99LTcLq6OZpq7U767DdkQCX8dWafSoqq9D4fnF2RwE8Su9m9fTDXwfq3vNb69etmRr20kJNT0hSBcOfa8yprvh5WdJ9ko7fN7ShZVkZklT1k5PuAQBAtXlvyV7tOchA55OpF+SnaTf2lo+X0fj3VyqzgG9OgZNxOCzNWJ6s7jFh6tg01O44gMfx8/HSXUNb6ee/DVK3mDA9MitRl01dqsT0PLujuaWTFj/GmIslZVqWteZMnsAYc5sxZrUxZnVWVtaZPAQAAPAwablFem3eLl3QoaGGMND5pGLqB+q98b106HCpbvpwlQ6XMDQTOJHFuw5q78EjGhcfZ3cUwKPFNQjS9Jt665Wruyott0gjX1+qf3+/RUf4e6xancqKn/6SRhpjkiR9JmmoMeYjSQeMMY0lqernH05msizrbcuyelqW1TMiIqKaYgMAAHf21JwtssRA59PRJTpMU6/rrq0ZBZrw8VqVVThOfifAQ81ISFKDun66sFMju6MAHs8Yo1Fdm2rePUM0pme03lm8V+dNXqhftxywO5rbOGnxY1nWvyzLirIsK07S1ZJ+syzrekmzJY2vutl4SbNqLCUAAPAYC3dk6cfN+/WXoa0UFc5A59NxTttIPX1pRy3akaUHvt4ky2JeAvC/UrMLNW9bpq7pHSN/H04jBZxFaKCvnrmsk768I151A3x0y/TVumPGGmXkFdkdzeWdzq5e/+tZSecZY3ZKOq/qdwAAgDNWUl6hx2YnqlmDIN0ysJndcVzSVb1idPewVvpizT7959eddscBnM5Hy5PlZYyu7RNjdxQAf6BnXD3N+ctA/eOCNpq/PVPnvrRQHyzdy/Dns+BzOje2LGuBpAVVfz4kaVj1RwIAAJ7q3cV7tffgEU27qTffxJ+Fv53bShl5RXp13k41Dg3QNb35gAtIUnFZhT5fnarz2zdU49A6dscB8Cf8fLw08ZyWuqRzEz00a7Me/26LvlmXpqcv7cRA9jNwNit+AAAAqs2+nEK99ttOXdixkQa3Zi7g2TDG6N+XdtLg1hF66NvN+m0bcxIASZq9IV25hWUMdQZcREz9QE27sZdevaab0nOLNfL1JXriuy1sYnCaKH4AAIBTeGrOVhkZPcRA52rh6+2lqdd1V/vGIZr48TptSM21OxJgK8uyNG1Zklo3rKu+zevZHQfAKTLGaGSXJpo3abCu6R2j95dWDn/+KXG/3dFcBsUPAACw3YLtmZqbuF9/GdZSTcM4/aK6BPn76P0beqlBsJ9u+nCVkg4esTsSYJu1KblKTM/XuPg4GWPsjgPgNIXW8dW/L+2kr+7sp9A6vrp9xhrdOn210nMZ/nwyFD8AAMBWRwc6N48I0i0Dmtsdx+1EBPtr2o295bAs3fDBSh06XGJ3JMAW0xOSFOzvo0u7NbU7CoCz0CM2XN/9ZYDuv7CtFu/M0rmTF+rdxXtUXuGwO5rTovgBAAC2emfRHiUdKtTjIzvIz4e3JjWheURdvTu+lzLyinXztNUqKq2wOxJQq7IKSvTDpgxd3iNKQf6ntb8NACfk6+2lOwa30C9/H6w+zerpqe+3atSUpdq4L9fuaE6Jd1cAAMA2qdmFen3+Ll3UqZEGtmKgc03qERuu167ppo37cvWXT9fyzSg8ymcrU1RWYWlsfKzdUQBUo+h6gXr/hl6ael13ZRWUaPSUpXpsdqIKisvsjuZUKH4AAIBtnpyzpXKg8wgGOteG8zs00uMjO+jXrZl6ZHaiLMuyOxJQ48orHPp4RYoGtmqgFhF17Y4DoJoZY3RRp8b6ddJgXd83VtMSknTu5IWauzmDv+eqUPwAAABbzN+WqZ+3HNBfh7VSEwY615qx8XG6c0gLfbIiRVPm77I7DlDjftlyQPvzi9nCHXBzIQG+emJUR319Zz/VC/LXHR+t1S3TVmtfTqHd0WxH8QMAAGpdcVmFHvuucqDzzQOa2R3H49x3QRtd2q2pXvx5h75cs8/uOECNmpaQpKZhdTS0baTdUQDUgm4x4frurv568KJ2Wrb7kM6bvEjvLPLs4c8UPwAAoNa9vWiPkg8V6omRHRnobANjjJ67vLMGtGyg+7/aqEU7suyOBNSI7fsLtHxPtsbGx8rbiy3cAU/h4+2lWwc11y/3DFK/FvX17x+26pLXl2pdSo7d0WzBOy0AAFCrUrMLNWX+Lo3o3FgDWjWwO47H8vPx0hvXd1fLyLq686M12pyWZ3ckoNpNT0iSv4+XruoZbXcUADaICg/Uu+N76s3ruyv7SIkue2OZHpm1WfkeNvyZ4gcAANSqx7/bIm8vo4dGtLM7iscLDvDVtJt6K7SOr278cJVSs5mDAPeRX1ymb9al6ZIuTRQe5Gd3HAA2McZoeMfG+vWewRofH6cZy5N17ksL9f1Gzxn+TPEDAABqzW/bDujXrQd097BWahzKQGdn0DAkQNNu6q2Ssgrd8MFK5RaW2h0JqBZfrdmnwtIKjWeoMwBVftnx2MgO+nZCf0UE+2viJ2t144erlFfo/qt/KH4AAECtKC6r0GOzt6hlZF3d2J+Bzs6kVcNgvTOup1Kzi3TLtNUqLquwOxJwVhwOSzMSktUtJkydokLtjgPAiXSJDtOsif310Ih2Ki13qG6Aj92RahzFDwAAqBVvLdyjlOxCPTGyAwOdnVCf5vX1n6u6ak1Kjv722XpVODxj+Tvc05JdB7Xn4BFW+wD4Qz7eXrplYHN9fEsfjxj8zrsuAABQ41IOFWrqgl26pEsT9WvJQGdnNaJzYz00or3mJu7Xk3O2eMzsA7if6QnJqh/kpws7NbI7CgAnZoz7lz6S5P5rmgAAgO2emJMoHy+jBy9ioLOzu3lAM2XkFundJXvVJCxAtw1qYXck4LSkZhdq3rYDmjikpfx9vO2OAwC2o/gBAAA16tctB/Tr1kw9cFFbNQoNsDsOTsEDF7VTRn6xnv5hmxqGBGhU16Z2RwJO2UcrkuVljK7tE2N3FABwChQ/AACgxhSXVejxOYlqxUBnl+LlZfTSlV2UVVCie7/YoIhgf/VrwSl6cH7FZRX6fFWqzmvXUE3C2DkQACRm/AAAgBr0xoLdSs0u0uOjOsjXm7cdriTA11vvjO2pZg2CdPv0Ndq2P9/uSMBJfbchXbmFZRrXL9buKADgNHgHBgAAakTyoSN6Y+FujezShNUiLio00Fcf3thbgf7euuH9VcrIK7I7EvCnLMvStIQktYqsq/jm9e2OAwBOg+IHAABUO8uy9NjsRPl6GT04goHOrqxJWB19eGNvHS4p1w3vr1JeUZndkYA/tC41V5vT8jWuX5zH7NQDAKeC4gcAAFS7X7dmav72LP39vNZqGMJAZ1fXrnGI3hrbQ3sOHtbtM1arpLzC7kjA/zN9WZLq+vvo0m4MIweA41H8AACAalVUWqHHZieqdcO6Gt8vzu44qCb9WzbQC1d00fI92br3i41yOCy7IwHHZBWU6IdN+3VFjyjV9Wf/GgA4Hq+KAACgWr2xYJfScov02W19GejsZkZ3a6qMvGI9N3ebGocG6IGLOI0PzuHzVSkqrXDo+r4MdQaA/0XxAwAAqk3SwSN6c9Eeje7aRH0ZruqW7hjcXBl5RXp70R41Dg3Qjf2b2R0JHq68wqGPV6RoYKsGahlZ1+44AOB0+BoOAABUC8uy9Nh3ifLz9mIliBszxujRSzrogg4N9cScLfpxU4bdkeDhft16QBl5xRrLah8A+EMUPwAAoFr8suWAFlQNdI5koLNb8/YyeuXqbuoWHaa7P1+vVUnZdkeCB5u2LFlNw+poWLuGdkcBAKdE8QMAAM5aUWmFHv9ui9o0DNb4eL519wQBvt56b3wvRYXV0S3TVmtXZoHdkeCBdhwoUMKeQ7q+b6y8vdjCHQD+CMUPAAA4a1OrBjo/MaqDfBjo7DHCg/w07abe8vX20vj3Vykzv9juSPAw0xOS5Ofjpat6RdsdBQCcFu/MTlNZhUO3TFulnxL3y7LYxhQAgL0Hj+ithXt0abem6sNAZ48TXS9QH9zQSzmFpbrhg1UqKC6zOxI8RH5xmb5em6ZLOjdRvSA/u+MAgNOi+DlN+/OKlXyoULfPWKNr3lmuzWl5dkcCAMA2lmXp0dmJ8vfx0r8uamt3HNikU1Sopl7XXdsPFGjCx2tVVuGwOxI8wNdr9qmwtELj+3F6KQCcCMXPaYquF6gf7x6oJ0d10I4Dh3XJ60t07xcbdIClzQAAD/RT4gEt2lE10DmYgc6ebEibSD17WSct3nlQ//xqIyujUaMcDkvTE5LVNTpMnaPC7I4DAE6N4ucM+Hh7aWx8nObfO0S3DWyu2evTdc6LC/TqvJ0qKq2wOx4AALWisLRcT87ZoraNgjWOgc6QdGXPaN1zXmt9vTZNL/28w+44cGNLdx/UnoNHWO0DAKeA4ucshNbx1b8uaqdf7hmkIW0iNPmXHTrnxQX6eu0+ORx8ywUAcG9T5h8d6NyRgc445i9DW+qa3tF6ff4ufbwi2e44cFPTE5JVP8hPF3VqbHcUAHB6vEurBrH1gzT1uh6aeXu8IkP8dc/MDRo9dalWJWXbHQ0AgBqxJ+uw3l60R5d1b6rezerZHQdOxBijJ0d11NC2kXr42836ZcsBuyPBzaRmF2re1gO6une0/H287Y4DAE6P4qca9W5WT99O6K/JY7ooM79EV76ZoAkfr1HKoUK7owEAUG2ODnQO8PHWvy5sZ3ccOCEfby+9fm03dWoaqr98ulbrUnLsjgQ38vGKFEnSdX04zQsATgXFTzXz8jK6rHuU5t87RPec11rzt2Xp3MkL9cwPW5XP9qYAADfwU+J+Ld55UJPOb62IYH+748BJBfr56L0beqlhSIBunrZaew8esTsS3EBxWYU+X5Wi89s3UpOwOnbHAQCXQPFTQ+r4eeuvw1ppwT+GaGTXJnp78R4NeWGBZixPVjlbnAIAXFRhabme+G6L2jUO0fV9+bYdJ9agrr+m3dhbknTDByt18HCJzYng6uZszFBOYRkD5QHgNFD81LCGIQF68cou+u6uAWoVWVcPf7tZF76yWAu2Z9odDQCA0/b6b7uUnlesJ0d1YKAzTklcgyC9N76nDuQX6+YPV6mwtNzuSHBRlmVp2rIktYysq/gW9e2OAwAug3dstaRj01B9dltfvTW2h8oqHLrhg1Ua9/5Kbd9fYHc0AABOye6sw3pn8R5d3j1KPeMY6IxT1y0mXK9f012b0vI08eO1rH7GGVmfmqtNaXkaHx8rY4zdcQDAZVD81CJjjC7o0Eg//32wHhrRTutTcnThK4v04DebWPoMAHBqlmXpsdmJCvD11v0XtrU7DlzQue0b6snRHTV/e5Ye+nazLMuyOxJczPSEZNX199Gl3aPsjgIALsXH7gCeyM/HS7cMbK7Lu0fplXk7NWN5smavT9fEoS11Q784BfiyLSWA6pVbWKp1Kblal5KjyJAAXdM7Rt5efFuKU/fj5sqBzo+P7MBAZ5yx6/rEKiO3WK/P36UmYXX012Gt7I4EF3HwcIm+35iha3pHq64/H2EA4HTwqmmj8CA/PTayg67vG6tnftiqZ3/cpo9XJOv+4e10UadGLGEFcEYqHJZ2ZhZobXKu1qbkaG1KjvZkVe6mY4xkWdK369L00pguiq0fZHNauIIjJeV6cs4WtW8couv6xNgdBy5u0vmtlZFXrMm/7FCj0ACN6RltdyS4gM9Xpaq0wqGx8XF2RwEAl0Px4wRaRtbVezf00pKdB/XU91s08ZO16hkbrocubq+u0WF2xwPg5PIKy7Q2NUfrknO0NiVX61NzdbikcnhqvSA/dY8J0+Xdo9Q9JlxdokM1d/N+PTo7UcNfXqwHRrTT9X1iKJpxQq/9tksZecV6/dpuDHTGWTPG6NnLOymzoFj/+nqTIoP9NaRNpN2x4MTKKxz6aHmyBrRsoJaRde2OAwAux9Tm+dU9e/a0Vq9eXWvP54oqHJa+WJ2qF3/eoYOHSzS6axPdN7ytmoTVsTsaACfgcFjamXm4ciVPcuVqnt1Vq3m8jNS2UYi6x4ape0y4useEK7Z+4B+WOhl5Rbrvy41avPOgBrZqoOev6KzGobzO4P/blVmg4S8v1qXdmuqFK7vYHQdu5HBJuca8maCkQ0f0+W3x6hQVanckOKm5m/frjo/W6K2xPXRBh0Z2xwEAp2SMWWNZVs8/vI7ixzkdLinXGwt26Z3Fe2Uk3Taoue4Y3EJBnNMMeJS8wjKtS61cybMuJUfrU3JVULWaJzzQt7LgiQ1Xt5gwdYkKO63XCMuy9NGKFD39/Vb5eBs9MaqDRndtyuofHGNZlq5/b4U27cvTb/cOUYO6zPZB9crML9alU5eppNyhbyb0U3S9QLsjwQld+85yJR8q1MJ/DGHVIQD8CYofF7Yvp1DPz92u2RvSFRHsr3+c30aX94hiKCvghhwOS7uyDh9bybM2JVe7Mg9LqlzN06ZRiLrHhB0re+L+ZDXP6Uo6eESTvtigNck5Gt6hkf59aUfV5wM+JM3ZmK67PlmnJ0d1YK4GasyuzAJd/kaC6gf56as7+yk8yM/uSHAiOw8U6Lz/LNJ9w9towpCWdscBAKdF8eMG1qbk6Kk5W7Q2JVftG4fooYvbqV+LBnbHAnAW8orKtD4191jRsz41VwXFlat5wo6u5qkqejpHh9XoLiYVDkvvLN6jyT/vUEgdHz19aSedz3J6j3akpFzDXlqo+nX9NPuuAXzhgBq1Oilb1767Qh2bhOiTW/uywymOefjbzfp8daoS7h/KlxIAcAIUP27CsizN2ZihZ3/cprTcIp3brqEeuKitmkcw5A5wdg6Hpd1ZR2fzVO62tSvrsCyrcqetNg2D1e1o0RMbruYNgmw55Wrb/nzd8/kGbcnI12Xdm+rRSzootI5vreeA/Z75caveWrhHX0/op+4x4XbHgQf4cVOGJnyyVue1a6g3ru9B2QgVFJep79PzdEHHRpo8pqvdcQDAqVH8uJnisgq9v3Svps7freKyCo2Nj9Xdw1opLJCl0YCzyC8u0/qU3GOnbK1PyVF+1Wqe0Dq+6hbz+wDmLtGhCg5wnnKltNyh13/bqSkLdisy2F8vXNFFA1qxwtCTHB3ofHn3KD13RWe748CDfLB0rx7/bovGxcfq8ZEdmDnm4aYtS9KjsxM1a2J/dWGnWwA4obMqfowx0ZKmS2okySHpbcuyXjHG1JP0uaQ4SUmSxliWlXOix6L4qV5ZBSWa/MsOfb4qRcEBvrp7WCuNjY+VL0PvgFrlcFjac/CI1qbkaF1KjtYk52hn5u+reVpHBqt7bFjVip7K1TxeLvBN9vrUXN0zc732ZB3RuPhY3X9hWwX6MWDe3VmWpeveXaHNaXmaf+8QTq1ArXv6h616e9Ee/XN4W905pIXdcWATy7I0bPJCBQf4atbE/nbHAQCnd7bFT2NJjS3LWmuMCZa0RtJoSTdIyrYs61ljzP2Swi3L+ueJHovip2Zs25+vp+Zs1ZJdB9W8QZD+dVE7ndsukm/JgBpSUFymDal5Vat5crQuJVd5RWWSpJAAn2MFT/fYMHWJDlOIE63mOV3FZRV6fu52vb90r+LqB+qlMV3VI5bTftzZdxvS9ZdP1+nJ0R01tm+s3XHggRwOS3d/vl7fbUjXy1d11ehuTe2OBBss2XlQ17+3QpPHdNFl3aPsjgMATq9aT/UyxsyS9HrVP0Msy8qoKocWWJbV5kT3pfipOZZlaf72TP37+63anXVE/VrU14Mj2qlDk1C7owEuzbKqVvMk/76l+vYDBcdW87SKrHvslK3usWFq3qCuS6zmOV0Juw/p3i82KCOvSLcPbqG/ndtK/j4MX3U3h0vKNeylBYoI9tesiQx0hn1Kyit0w/urtDo5Wx/e2Fv9W3K6qae5bfpqrU7O0bL7hzLsGwBOQbUVP8aYOEmLJHWUlGJZVthx1+VYlnXCr4EpfmpeWYVDn6xI0X9+3aG8ojKN6RGtSee3VmRIgN3RAJdwuKRcG47baWtdaq5yCytX8wQfW81TOZ+na4xrr+Y5XQXFZXpqzlZ9vjpVbRsFa/KYrmrfJMTuWKhGR0+x+WZCP3VjoDNslldUpjFvJig9t0gz74hXu8a83niKfTmFGvT8fN0xuIXuG97W7jgA4BKqpfgxxtSVtFDSvy3L+toYk3sqxY8x5jZJt0lSTExMj+Tk5DP4n4DTlVdYptd+26lpCUny9fbSnYNb6NZBzfnGBDiOZVnae/CI1h4dwpycox0HCuSoelk8tpontrLoaRHhnqt5Ttdv2w7on19tUm5hqf52bmvdPqi5fJgt5vJ2HCjQRa8s1hU9ovTs5Qx0hnPIyCvSpVOWyZKlryf0V9OwOnZHQi14bu42vbVwtxb/cyj/nwPAKTrr4scY4ytpjqSfLMuaXHXZdnGql9NLOnhEz/64TXMT96tJaIDuG95WI7s04cMrPNKRo6t5Un4/bSvn6Goefx91PbrTVmy4ukaHsY35CeQcKdVDszbr+40Z6hodppfGdFGLiLp2x8IZsixL17yzXFszCjT/3iGqF8QukXAe2/bn68o3EtQoNEBf3tFPoYG8Nruz4rIKxT8zT72b1dNbY//w8wsA4A+c7XBnI2maKgc5/+24y1+QdOi44c71LMu670SPRfFjn+V7Dump77doc1q+ukSH6eER7dQzrp7dsYAaY1mWkg4VHjtla21Krrbvzz+2mqdFRJC6x4SrR2xl0dOS1Txn5LsN6Xp41mYVl1Xon8Pbanx8HP8eXdCs9Wm6+7P1+velHXVdHwY6w/ks231QN7y/Sl2iQzV5TFdF1wu0OxJqyFdr9mnSFxv08S19mO0EAKfhbIufAZIWS9qkyu3cJekBSSskzZQUIylF0pWWZWWf6LEofuzlcFj6el2aXvhpmw7kl2hE58a6f3hb3jzBLRwpKdeGfblal1I5n2ddaq6yj5RKkur6+6hrdJi6x4SpW2y4ukWHKSyQFQ3VJTO/WP/8aqPmb89SfPP6euHKzooK53XFVRQUl2nYSwvVKDRA30zoz0BnOK3vNqTrnpnr5bCkUV2b6M7BLdSqYbDdsVDNRr2+RIdLyvXrPYPZoRYATkO17up1Nih+nENhabneWrhHby3aLYdDumlAM008p4WCPWhILVybZVlKPlR4bDv1tcm52n6gQBVVy3maV63mOTqfp1VkMB9ma5hlWfp8VaqenLNFxhg9ckl7XdkjijftLuCpOVv03tK9+nZCf3WJDrM7DnBCGXlFenfxXn2yIkVFZRW6oENDTRjSkv923cT61FyNnrJUT4zqoHHxcXbHAQCXQvGDP7Q/r1jP/7RNX69NU/0gP91zfmtd1TOaIa1wOoWl5dq4L+9YybMuJUeHqlbzBPl5/z6bJyZc3WJYzWOn1OxC3fvFBq3Ym61z20Xq6cs6KTKYXQWd1fb9Bbro1cUa0zNaz1zWye44wCnLPlKqD5fu1YfLkpRfXK4BLRtowjktFN+8PoWzC7vn8/X6ecsBLX9gmOr6+9gdBwBcCsUPTmjjvlw9NWerViZlq3XDunpwRHsNbh1hdyx4KMuylJpd9PtqnpQcbc04bjVPg6DKLdWrdtpq3ZDVPM7G4bD0/tK9ev6n7Qry89ZToztpROfGdsfC/7AsS1e/vVzbDxRo/qQhCmegM1xQQXGZPlmRoncW79XBwyXqFhOmCUNaaljbSOaNuZhDh0sU/8xvurp3tJ4Y1dHuOADgcih+cFKWZemnxP16+odtSsku1JA2EXrwonacO48aV1RaoY37co9tqb4uJUcHD/++mqdLdNixU7a6RYfz4dSF7Mos0KSZG7RhX55GdmmiJ0Z1YDWWEzk60PmZyzrpmt4xdscBzkpxWYW+XLNPby7crX05RWrTMFgTzmmhEZ0as5LZRUyZv0sv/LRdv94zSC0jef8JAKeL4genrKS8QtOXJevV33aqsLRC1/aO0d/ObaX6df3tjgY3YFmW9uVUreZJrtxpa2tGvsqrVvM0axCkbsedttWmEat5XF15hUNTF+zWq/N2qn5dPz17eWed0ybS7lger6C4TENfWqgmVQOdWRkBd1Fe4dB3G9P1xoLd2nHgsGLqBer2wc11efcoBfh62x0Pf6K8wqFBz89Xs4ggfXxLX7vjAIBLovjBaTt0uESvzNupj1ekKNDPW38Z2lLj+8XJ34c3TTh1xWUVx83mqSx6Dh4ukSQF+nmrS1TYsVO2usWEqx6redzW5rQ83TNzvXYcOKxresfowRHtmN9goyfnbNH7DHSGG3M4LP269YCmLNitDam5igz21y0Dm+naPrG89jihuZv3646P1uitsT10QYdGdscBAJdE8YMztvNAgZ7+Yavmb89STL1A/evCthresRGDE/H/HL+aZ13VaVtb0n9fzRNXP7Cy4IkNV/eYMLVpGMzyew9TXFah//yyQ28v3qOo8Dp66cqu6t2snt2xPM62/fka8eoSXdUrWk9fykBnuDfLspSw+5CmLNilpbsOKbSOr27oF6cb+sVx6rATue7d5dqbdUSL7juH9wYAcIYofnDWFu3I0lPfb9GOA4fVO66eHrq4nTpHhdkdCzYqLqvQprS8qpU8lat5sgoqV/PU8fVW56hQdY/9faetBpwuiCqrkrI1aeYGpeYU6pYBzTTp/DacglFLLMvSVW8t187MAv3GQGd4mPWpuZo6f5d+3nJAgX7eurZ3jG4Z2FyNQtl50E67Mgt07uRF+scFbTTxnJZ2xwEAl0Xxg2pRXuHQzNX7NPmX7Tp4uFSXdWuqfwxvo8ahdeyOhhpmWZbScosqBzAnVw5g3pKRr7KKytePmHqB6h4TdqzoaduI1Tw4sSMl5Xrmx636aHmKWkbW1eQxXSiTa8E36/bp759v0LOXddLVDHSGh9pxoEBvLNit2RvS5W2MLu/RVLcPaqG4BkF2R/NIj8zarM9WpirhX0OZKQkAZ4HiB9WqoLhMUxfs1ntL9srLSLcNaqE7BjdXoB/nzLuL4rIKJabnaU1yjtYmV562lVm1mifA10udo44OYK4se1jNgzO1cEeW/vnlRmUdLtFd57TUXUNbypfSsEbkF5dp6IsL1TS8jr65sx8DneHxUrML9dai3Zq5ep/KKxy6uHMT3Tmkhdo1DrE7mscoKC5T36fn6YKOjTR5TFe74wCAS6P4QY1IzS7Uc3O3ac7GDEUG++sfF7TR5d2j+DDhgtJzj+60VVnyJKbnHVvNE12vzrFdtrrHhKtt42A+mKNa5RWW6bHvEvXNujR1ahqqyWO6qFVDtvKtbo9/l6gPlyVp9sQB6hQVanccwGlkFhTrvSV79VFCso6UVmhY20hNOKeFesQyg6ymTU9I0iOzEvXtxP7qyqB5ADgrFD+oUWuSs/XEnK3akJqrDk1C9NCI9opvUd/uWPgTJeUV2pyWr3UpOcfKnv35xZIkfx8vdYkKU7djO22FKTKY2QeoHXM3Z+iBbzbrcEm5/nF+G900oJm8KZKrxZb0fF382mJd2ydGT41moDPwR/IKyzQtIUkfLN2rnMIy9WlWTxPPaamBrRqwqUUNsCxL505eqLr+Ppp11wC74wCAy6P4QY1zOCx9tzFdz/24Tel5xTq/fUM9cFE7zpd3Ahl5RcdW8qxNyVFiWr5KKxySpKjwOv91yla7xiGs5oGtsgpK9MA3m/TLlgPqHVdPL17ZRTH1A+2O5dIsy9KYtxK0O+uIfps0WGGBDHQGTqSwtFyfrkzVO4v2aH9+sTo1DdWEIS10QYdGrGquRkt3HdR1767QS1d20eU9ouyOAwAuj+IHtaa4rELvLt6jqQt2q6zCoXHxcfrr0FYKDfS1O5pHKCmvUGJ6ftUA5sqyJyPv99U8naNCq1byhKt7LKt54Jwsy9JXa9P0+OxEVViWHhzRTtf2juEb9zP09dp9umfmBj1/eWeN6RVtdxzAZZSUV+jbdWl6Y8FuJR0qVIuIIN0xuIVGd2vKlyTV4PYZq7UqKUfL7h/Kzo4AUA0oflDrMguKNfnnHfp8dapC6/jqb8Na6bq+sbxRqmb784qrTteqXM2zOT1fpeWVq3mahtWp2mWr8rStdo1D5OfDv3+4jrTcIt335QYt3XVIg1tH6LnLO7Pt8mnKKyrTsJcWKLpeoL66g4HOwJmocFj6YVOGpi7Yra0Z+WoaVke3DWquq3pFU1icobTcIg187jfdPriF/jm8rd1xAMAtUPzANlvS8/XU91u0bPchNY8I0oMXtdPQtpF8c38GSssdSkzPq9xSPSVH65JzlF61msfPx0udm4YeK3q6xYSrYQgfkOH6HA5LH61I1tM/bJW/j7eeGNVBI7s04TXkFD02O1HTE5I0+64B6tiUgc7A2bAsSwu2Z2nK/F1anZyjBnX9dGP/ZhobH6uQAFY2n47n527Tmwt3a9F95ygqnNN5AaA6UPzAVpZlad7WTD39w1btOXhEA1o20IMj2rFd6kkcyC8+tpJnbUquNqXl/ddqnq4xv2+p3qFJKKt54Nb2ZB3WpC82aF1Kri7q1EhPje6kekHMqjmRowOdr+sTqydHd7Q7DuBWVu7N1pT5u7RwR5aC/X00Nj5WNw1opgZ1/e2O5vSKyyrU79nf1DM2XG+P+8PPJwCAM0DxA6dQVuHQR8uT9fKvO1VQXKYxPaN1z/mtmTOjytU8WzLyjxU961JylZZbJEny8/ZSx6YhlSVPbOWW6pzuAk9U4bD01qLd+s8vOxRax0/PXtZJ57ZvaHcsp+RwVA503nPwiOZPGsKcNaCGbE7L0xsLduuHzRny8/bSNb1jdOug5moaVsfuaE7r6Nyxj27uowGtGtgdBwDcBsUPnEpuYalenbdL0xOS5O/jpQnntNTNA5p51HnymQXFWpuce2xL9Y378lRStZqncWjAsa3Uu8eGq0OTEPn7eM6/G+Bktmbk656ZG7Q1I19X9ojSI5e0VzCnWfyXL9fs071fbNDzV3TWmJ4MdAZq2u6sw3pr4W59vTZNkjS6W1PdMbiFWkbWtTmZ8xk1ZakKiss0757BnLYLANWI4gdOaU/WYT3z4zb9suWAmobV0X3D27jl7I6yCoe2HlvNUzmfZ1/O76t5OhxdzVO101bjUL4lBE6mtNyhV+bt0BsLdqtxaB29cEVn9WvJN8dS5UDnoS8uUGz9QH3JQGegVqXlFumdRXv02aoUlZQ7NLxDI00Y0lKdopixJUnrU3M1espSPT6yg8b3i7M7DgC4FYofOLVluw/qqTlbtSUjX91iwvTQiPbqERtud6wzllVQUjWXJ0frknO1MS1XxWWVq3kahQSoe2zYsS3VOzZlNQ9wNtam5OjemRu05+AR3dAvTv8c3lZ1/Dz7mHp01mbNWJ7MQGfARocOl+iDpUmalpCkguJyDWodoYlDWqh3s3pu9wXX6bhn5nr9tHm/lj8wjJWaAFDNKH7g9Coclr5au08v/LRdWQUlurhzY91/YVun3+mhrMKhbRkFx4qetSk5Ss2uXM3j623UoUnosZU83WPC1YRz/oFqV1RaoefmbtOHy5LUvEGQXhrTRd1iXLc8Phub0/I08vUlGts3Vo+PYqAzYLf84jJ9vDxF7y3Zo4OHS9UjNlwTz2mhc9p43g6nhw6XKP7Z33RVz2gGzgNADaD4gcs4UlKutxbu1tuL98hhSbcMaKY7h7Rwmm+FDh4u+a9Ttjbu+301T8MQ//86ZatDk1CPmlsE2G3ZroP6x5cblZFXpDuHtNDdw1p71G53DoelK95cpuRDhfrt3iEKreMcr5sAKneymrk6VW8t3KO03CK1bRSsCee01IhOjeXtIadjTl2wS8/P3a5f/j5IrRoG2x0HANwOxQ9cTnpukV74abu+WZemBnX9dM95bXRVr+hafXNUXuHQtv1Vq3mqyp6U7EJJlat52jcJVfejW6rHhqtJaIDHfXsHOJv84jI9+d0WfbFmn9o1DtHkMV3UrnGI3bFqxczVqbrvy4168couuqJHlN1xAPyBsgqHZq9P19QFu7Q764hi6wfqjsEtdFn3pm596nd5hUODX6icPfbJrX3tjgMAboniBy5rfWqunpqzRauTc9S2UbAeHNFOA1tF1MhzHTpccmwlz9rkyp22isoqJEkRwf7HSp4eseHq2JTVPIAz+2XLAf3r603KKyrV389rrdsGNpePt/uu/skrLNM5Ly1Q8wZBmnl7PAOdASfncFj6ecsBTV2wSxv35alhiL9uHdhc1/SOUZC/j93xqt1Pift1+4w1evP6HhresZHdcQDALVH8wKVZlqUfN+/XMz9uVWp2kYa2jdQDF7VVy8gzXyZ8dDVP5XbqlWVP8qHK1Tw+Xkbtm4T8vqV6TLiiwuuwmgdwMdlHSvXQt5v0w6b96h4TppfGdFWzBkF2x6oRj8zarI+WJ2vOXwaqfRPPWOEEuAPLsrRk10FNnb9bCXsOKSzQVzf2a6bx/WIVFuhnd7xqc/27K7Qn67AW3XeOW5fwAGAnih+4heKyCk1blqTXf9ulwrIKXd8nRnef21r1gk7+xij7SGnV6Vo5VbN58lRYWrmap0HdqtU8sZXzeTpHsZoHcBeWZWn2hnQ9MitRpeUO/euitrq+T6xbrYg5OtB5XHycHhvZwe44AM7QmuQcvbFgl37dmqkgP29d1zdWtwxopsiQALujnZVdmQU6d/Ii/eOCNpp4Tku74wCA26L4gVs5eLhEL/+6Q5+sSFGQv4/uHtZK4+Ljjg1xrXBY2r7/95221qXkau/BI5Ikby+j9o1D/qvoYTUP4P4O5Bfrvi83auGOLA1o2UDPX9HZLXbZczgsXf7mMqVmF2nepMEMdAbcwLb9+XpjwW59tyFdPl5eurJnlG4f1EIx9Z17p9M/8+iszfp0ZaqW/WuoGtT1tzsOALgtih+4pR0HCvTU91u1aEeWYusHaniHRtqUlqcNqbk6cmw1j5+6Hd1pKyZMnaPCVMeP1TyAJ7IsS5+uTNVT32+RtzF6dGQHXd69qUsXvzNXpeq+rzbqpSu76HIGOgNuJfnQEb21aI++XL1PFZalSzo31p1DWqpNI9fZEetwSbn6Pj1P57dvqMlXdbU7DgC4NYofuLUF2zP17++3as/BI2rXOPj3LdVjwhVdj9U8AP5byqFC3fvFBq1MytZ57Rvqmcs6ueS30LmFpRr60kK1iKgc6MxrHeCeDuQX670le/XR8mQVllbo3HYNNeGcFuoeE253tJOakZCkh2cl6psJ/dTNBfICgCuj+IHbsyxLpRUOt94KFUD1qXBYen/JXr3w83bV9ffR05d21PCOje2OdVoe+naTPl2Zqjl/GeAxW9YDniznSKmmJSTpg6VJyisqU78W9TVhSEv1b1nfKYtfy7J03n8WKdDPW7Mm9nfKjADgTk5U/DBWH27BGEPpA+CUeXsZ3Tqoub7/ywA1CQvQHR+t1d8/X6+8wjK7o52STfvy9PGKFI2Lj6X0ATxEeJCf/nZuay27f6geGtFOuzIP6/r3Vmj0lKX6KXG/HI7a+zL3VCTsPqRdmYc1Lj6O0gcAbMaKHwCARyurcOj133bp9fm7FFHXX89d0VmDW0fYHetPORyWLn1jmdJyivTbvYMVEsBAZ8ATlZRX6Ou1aXpjwW6lZBeqVWRd3TmkhS7p0kS+TrBl+h0z1mjF3kNK+NcwdksFgFrAih8AAP6Er7eX/n5ea307ob+CA3w0/v2VevCbTTpSUm53tD80c3WqNqTm6sERbSl9AA/m7+Ota3rH6LdJg/XK1V3l7WV0z8wNGvLCAs1ISFJxWYVt2dJyi/Tzlv26qlcMpQ8AOAGKHwAAJHWKCtV3fxmgWwc20ycrU3TRq4u1Kinb7lj/JedIqZ6bu0294+ppdNemdscB4AR8vL00qmtT/Xj3QL03vqcahvjr4VmJGvDcfL25cLcKimv/FNZPViRLkq7rE1Przw0A+P8ofgAAqBLg660HR7TXZ7f2lcOyNOatBD3zw1Zbvzk/3gs/b1d+cbmeGN2BmRkA/osxRsPaNdRXd/bTZ7f1VbvGwXr2x23q/+xveunn7Tp0uKRWcpSUV+izlaka1q6housF1spzAgBOjOIHAID/0ad5ff149yBd3StGby3ao5GvL9HmtDxbM23cl6tPV6bohn5xatuIgc4A/pgxRn2b19eMm/vou7sGqH/LBnp9/i71f+43Pf5dotJzi2r0+X/YlKFDR0o1Lj62Rp8HAHDqGO4MAMAJzN+eqX9+uVHZR0r112GtNGFIC/nU8uBUh8PSpVOXKj2vWL9NGqxgZvsAOA27Mgv0xoI9mrU+TcZIl3WL0u2Dm6t5RN1qf67RU5Yqv7hMv/59sLy8WJkIALWF4c4AAJyhc9pE6ue/D9JFnRpr8i87dPkby7Qrs6BWM3y+OlUb9uXpoRHtKH0AnLaWkcF6aUwXLfjHEF3bO0bfrk/TsMkLNfGTtUpMr77VjBtSc7U+NVfj+sZS+gCAE6H4AQDgJMIC/fTqNd005druSsku1IhXl+jdxXvkcNT8qtmjA537NKunkV2a1PjzAXBfUeGBenxURy3551DdObiFFm3P0ohXl+iGD1Zq5d6zH2Y/PSFZQX7eurxHVDWkBQBUF4ofAABO0YjOjfXT3wdpYKsGeur7rbrmneVKzS6s0ed8/qftKigu1xOjOjLQGUC1iAj2133D22rJ/UP1jwvaaNO+PI15K0FXvrlM87dn6kxGQWQfKdV3G9N1afemrEwEACdD8QMAwGmIDA7QO+N66vkrOisxPV/DX16kz1amnNEHpZNZn5qrz1al6MZ+cWrTKLjaHx+AZwut46uJ57TUkn8O1WOXtFdaTpFu/GCVRry6RHM2pqviNFY1fr4qVaXlDo2Lj6u5wACAM8JwZwAAztC+nEL944uNSthzSEPbRurZyzopMiSgWh67omqg8/68Ys1joDOAWlBa7tCs9Wl6Y+Fu7ck6omYNgnTH4Oa6tFuU/Hz+/PviCoelQc/PV0y9QH16W99aTAwAOIrhzgAA1ICo8EB9fEsfPXpJey3ddVDn/WeRZm9Ir5bH/mxVijbuy9ODDHQGUEv8fLx0Zc9o/fL3wZp6XXcF+Xvrn19t0uAX5uv9JXtVWFr+h/ebt/WA0nKLNL4fW7gDgDNixQ8AANVgd9ZhTZq5QetTczWic2M9NaqjwoP8zuixso+U6pwXF6hd42B9emtfZvsAsIVlWVq086CmzN+llXuzVS/ITzf2i9O4+DiFBv5eSI99b4V2ZR7W4vvOkY833ysDgB1Y8QMAQA1rEVFXX94Rr39c0EY/J+7X+S8v0m/bDpzRYz0/d5uOlDDQGYC9jDEa3DpCM2+P15d3xKtrdJhe+mWH+j/3m575casyC4orC5+dB3VdnxhKHwBwUqz4AQCgmm1Jz9c9M9dr2/4CXdUzWg9dfOqna61NydFlU5fptkHN9cBF7Wo4KQCcni3p+Xpj4W59vzFdPt5eiqsfqKSDhVr2r6FqUNff7ngA4LFY8QMAQC1q3yREs+7qrzuHtNAXa1I1/OXFSth96KT3q3BYemTWZjUM8ddfh7WqhaQAcHraNwnRa9d007xJQ3RZt6bae/CIRndrQukDAE6MFT8AANSgNcnZmjRzg5IOFeqm/s103/A2CvD1/sPbzlierIe/3azXrummS7o0qeWkAHD68orKVMfX+4S7fgEAah4rfgAAsEmP2Hr64e6BGh8fq/eX7tWIVxdrQ2ru/7vdocMlevGn7erXor4u7ty49oMCwBkIreNL6QMATo5XaQAAalign48eH9VRH93cR4WlFbrsjWV66eftKi13HLvN83O3Vw107sBAZwAAAFQbih8AAGrJgFYNNPdvgzS6a1O99tsuXTp1qbbvL9DalBx9vjpVNw9sppaRwXbHBAAAgBthxg8AADb4KXG/Hvxmk/KLytW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      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "q.groupby('de').title.count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d3dc1ce",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c43bff76",
   "metadata": {},
   "source": [
    "Plot the number of \"Rustler\" characters in each decade of the history of film."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "982a7256",
   "metadata": {},
   "outputs": [],
   "source": [
    "w = d[d.character=='Rustler']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "188582be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='de'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "w.groupby('de').character.count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "819594c3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "16b6c3dc",
   "metadata": {},
   "source": [
    "Plot the number of \"Hamlet\" characters each decade."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "15802a2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "e = d[d.character==\"Hamlet\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "d4c6c0dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='de'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NWbr+yfUqqarTizMu1veuYKt2oLEac8XPYklPSnr+pON/t9b+tdknAgAAAABAJ1a7Lu3fVX+/bQTVLuAcnTX4sdauNcZEt8IsAAAAAABIqq92PbA0WRlUu4AmOWvV6wweNMZsd1XBOp/uTsaYmcaYzcaYzYWFhU14OgAAAACAt7PW6uWN9dWu0qo6LZ0xlmoX0ATnG/zMkxQnaYSkfEl/O90drbULrbUJ1tqEyMjI83w6AAAAAIC3K6+u0w9f2apHVuzQ6OgIvfu9Cbokrou7xwI82nnt6mWtPXjsc2PM05LeabaJAAAAAAA+JyW/RHOX1Ve7HrpqoB6g2gU0i/MKfowxPa21+a4vb5S080z3BwAAAADgVOp37crWr1buUseQQC2dMZarfIBmdNbgxxjzkqRESV2NMTmSfiUp0RgzQpKVlCFpVsuNCAAAAADwRmXVdXr0jR16a2ueJgzoqiduZdcuoLk1ZlevO05xeFELzAIAAAAA8BEp+SWauzRZGYfK9eOrB+qBxP7yo9oFNLvzqnoBAAAAAHA+rLV6eVO2fr1yl8JDArXsO2M1NpZqF9BSCH4AAAAAAK3i5GrX328boa6hVLuAlkTwAwAAAABocVS7APcg+AEAAAAAtBhrrV7amK3fvE21C3AHgh8AAAAAQIsoq67Tz1fs0MptVLsAdyH4AQAAAAA0u915JXpwWX216+FrBmnOpDiqXYAbEPwAAAAAAJrNsWrXr9/epc7tA/XSd8bqYqpdgNsQ/AAAAAAAmgXVLqDtIfgBAAAAADTZ7rwSzV2WrEyqXUCbQvADAAAAADhv1lot25il37y9m2oX0AYR/AAAAAAAzktpVa1+/sZOvb0tTxMHRurvtw5XF6pdQJtC8AMAAAAAOGe78or14LItVLuANo7gBwAAAADQaCdXu16eeYnGxES4eywAp0HwAwAAAABolNKqWv1sxQ69sz2fahfgIQh+AAAAAABntSuvWHOXJiv7SKV+MnmQZk+k2gV4AoIfAAAAAMBpWWu19Iss/fad3YpoH6SXvjOWahfgQQh+AAAAAACn1LDaNWlgpJ6g2gV4HIIfAAAAAMDX7Mwt1oPL6qtdP508WLMmxlLtAjwQwQ8AAAAA4DhrrV78Iku/c1W7Xp45VqOjqXYBnorgBwAAAAAgqb7a9ciKHVq1PV+JgyL1xK0jFNEhyN1jAWgCgh8AAAAAANUuwEsR/AAAAACADzte7Xp7tyI6UO0CvA3BDwAAAAD4qIbVrssGRepvVLsAr0PwAwAAAAA+aGduseYuS1bOkUo9cu1gzZxAtQvwRgQ/AAAAAOBDrLV68fNM/e6dFHUJDdIrM8cqgWoX4LUIfgAAAADAR5RU1epnr+/Qqh1UuwBfQfADAAAAAD6Aahfgmwh+AAAAAMCLUe0CfBvBDwAAAAB4qZKqWj3y+na9u+OALhsUqSduHaHOVLsAn0LwAwAAAABeaGdusR5Ymqzco5X62bWD9R2qXYBPIvgBAAAAAC9irdULn2fq8XdS1DU0SK/OGqv4flS7AF9F8AMAAAAAXqK0qlY/dVW7Lh/cTX+7ZTjVLsDHEfwAAAAAgBfIPlyh+xdvUlpROdUuAMcR/AAAAACAh9uccVgzX0iSw2n1wvQxGhfX1d0jAWgjCH4AAAAAwIO9sSVHP12+Q707h2jRtATFRoa6eyQAbQjBDwAAAAB4IKfT6omPvtSTn+zXJbFdNO/bo9SpPev5ADgRwQ8AAAAAeJjKGoceem2r3t1xQLeP7qPf3TBMgf5+7h4LQBtE8AMAAAAAHqSgpEoznt+sHbnFemzqEE2/NEbGsIgzgFM7ayRsjHnWGFNgjNnZ4FiEMeYjY8w+18fOLTsmAAAAAGBXXrGuf2q99heU6em7EzRjQiyhD4Azasy1gIslTT7p2COSPrbWDpD0setrAAAAAEAL+XDXAd0yf4OMpOWzx+nKod3dPRIAD3DW4Mdau1bS4ZMOXy9pievzJZJuaN6xAAAAAACSZK3VgjWpmvVikgZ0D9ObD47X0F4d3T0WAA9xvmv8dLfW5kuStTbfGNOtGWcCAAAAAEiqqXPqsTd36NXNOZp6UU/97ZbhCg70d/dYADxIiy/ubIyZKWmmJPXt27elnw4AAAAAvMKR8hrNfjFJX6Qf1veuGKAfXDFAfn6s5wPg3Jzvfn8HjTE9Jcn1seB0d7TWLrTWJlhrEyIjI8/z6QAAAADAd6QWlunG/6zXluyj+sdtI/SjqwYS+gA4L+cb/KyUNM31+TRJbzXPOAAAAADg29bvL9KNT61XaVWdXvrOxbphZG93jwTAg5216mWMeUlSoqSuxpgcSb+S9CdJrxpjpkvKknRLSw4JAAAAAL5g2RdZ+uVbOxUb2UGLpo1Wn4j27h4JgIc7a/Bjrb3jNDdd0cyzAAAAAIBPcjit/vBuihZ9mq7EQZH69x0jFRYc6O6xAHiBFl/cGQAAAABwemXVdfreS1v0vz0Fum98tB6dMkQB/ue7KgcAnIjgBwAAAADcJOdIhWYs2ax9BWX63Q3DdPfYfu4eCYCXIfgBAAAAADdIzjqimc9vVnWdU4vvG60JA9gFGUDzI/gBAAAAgFa2cluefvzaNvXoGKyXZ45W/26h7h4JgJci+AEAAACAVmKt1T8/3qd//HefxkRHaP7d8YroEOTusQB4MYIfAAAAAGgFVbUO/WT5dq3clqeb46P0+xuHqV2Av7vHAuDlCH4AAAAAoIUVllZr5gubtSXrqH46ebBmT4qVMcbdYwHwAQQ/AAAAANCC9hwo0fTFm3W4vEbzvx2vycN6uHskAD6E4AcAAAAAWsj/9hzUd5dtUWhwgF6bfYmG9Q5390gAfAzBDwAAAAA0M2utnl2fod+v2q2hvTrqmXtGq0d4sLvHAuCDCH4AAAAAoBnVOpz61cpdWvZFliZf0ENP3DZc7YP40QuAe/C3DwAAAAA0k+KKWj2wLEnr9x/SA4lx+vHVg+TnxyLOANyH4AcAAAAAmkFGUbnuX7xJ2Ucq9Ldbhuum+Ch3jwQABD8AAABwP4fT6lB5tQpLG/wqq/9YVFajwtIq1Tms7r80RtcO68E22GhzPk87pNkvJslIWjpjrMbERLh7JACQRPADAACAFmKtVUlV3deCnFN9fbi8Wk779e8R2i5AkWHtFBnaTocravTA0mQl9Ousx64bqhF9OrX67wk4lVc3ZevRN3eoX5cOWjQtQf26dHD3SABwHMEPAAAAzklVreOsQc6xr2vqnF97fKC/UWRoO0WGtVPvTsEa0Sf8+NfHf4UGq2tY0AkL4tY5nHp1c46e+GivbnhqvW4Y0UsPTx6s3p1CWvO3DxzndFr9+f09WrA2TRMGdNWTd45SeEigu8cCgBMYa0/x1koLSUhIsJs3b2615wMAAEDjnKlqdfLXpVV1X3u8MVJE+6AGwc3JQc5Xn4eHBDapqlVaVav5a1L19Lp0GUnfmRCr2YlxCm3He5poPeXVdfrBK1v10e6DuntsP/3qG0MV4O/n7rEA+ChjTJK1NuGUtxH8AAAAeKfmqFqFuapWXc8S6ER0CFJgK//Qm3OkQn/5YK/e2pqnrqHt9NDVA3VrQh/5s4MSWlh+caWmL96sPQdK9Mvrhure8THuHgmAjyP4AQAA8CLHqlYFpwl0isrOXLUK8vf7Ksw5TZDTLayduoa2U0iQvxt+h+dmS9YRPb4qRUmZRzS4R5genTpEEwZEunsseKntOUc1Y8lmVdQ49O87R+qyQd3cPRIAEPwAAAC0dXUOpw6X19SHOae5MqfI9XVp9amrVl06BKnrGSpW3Vxr53QMCfC6XbGstXp3xwH98b0U5Ryp1GWDIvXzKUM0oHuYu0eDF3l3R75+9OpWdQ1tp0XTRmtQD/58AWgbCH4AAADcwFqrkso6FZZVfXV1zmmu0DlUXqNTvSwLCw44ZcXqeMATWh/oRHQIYn0R1V8NteSzDD35v/2qqHXozjF99YMrB6hLaDt3jwYPZq3VU5/s118//FLx/Tprwd3x6sqfKQBtCMEPAABAM6qscaio7PRVq8Kyr67OqXGcomoV4HfGxY8bfh0c2ParVm3RobJq/eO/+7RsY5baB/rrwcv7a9q4aP574pxV1zn0yOs79MaWXN0wopf+dNNF/DkC0OYQ/AAAADSStVY7cou150DpeVStzh7kRIa1U8dg76tatVX7C0r1h3f36H97CtQnIkSPTB6iKRf24L8/GuVQWbVmvZCkzZlH9NBVA/Xg5f35swOgTSL4AQAAOIuDJVV6Y0uuliflaH9B2fHjHY9VrcLaKTIsWF1Dg04Z7ES0p2rVlq3bV6jfr0rRngOliu/XWY9NHaKRfTu7eyy0YV8eLNX0JZtUUFKtJ24doakX9XT3SABwWgQ/AAAAp1BV69B/Uw5qeVKO1n5ZKKeVEvp11s3xURrfvytVKy/jcFq9tjlbf/3wSxWVVeubw3vpJ5MHKapze3ePhjZmzZeFenBpsoKD/PX0PQka0aeTu0cCgDMi+AEAAHCx1mpbTrGWJ2Vr5dY8lVTVqVd4sL41Kko3xUcppmsHd4+IFlZWXaf5q1P19Lo0WUkzLo3RnMQ4hQUHuns0tAFLPsvQb97epUE9OmrRtAT16hTi7pEA4KwIfgAAgM87WFKlFcm5Wp6UrdTCcgUH+unaYT11c3yULontIj8/1u3wNblHK/WX9/foza156hoapB9dNUi3JkRR2fNRdQ6nfvvObj2/IVNXDumuf94+Qh3aBbh7LABoFIIfAADgk6pqHfpod32Va92++irX6Oj6KteUC3tyhQckSduyj+rxVbu1KeOIBnUP06NTh2jiwEh3j4VWVFJVq7lLk7VuX5FmTozVTycPlj9hMAAPQvADAAB8hrVWW7OPanlSjt7e9lWV66b4KH1rFFUunJq1Vu/vPKA/vrdHWYcrNGlgpB6dOkQDu4e5ezS0sKxDFZq+ZJPSi8r1+xuH6bbRfd09EgCcM4IfAADg9Q4UH9uViyoXzl91nUPPf5apf/1vn8qr63THmL764VUD1TW0nbtHQwvYlHFYs15IksNpNf/b8bokrou7RwKA80LwAwAAvBJVLrSUw+U1+ud/v9SLX2QpJNBfcy/rr/vGR7PLmxdZkZyjR17foajOIVp072iuBgTg0Qh+mpnTaXnXEAAAN7HWakuDKldpVZ16dwrRTaN661ujohTND29oRvsLyvSn91L035QC9e4UokeuHazrLuopY3gt6KmcTqu/fbRXT32SqnFxXTTvrniFtyckBuDZCH6aUWWNQ1P+tU5TLuyh+8bHcNkvcArVdQ69kZyrt7fnaVxcV317bD+Fh/CCCkDTHCiu0ootOVqelKM0V5VriqvKNZYqF1rY+v1FenxVilLySzSybyc9NnWo4vt1dvdYOEeVNQ796NWtem/nAd0xpo9+e/0wBbKLGwAvQPDTjApKqvSrlbv0/q4DCvL3060JfTRzYqz6RLR392iA25VW1WrZF1la9Gm6Ckqr1btTiHKPViq0XYDuGttX08fHqFvHYHePCcCDVNU69KGryvWpq8o1JjpCN8dH6doLe1DlQqtyOK1eT8rRXz7cq8LSal13UU/9dPJgXgd6iIMlVfrO85u1I7dYj04ZoumXxnDlFgCvQfDTAlILy7RwTZpWbMmR00rXXdRTsyfFaUjPju4eDWh1haXVWvxZup7fkKnSqjqN799Fcyb11/j+XbQrr0QL1qZp1fY8Bfj56ab43po5MY4ePYDTosqFtq68uk4L1qRq4bo0Oa10//gYPXBZnDoSRLZZO3OLNWPJZpVW1eqft4/UlUO7u3skAGhWBD8t6EBxlRZ9mqZlX2SpvMahywZFak5if42O7sw7CPB62YcrtHBtml7dnK0ah1PXDuuh2ZPidFFUp6/dN/NQuRauTdNrSTmqdTg1ZVh9WHphVHjrDw6gTTq5yhUS6K9rh/WgyoU2K+9opf76wV6t2JKrLh2C9MOrBur20X0UQHWoTflg1wH94OWt6tw+UIvuHc0btQC8EsFPKzhaUaMXNmTquc8ydLi8RvH9OmvOpDhdPrgbL1ThdVLySzR/Tare2Z4vPyPdNCpKMyfGKjYy9KyPLSit0nPrM/TihkyVVtdpwoCumjMpTpfEdSEsBXxQVa1DH+w6UF/l2l8ka6UxMRHHd+UKbRfg7hGBs9qec1SPr0rRxvTDGtAtVI9OHaLEQd3cPZbPs9Zqwdo0/fn9PbooqpOevide3cKonAPwTgQ/raiyxqHXkrK1YE2aco9WamD3UM2eFKdvDO/FwnHwaNZabco4onmr9+uTvYXqEOSvu8b20/3jY9Qj/NxfRJVU1Wrp5/XrARWVVWt4VLjmJMbp6qE9CEsBL2etVXJWfZXrne0NqlzxUbppVG/160KVC57HWqsPdh3UH99LUeahCk0cGKlHpwzRoB5h7h7NJ9XUOfXoGzv0WlKOrruop/56y3AFB/q7eywAaDEEP25Q63Bq1fZ8zVudqr0HS9W7U4hmTIjRbaP7qH0Q717CczidVh/vKdC81fuVnHVUXToE6b7x0bp7bHSzbH1aVevQ68k5Wrg2TZmHKhQb2UGzJ8bp+pG91C6AF2iAN8kvrtSK5Fy9npSjtCJXletCV5UrhioXvENNnVPPb8jQvz7ep7LqOt0+pq9+eOVARYaxE2xrOVJeo1kvJmlj+mF974oB+sEVA/j7BYDXa7HgxxiTIalUkkNS3eme5BhfCn6Osdbqk70Fmrc6VZsyjqhz+0DdOy5G91zST507BLl7POC0ah1Ordyap/lrUrWvoExRnUM0a2Ksbkno0yLvmDmcVu/trA9Ld+WVqHvHdppxaazuuLgvVQ/Ag1Hlgq86Ul6jf368Ty9+nqngQH/NSYzT9EtjuOqkhe0vKNP0JZuUX1ylv9x8ka4f0dvdIwFAq2jp4CfBWlvUmPv7YvDT0KaMw5q/OlUf7ylQ+yB/3TGmr2ZMiFHP8BB3jwYcV1FTp1c2ZevptWnKK67S4B5hmpMYp6kX9myVxSqttVq3r0jzVqdqQ9ohdQwO0LRx0bp3XLS6hPJuKeAJTqhybctTaXV9levm+CjdNCpKfbuw9TV8R1phmf743h59tPugencK0U8mD9I3h/diXbsW8Om+Is1ZmqR2AX5acHeC4vt1dvdIANBqCH7amL0HSrVgTare2pYnPyPdMKK3Zk2KVf9udMDhPkfKa/T8hkwt/ixdRypqNSY6QnMS45Q4KNJtL063ZB3R/DWp+nD3QbUL8NNtCX00Y0Ks+kTwQyPQFuUdrdQbW3K1PClH6a4q15QLe+rm+ChdHBNB1QI+7bPUIj3+Top255doRJ9O+sV1QxTfL8LdY3mNpV9k6pdv7VL/yFA9My2B1woAfE5LBj/pko5IspIWWGsXnuI+MyXNlKS+ffvGZ2ZmnvfzeZvswxVa9Gm6Xt6Upeo6p64e2l2zJ8VpZF/enUDryTtaqWfWpeuljVmqrHXoyiHdNHtSnBKi286L0f0FZVqwJlVvbs2V00rfHN5LsybFanAPtmMF3K2yxqEPd59Y5brYVeW6lioXcAKH02pFco7+8sFeFZRWa+pFPfXI5MGEFE3gcFr9flWKnl2frssGRepfd4xUWHDT1yAEAE/TksFPL2ttnjGmm6SPJH3XWrv2dPfnip9TO1RWrSWfZWjJhkwVV9ZqbGyE5iT218QBXbkMGC1mf0Gp5q9J05tbcmUlXT+8l2ZNimvTu4/kF1dq0bp0LduYpYoah64Y3E2zE+M0ug2FVIAvqK9yHXFVufJVWl2nqM4humkUVS6gMSpq6rRgTZoWrE2V0yndNz5acy/vr44EFuektKpW3395q/63p0D3j4/Ro1OHyJ8rCwH4qFbZ1csY82tJZdbav57uPgQ/Z1ZWXaeXN2bp6XVpOlhSraE9O2pOYpymXNiTf8TQbJKzjmj+6vr6VHCgn24fXb/WVFRnz/lB7WhFfS3tufX1tbSEfp01JzFOlw3qRpUEaEEnV7naB/nr2mFUuYDzdaC4Sn/5YK9WbMlR5/ZB+uGVA3THmL6tsqaep8s5UqHpizdrf2GZfvPNC/Ttsf3cPRIAuFWLBD/GmA6S/Ky1pa7PP5L0W2vt+6d7DMFP41TXOfTWljzNX5uqtMJy9evSXjMnxuqmUVHsBIHzYq3V2n1Fmrd6vz5PO6zwkMDjCyZHePDuchU1dXp1U7aeXpeu3KOVGtQ9TLMTY3XdRb0UyItmoFmcqso1NjZCN8f30bXDeqgDVS6gyXbmFut37+zWF+mH1b9bqB6dMsSta+y1dclZRzTz+c2qrnNq3l3xunRAV3ePBABu11LBT6ykN1xfBkhaZq39/ZkeQ/BzbpxOqw93H9S81fu1LadYXUPbafqlMbprbF8uBUaj1DmcenfnAc1fnard+SXq0TFYMybE6I4xfb3qh7Vah1Nvb6vfev7Lg2Xq3SlEMyfG6taEPgoJIiwFzpW1VkmZrirX9nyVuapcx3blYj0SoPlZa/XR7oP643t7lF5UrgkDuurRqUNYz+4kb23N1cPLt6tneLAWTRut/t1C3T0SALQJrVL1agyCn/NjrdWGtEOatzpV6/YVKaxdgO4a20/3XxqtbmHB7h4PbVBVrUPLk3K0cG2asg5XKDayg2ZPitMNI3orKMB7r4RxOq0+2Vug/6xOVVLmEUV0CNJ946J1zyXRCm9PWAqcTe7RSr2RnKPXk3OPV7mO7co1JpoqF9AaauqcevHzTP3z430qrarVbaP76IdXDfT513zWWv3jv/v0z4/3aUxMhBZ8O16dPfiqZQBobgQ/XmRnbrHmrUnVezvyFeDvp5vjozRzQqyiu3Zw92hoA0qqavXi55l69tMMFZVVa3ifTpozKU5XD+3ucz+wbco4rHmrU/W/PQXqEOSvO8b01fQJMeoZHuLu0YA2pbLGoQ921Ve51qdS5QLaiqMVNfrXx/v1/IYMtQvw0wOX9df0S2N8svZfVevQw8u36+1tebolPkq/v/FCr34jCwDOB8GPF0ovKtfCtWl6PSlHdU6nplzYU7MnxWlY73B3jwY3KCip0rPrM7T080yVVtdp4sBIzZkUp7GxET6/PkBKfokWrEnV29vz5WekG0f21qxJcYqL5NJw+K5TVbn6RHy1KxdVLqDtSC8q15/eS9EHuw6qV3iwfjJ5sL45vJfPvKFTUFqlmc8naVvOUf108mDNmhjr869tAOBUCH68WEFJlRatT9fSz7NUxg/8PiejqFwL16VpeVKO6hwEgGeSfbhCT69L0yubslXjcOqaoT00JzFOw/t0cvdoQKs5VuVanpSjjEMVah/kr6muKtdoqlxAm/Z52iE9vmq3duaWaHhUuB67bqhGR0e4e6wWlZJfoumLN+lIRa3+ftsITR7Ww90jAUCbRfDjA4ora7X0i0w9+2m6ispqNKJPJ8320YqPL6Dyd/6Kyqq1eH2Gnt+QoZKqOo2L66I5iXG6tH9XwlJ4pcoah97fla/lSTn6LPWQrJUuie2im+OjNJkqF+BRnE6rN7bk6v8+2KODJdWacmEPPTJ5iPp28b6r9D5OOajvvbRFYcGBemZaAm9qAcBZEPz4kJMX9Y2L7KBZPrCory841SLf376kn+4bzyLf56Osuk4vfZGlZz5N08GSag3r3VFzJvXX5GE95E9YCg9nrdXmzCNavjlHq3Z8VeW6eVQffWtUb6pcgIerqKnT02vTNX9NqhxOq3vHR2vuZf0VHuL5GxlYa7Xo03T9/t0UDesVrmemJah7R17nAMDZEPz4oGPbeM9bnaqU/BL1DA/W9Eu9bxtvX+B0Wn24+6DmrUnVtuyj6hraTtMvjdFdY/uqY7Dnv8Bzt+o6h97ckqsFa9KUVlSu6C7tNXNinL41qrdPLqAJz5Z7tFIrknK0PDlHmVS5AK93sKRKf/1gr5Yn56hTSKB+eNVA3TGmrwL9PfPNvlqHU798a5de2pila4f10BO3jlBIEP8WA0BjEPz4MGut1nxZqHmrU/VF+mGFhwRq2rho3TsuWhFsgdmm1dQ59ebWXM1fk6q0wnL1jWivWZNiddOoKAKJFuBwWn2464DmrUnV9pxiRYa5AraL+yqMgA1tWEVN3fFduahyAb5pV16xHn8nRRvSDik2soMenTJElw/u5lEV5uKKWs1ZmqTPUg9p7mVxeuiqQYTVAHAOCH4gSUrKPKL5a1L10e6DCg700+2j+2rGhBhFdeaS/7akvLpOL23M0jPr0nWgpEpDe3bUnMQ4XTushwI89B08T2Kt1Wep9ZW6T/cXKSw4QHeP7af7xscoMqydu8cDJJ26ytU3or1ujo/SjSOpcgG+yFqrj1MK9Id3U5RWVK7x/bvo0SlDNbRXR3ePdlbpReWavniTso9U6E/fukg3xUe5eyQA8DgEPzjBvoOlWrA2TW9uyZUkfXNEL82eFKeB3cPcPJlvO1RWrSWfZWjJhkwVV9ZqbGyE5iT218QBLDrsLjtyijV/Tare3ZmvQH8/3ZoQpZkT4rxyEU14hpwjFVqRnKvXXVWuDkH+mnpRT90c30ejozvzdwUA1TqcWvp5pv7x8T4VV9bq1vg+eujqgerWRtfJ2ZB6SLNfTJK/n9GCu+O9fqcyAGgpBD84pdyjlVq0Ll0vbcxSZa1DVw7ppjmJcYrvxz+4rSnnSIWeWZeulzdlqarWqWsu6K7Zk+I0sm9nd48Gl7TCMj29Lk2vJ+WqzunUdRfVh6We8C4qPF9FTZ3e3/lVlUuSxsV9VeVqH0SVC8DXFVfU6t//26clGzIU6O+nOZPiNGNCbJtaM+eVTVl69I2diu7aQc9OG80bKwDQBAQ/OKMj5TVasiFDiz/L0NGKWo2JjtCcxDglDork3eMWtPdAqRasSdVb2/JkJN04srdmTYpV/25cedVWHSyp0rOfpuvFzzNVXuPQpIGRmpMYp4tjIjhX0KystdqUcUTLk7K1anu+ymscx6tc3xrVm4ougEbLKCrXn97bo/d3HVDP8GD9ZPIgXT+8t1vXz3E4rf78/h4tXJumCQO66qm7RrFhBQA0EcEPGqWipk4vb8zWM+vSlFdcpcE9wjQnMU5TL+zJ2jLNaHPGYc1fk6r/phSofZC/7hjTV9MvjVGvTiHuHg2NVFxRqxe/yNSzn6brUHmNRvbtpDmT4nTlkO4sRIkmOVblWp6Uo6zDVLkANJ8v0g7p8VUp2pFbrIuiwvXY1KEaE9P6V3mXV9fp+y9v1X9TDuqeS/rpl9cN5XUmADQDgh+ck5o6p1Zuy9OCNanaV1CmqM4hmjUxVrck9GE3qfNkrdUnews0b3WqNmUcUef2gbp3XIzuuaSfOrO7mseqqnXotaQcLVybquzDlerfLVSzJ8Xpm8N7KSiAF7E4O6fTKutwhTZnHtGK5K+qXOP711e5rrmAKheA5uN0Wr21LVf/9/5e5RdXafIFPfTItYMV3bVDqzx/3tFKTV+yWXsPlOhX37hA08ZFt8rzAoAvIPjBeXE6rT7eU6D/rN6vLVlH1aVDkO6/NEbfHttP4SFcjtsYdQ6n3tmer/lrUrXnQKl6dwrRjAkxum10H36Y8yJ1DqdW7cjXvNX1/597hQdr+oRY3T66D1tp47iqWoe+PFiq3Xkl2p1fot15JUrJL1F5jUOS1K9Le908Kko3UuUC0MIqaxx6Zl2a5q1JVa3DqWmXROu7lw9QePuWe323LfuoZjy/WZU1Dj1550glDurWYs8FAL6I4AdNYq3VxvTDmrcmVav3Fiq0XYDuvLi+ntS9je4Q4W6VNQ69lpSthWvTlHOkUgO6hWpOYpy+MbyXArmc2WtZa7X6y0LNW52qjemH1al9oKZdEq17x0VzZZePOVxe4wp4io8HPamF5XI46//NDW0XoCE9wzS0Z0cN7dVRF/QK1wW9OlLlAtCqCkqq9LcPv9SrSdkKDwnUD64YoLvG9mv21yqrtufrR69uVWRYOz1772h2kgWAFkDwg2azO69E89ek6p3teQrw89O3RvXWzImxio0MdfdobUJxRa1e+DxDz63P0KHyGo3q20kPJPbX5YO7sfaLj0nKPKx5q9P035SDCgn01+1j+mjGhFj1Zi0nr3KsqnXsCp5jHw+UVB2/T6/wYA3t1VFDenY8HvT06dyevxMAtBm780r0+3d3a/3+Q4rt2kE/mzJEVw7p1uQw2lqrJ/+3X3/76EvF9+ushXfHq0tou2aaGgDQEMEPml3WoQotXJeqVzfnqNbh1LXDemj2pDhdFNXJ3aO5xYHiKi36NE3LvshSeY1Dlw2K1JzE/izGCn15sFTz16Rq5dY8SdL1I3pr9qRYDeDdTo9ztqqWv5/RgG6hx8OdoT3rwx6u9gLgCY6tR/j4qhSlFZbrktgueuy6IbqgV/h5fb+qWoceeX273tyapxtH9tYfv3Uha0UCQAsi+EGLKSyt1uLP0vX8hkyVVtXp0v5dNXtSnMb37+ITgUdqYZkWrknTii05cjitvjG8l2ZPitOQnh3dPRramNyjlXpmXZpe3pitylqHrhraXXMS4zSqb2d3j4ZTOFRW/bWreNKKTqxqNQx4hvbqqP7dQvmhBoDHq3U49dLGLP39oy91tLJWN4+K0o+vGXRO9f6ismrNeiFJSZlH9OOrB2ruZf194nUhALgTwQ9aXGlVrZZ9kaVnPk1XYWm1LuwdrjmJcbrmgh7y98I6w7bso5q/JlXv7zqgIH8/3Ta6j74zIVZ9IliQFWd2uLxGSz7L0JINGTpaUauLYyI0JzFOkwZG8qLYDZxOq8zDFV9bj+dgSfXx+xyran0V9IQrqnMIVS0AXq24slZPfbJfz61PV4Cfn2ZPitN3JsacdXOKLw+W6v7Fm1RYWq2/3zZCUy7s2UoTA4BvI/hBq6mqdeiNLblasCZVGYcqFNO1g2ZNjNWNo3qrXYBnvxNurdX6/Yc0b81+rd9/SGHBAfUL946PVlf66jhH5dV1enlTtp5Zl6b84ioN6dlRsyfFauqFPRXAAuAtoqrWob0HSk+4kiclv0QVrqpWgJ9Rf6paAHCCzEPl+vP7e/TujgPq0TFYD18zSDeO7H3K8Hv13gI9uGyLQoL89cw9CRrep1PrDwwAPorgB63O4bR6f+cBzVuzXztzS9QtrJ1mTIjRnRf3U6iHbW/tcFp9sOuA5q1O1Y7c4uO/lzvG9FVYMNvao2lq6px6a2uu5q9JVWphufpEhGjmxDjdEh9FbagJisqqlXJSVSu1sEyuppbC2gVoyLGreKhqAcBZbco4rMff2a1tOcUa1rujHps6VGNjuxy/ffH6dP32nd0a3KOjnpmWoF5sZgAArYrgB25jrdWn+4s0b3WqPks9pI7BAbrHQ66Sqa5zaEVyrhauTVN6UblXXb2EtsfptPoo5aDmrU7V1uyj6hoapPvGx+jbY/spPISA8XScTquMQ+VfW4+noPSrqlbvTiH1O2q5gp4LenVUVOcQqnUAcI6cTquV2/L0f+/vUV5xla65oLsevmawlnyWoRc+z9SVQ7rrn7ePUAcPe5MPALwBwQ/ahG3ZRzVvdao+2N2218U5tl7Rok/TVeBar+iBxDhd7aXrFaFtsdbqi/TDmrc6VWu+LFRouwDdNbavpo+PUbdzWFjTG1XWOLT3+K5a9evx7DlQ+vWq1gnr8XRUp/ZUtQCgOVXVOrTo03T955P9x3c2nDUxVj+ZPJjXSgDgJgQ/aFMa7oTltNJ1F/VsEzthnWqHsjmJcRoX5xs7lKHt2ZlbrAVr07Rqe54C/Px0U3yUZk2MVXTXDu4ercUVlVWfcAXP7vwSpZ2uquX6OKB7KFfjAUArKiit0oI1aRrWu6NuHBnl7nEAwKcR/KBNOlBcpUWfpmnZF1kqr3HoskGRmpPYX6OjO7dq0JJ1qEJPr0vTq5uzVeNw6tphPTR7UpwuiurUajMAZ5J5qFwL16bptaQc1TmcunZYfVh6YVS4u0drMofTKpOqFgAAANAkBD9o045W1OiFDZl67rMMHS6vUXy/zpozKU6XD+7Wotsl784r0fw1qXpne578/YxuGhWlmRNjFRsZ2mLPCTRFQWmVnlufoRc3ZKq0uk4TBnTVnElxusRDrkprTFVrQPcw125aYVS1AAAAgEYi+IFHqKxx6NXN2Vq4Nk25Rys1sHuoZk+K0zeG91JgM21vba3VxvTDmrcmVav3FqpDkL/uGttP94+PUY9w314/BZ6jpME6VIWl1RoeFa45iXG6emiPFg1Lz0VhafVJV/EUK72o/KuqVnDACTWtY7tqUdUCAAAAzh3BDzxKrcOpVdvzNW91qvYeLFXvTiH6zoQY3Ta6r0KCzu+HQqfT6uM9BZq3er+Ss46qS4cg3X9pjL59cT+Ft2fHJHimqtr6necWrE1V5qEKxUZ20OyJcbp+ZK9WC1Acx3bVOmk9nsKTqlonL7hMVQsAAABoPgQ/8EjWWn2yt0DzVqdqU8YRRXQI0rRLojVtXL9GVz9qHU6t3Jqn+WtSta+gTFGdQzRrYqxuSeij4ECuLIB3cDit3ttZH5buyitRj47BmjEhRreP6avQZtxSt7LGoT0HTgx49uSXqrL261Wt40FPz46EqwAAAEALI/iBx9uUcVjzV6fq4z0Fah/krzvG9NWMCTHqGR5yyvtX1NTp5Y3ZemZdmvKKqzS4R5jmJMZp6oU9FdBMtTGgrbHWat2+Is1bnaoNaYfUMThA08ZF695x0eoS2u6cvhdVLQAAAMBzEPzAa+w5UKIFa9K0clue/Ix0w4jemjUpTv271S/IfKS8Rks2ZGjJZxk6UlGrMdERmpMYp8RBkdRK4FO2ZB3R/DWp+nD3QbUL8NNtCX00Y0Ks+kS0P+F+DqdVetFXu2ql5FPVAgAAADwNwQ+8TvbhCj2zLk2vbM5WdZ1TVw/trp7hIXplU7Yqax26ckh3zUmMVXy/CHePCrjV/oIyLVybqje25MpppW8O76VRfTsp5UCpa1etElXVOiVJgf5GA7qFnRDyDOlBVQsAAABo6wh+4LUOlVVryWcZWvxZhsprHLp+RC/NnhSngd3D3D0a0KbkF1dq0bp0LduYpYoahzoGB7gCnvDjQU//bqEKCqAKCQAAAHgagh94vYqaOlXXOtW5Q+MWfQZ8VUlVrUoqa9W7E1UtAAAAwFucKfhpvu1eADdqHxSgRm70Bfi0jsGB6hhMdQsAAADwFVzTDwAAAAAA4KUIfgAAAAAAALwUwQ8AAAAAAICXalLwY4yZbIzZa4zZb4x5pLmGAgAAAAAAQNOdd/BjjPGX9JSkayUNlXSHMWZocw0GAAAAAACApmnKFT9jJO231qZZa2skvSzp+uYZCwAAAAAAAE3VlOCnt6TsBl/nuI4BAAAAAACgDWhK8GNOccx+7U7GzDTGbDbGbC4sLGzC0wEAAAAAAOBcNCX4yZHUp8HXUZLyTr6TtXahtTbBWpsQGRnZhKcDAAAAAADAuWhK8LNJ0gBjTIwxJkjS7ZJWNs9YAAAAAAAAaCpj7dfaWY1/sDFTJP1Dkr+kZ621vz/L/QslZZ73EwJn1lVSkbuHADwA5wrQOJwrQONwrgCNw7mCltTPWnvKmlWTgh+gLTHGbLbWJrh7DqCt41wBGodzBWgczhWgcThX4C5NqXoBAAAAAACgDSP4AQAAAAAA8FIEP/AmC909AOAhOFeAxuFcARqHcwVoHM4VuAVr/AAAAAAAAHgprvgBAAAAAADwUgQ/aNOMMc8aYwqMMTsbHBtujNlgjNlhjHnbGNPRdfwqY0yS63iSMebyBo+Jdx3fb4z5lzHGuOP3A7SEczlPGtze1xhTZoz5cYNjnCfwaud6rhhjLnLdtst1e7DrOOcKvNo5vv4KNMYscR1PMcb8rMFjOFfg1YwxfYwxn7j+7O8yxnzfdTzCGPORMWaf62PnBo/5meuc2GuMuabBcc4XtBiCH7R1iyVNPunYM5IesdZeKOkNSQ+7jhdJ+obr+DRJLzR4zDxJMyUNcP06+XsCnmyxGn+eHPN3Se+ddIzzBN5usRp5rhhjAiS9KGm2tfYCSYmSal2P4VyBt1usxv+7coukdq7j8ZJmGWOiXbdxrsDb1Ul6yFo7RNJYSXONMUMlPSLpY2vtAEkfu76W67bbJV2g+vPhP8YYf9f34nxBiyH4QZtmrV0r6fBJhwdJWuv6/CNJN7nuu8Vam+c6vktSsDGmnTGmp6SO1toNtn5Rq+cl3dDiwwOt5FzOE0kyxtwgKU3158mxY5wn8HrneK5cLWm7tXab67GHrLUOzhX4gnM8V6ykDq6wNERSjaQSzhX4AmttvrU22fV5qaQUSb0lXS9pietuS/TVn/3rJb1sra221qZL2i9pDOcLWhrBDzzRTknfdH1+i6Q+p7jPTZK2WGurVf+Xb06D23JcxwBvdsrzxBjTQdJPJf3mpPtznsBXne7flIGSrDHmA2NMsjHmJ67jnCvwVac7V5ZLKpeULylL0l+ttYfFuQIf47rSbaSkLyR1t9bmS/XhkKRurrv1lpTd4GHHzgvOF7Qogh94ovtVfxllkqQw1b+zdJwx5gJJf5Y069ihU3wPtrODtzvdefIbSX+31paddH/OE/iq050rAZIulXSX6+ONxpgrxLkC33W6c2WMJIekXpJiJD1kjIkV5wp8iDEmVNLrkn5grS05011Pccye4TjQLALcPQBwrqy1e1R/Cb6MMQMlTT12mzEmSvW983ustamuwzmSohp8iyhJeQK82BnOk4sl3WyM+T9JnSQ5jTFVqn+xwnkCn3OGcyVH0hprbZHrtncljVL9uj+cK/A5ZzhX7pT0vrW2VlKBMWa9pARJ68S5Ah9gjAlU/euopdbaFa7DB40xPa21+a4aV4HreI5ObCscOy/4eQUtiit+4HGMMd1cH/0kPSZpvuvrTpJWSfqZtXb9sfu7Lq8sNcaMda2Of4+kt1p7bqA1ne48sdZOsNZGW2ujJf1D0h+stU9ynsBXne5ckfSBpIuMMe1da5dMkrSbcwW+6gznSpaky029Dqpf4HYP5wp8gevP9iJJKdbaJxrctFL1m83I9fGtBsdvd61DGqP6RZw3cr6gpRH8oE0zxrwkaYOkQcaYHGPMdEl3GGO+lLRH9Un4c667Pyipv6RfGGO2un4d69POUf1uFPslperruxkBHuscz5Mz4TyBVzuXc8Vae0TSE5I2SdoqKdlau8r1rThX4NXO8d+VpySFqn4NoE2SnrPWbnfdxrkCbzde0t2qDz+P/fwxRdKfJF1ljNkn6SrX17LW7pL0qqTdkt6XNNda63B9L84XtBhTv2g4AAAAAAAAvA1X/AAAAAAAAHgpgh8AAAAAAAAvRfADAAAAAADgpQh+AAAAAAAAvBTBDwAAAAAAgJci+AEAAGjAGPNrY8yP3T0HAABAcyD4AQAAAAAA8FIEPwAAwOcZYx41xuw1xvxX0iDXsThjzPvGmCRjzDpjzGA3jwkAAHDOAtw9AAAAgDsZY+Il3S5ppOpfGyVLSpK0UNJsa+0+Y8zFkv4j6XK3DQoAAHAeCH4AAICvmyDpDWtthSQZY1ZKCpY0TtJrxphj92vnnvEAAADOH8EPAACAZE/62k/SUWvtCDfMAgAA0GxY4wcAAPi6tZJuNMaEGGPCJH1DUoWkdGPMLZJk6g1355AAAADng+AHAAD4NGttsqRXJG2V9Lqkda6b7pI03RizTdIuSde7ZUAAAIAmMNaefGUzAAAAAAAAvAFX/AAAAAAAAHgpgh8AAAAAAAAvRfADAAAAAADgpQh+AAAAAAAAvBTBDwAAAAAAgJci+AEAAAAAAPBSBD8AAAAAAABeiuAHAAAAAADAS/0/cWEjERSg4nIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "e = d[d.character==\"Hamlet\"]\n",
    "plt.figure(figsize=(20,5))\n",
    "e.groupby(\"de\").character.count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7b84010",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "644160ca",
   "metadata": {},
   "source": [
    "What are the 11 most common character names in movie history?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "51793920",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Himself                   19486\n",
       "Dancer                    11995\n",
       "Extra                     10887\n",
       "Reporter                   8127\n",
       "Doctor                     7402\n",
       "                          ...  \n",
       "Bar Car Beauty                1\n",
       "Karen Tyler                   1\n",
       "Marjorie Knight               1\n",
       "Selina Dawes                  1\n",
       "Afgr.dama ? bens?nst??        1\n",
       "Name: character, Length: 1535711, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r = d.character.value_counts()\n",
    "r.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "12277c4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Himself        19486\n",
       "Dancer         11995\n",
       "Extra          10887\n",
       "Reporter        8127\n",
       "Doctor          7402\n",
       "Student         7146\n",
       "Policeman       6855\n",
       "Party Guest     6718\n",
       "Nurse           6637\n",
       "Bartender       6583\n",
       "Minor Role      6219\n",
       "Name: character, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.head(11)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "970b564d",
   "metadata": {},
   "source": [
    "Who are the 10 people most often credited as \"Herself\" in film history?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "828fa95f",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "t=d[d.character==\"Herself\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "45d04e3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "t=t.name.value_counts(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "d5d74848",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Queen Elizabeth II    11\n",
       "Joyce Brothers         9\n",
       "Margaret Thatcher      7\n",
       "Mary Jo Pehl           7\n",
       "Hillary Clinton        6\n",
       "Joan Rivers            6\n",
       "Rekha                  5\n",
       "Marilyn Monroe         5\n",
       "Bunny Yeager           5\n",
       "Caroline Rhea          5\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a99fd308",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c6632bae",
   "metadata": {},
   "source": [
    "Who are the 10 people most often credited as \"Himself\" in film history?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "cb0dd064",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=d[d.character=='Himself']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ec073aa0",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=y.name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "2ebdb69f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Adolf Hitler             99\n",
       "Richard Nixon            45\n",
       "Ronald Reagan            39\n",
       "John F. Kennedy          33\n",
       "Winston Churchill        23\n",
       "Ron Jeremy               23\n",
       "George W. Bush           23\n",
       "Benito Mussolini         22\n",
       "Franklin D. Roosevelt    20\n",
       "Bill Clinton             20\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79e55deb",
   "metadata": {},
   "source": [
    "Which actors or actresses appeared in the most movies in the year 1945?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "c86e7282",
   "metadata": {},
   "outputs": [],
   "source": [
    "u = d[d.year==1945]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "b74e2a4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Emmett Vogan         39\n",
       "Sam (II) Harris      32\n",
       "Bess Flowers         29\n",
       "Harold Miller        29\n",
       "Nolan Leary          27\n",
       "                     ..\n",
       "Thomas Murray         1\n",
       "Lee Murray            1\n",
       "Maurice Murphy        1\n",
       "Larry (XI) Murphy     1\n",
       "Chuy Reyes            1\n",
       "Name: name, Length: 7780, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "u.name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "acce6e64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Emmett Vogan'"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'Emmett Vogan'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "353fc9a0",
   "metadata": {},
   "source": [
    "Which actors or actresses appeared in the most movies in the year 1985?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "e9d3a9fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "i = d[d.year==1985]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "892936fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Shakti Kapoor         21\n",
       "Mammootty             21\n",
       "Sukumari              19\n",
       "Raj Babbar            15\n",
       "Mohanlal              15\n",
       "                      ..\n",
       "Xin (II) Liu           1\n",
       "Wen-Pin Liu            1\n",
       "Te-Kai Liu             1\n",
       "Kai Chi Liu            1\n",
       "Dalla ??r?ard?ttir     1\n",
       "Name: name, Length: 22558, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i.name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ebd86160",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Shakti Kapoor'"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "'Shakti Kapoor'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc6bceaf",
   "metadata": {},
   "source": [
    "Plot how many roles Mammootty has played in each year of his career."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "d385e964",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1367407</th>\n",
       "      <td>1993 Bombay March 12</td>\n",
       "      <td>2011</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Sathananda Bhatt</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367408</th>\n",
       "      <td>1993 Bombay March 12</td>\n",
       "      <td>2011</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Samir</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367409</th>\n",
       "      <td>Aa Neram Alppa Dooram</td>\n",
       "      <td>1985</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Jameskutty</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367410</th>\n",
       "      <td>Aa Rathri</td>\n",
       "      <td>1983</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Ravi</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367411</th>\n",
       "      <td>Aalkkoottathil Thaniye</td>\n",
       "      <td>1984</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Rajan</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1980</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>1367675</th>\n",
       "      <td>Vivekananda</td>\n",
       "      <td>1994</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Maharajah</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367676</th>\n",
       "      <td>White</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Prakash Roy</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367677</th>\n",
       "      <td>Yaathra</td>\n",
       "      <td>1985</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Unnikrishnan</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367678</th>\n",
       "      <td>Yavanika</td>\n",
       "      <td>1982</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>Jacob Eeraly (Sub Inspector of Police)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367679</th>\n",
       "      <td>Yugapurushan</td>\n",
       "      <td>2010</td>\n",
       "      <td>Mammootty</td>\n",
       "      <td>actor</td>\n",
       "      <td>K.C. Kuttan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>273 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          title  year       name   type  \\\n",
       "1367407    1993 Bombay March 12  2011  Mammootty  actor   \n",
       "1367408    1993 Bombay March 12  2011  Mammootty  actor   \n",
       "1367409   Aa Neram Alppa Dooram  1985  Mammootty  actor   \n",
       "1367410               Aa Rathri  1983  Mammootty  actor   \n",
       "1367411  Aalkkoottathil Thaniye  1984  Mammootty  actor   \n",
       "...                         ...   ...        ...    ...   \n",
       "1367675             Vivekananda  1994  Mammootty  actor   \n",
       "1367676                   White  2016  Mammootty  actor   \n",
       "1367677                 Yaathra  1985  Mammootty  actor   \n",
       "1367678                Yavanika  1982  Mammootty  actor   \n",
       "1367679            Yugapurushan  2010  Mammootty  actor   \n",
       "\n",
       "                                      character  rank    de  \n",
       "1367407                        Sathananda Bhatt   1.0  2010  \n",
       "1367408                                   Samir   1.0  2010  \n",
       "1367409                              Jameskutty   1.0  1980  \n",
       "1367410                                    Ravi   1.0  1980  \n",
       "1367411                                   Rajan   1.0  1980  \n",
       "...                                         ...   ...   ...  \n",
       "1367675                               Maharajah   0.0  1990  \n",
       "1367676                             Prakash Roy   1.0  2010  \n",
       "1367677                            Unnikrishnan   1.0  1980  \n",
       "1367678  Jacob Eeraly (Sub Inspector of Police)   7.0  1980  \n",
       "1367679                             K.C. Kuttan   0.0  2010  \n",
       "\n",
       "[273 rows x 7 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "o = d[d.name==\"Mammootty\"]\n",
    "o"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "4a36d3f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='year'>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "o.groupby('year').character.count().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f31b8865",
   "metadata": {},
   "source": [
    "What are the 10 most frequent roles that start with the phrase \"Patron in\"?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "65a8b7e7",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20478</th>\n",
       "      <td>Let It Ride</td>\n",
       "      <td>1989</td>\n",
       "      <td>Ralph Ahn</td>\n",
       "      <td>actor</td>\n",
       "      <td>Patron in Chinese Restaurant</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23605</th>\n",
       "      <td>Alex Cross</td>\n",
       "      <td>2012</td>\n",
       "      <td>Anthony Akins</td>\n",
       "      <td>actor</td>\n",
       "      <td>Patron in restaurant</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25129</th>\n",
       "      <td>Missing Pieces</td>\n",
       "      <td>2012</td>\n",
       "      <td>Rico Alago</td>\n",
       "      <td>actor</td>\n",
       "      <td>Patron in Restaurant</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29954</th>\n",
       "      <td>The Black Bird</td>\n",
       "      <td>1975</td>\n",
       "      <td>John Alderman</td>\n",
       "      <td>actor</td>\n",
       "      <td>Patron in Ballroom</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32123</th>\n",
       "      <td>Sparkle</td>\n",
       "      <td>2012</td>\n",
       "      <td>Eligah Alexander Jr.</td>\n",
       "      <td>actor</td>\n",
       "      <td>Patron in Audience</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</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>3272663</th>\n",
       "      <td>Above Suspicion</td>\n",
       "      <td>1943</td>\n",
       "      <td>Nita Pike</td>\n",
       "      <td>actress</td>\n",
       "      <td>Patron in Frisky Rabbit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3279767</th>\n",
       "      <td>Crashing</td>\n",
       "      <td>2007</td>\n",
       "      <td>Sachi Pollard</td>\n",
       "      <td>actress</td>\n",
       "      <td>Patron in the Coffee House</td>\n",
       "      <td>56.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3491000</th>\n",
       "      <td>Crashing</td>\n",
       "      <td>2007</td>\n",
       "      <td>Talia Tinari</td>\n",
       "      <td>actress</td>\n",
       "      <td>Patron in the Coffee House</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3492660</th>\n",
       "      <td>Breaking the Press</td>\n",
       "      <td>2010</td>\n",
       "      <td>Michelle Toche</td>\n",
       "      <td>actress</td>\n",
       "      <td>Patron in restaurant</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3507174</th>\n",
       "      <td>Let It Ride</td>\n",
       "      <td>1989</td>\n",
       "      <td>Myra Turley</td>\n",
       "      <td>actress</td>\n",
       "      <td>Patron in Chinese Restaurant</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>83 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      title  year                  name     type  \\\n",
       "20478           Let It Ride  1989             Ralph Ahn    actor   \n",
       "23605            Alex Cross  2012         Anthony Akins    actor   \n",
       "25129        Missing Pieces  2012            Rico Alago    actor   \n",
       "29954        The Black Bird  1975         John Alderman    actor   \n",
       "32123               Sparkle  2012  Eligah Alexander Jr.    actor   \n",
       "...                     ...   ...                   ...      ...   \n",
       "3272663     Above Suspicion  1943             Nita Pike  actress   \n",
       "3279767            Crashing  2007         Sachi Pollard  actress   \n",
       "3491000            Crashing  2007          Talia Tinari  actress   \n",
       "3492660  Breaking the Press  2010        Michelle Toche  actress   \n",
       "3507174         Let It Ride  1989           Myra Turley  actress   \n",
       "\n",
       "                            character  rank    de  \n",
       "20478    Patron in Chinese Restaurant  43.0  1980  \n",
       "23605            Patron in restaurant   0.0  2010  \n",
       "25129            Patron in Restaurant   0.0  2010  \n",
       "29954              Patron in Ballroom   0.0  1970  \n",
       "32123              Patron in Audience   0.0  2010  \n",
       "...                               ...   ...   ...  \n",
       "3272663       Patron in Frisky Rabbit   0.0  1940  \n",
       "3279767    Patron in the Coffee House  56.0  2000  \n",
       "3491000    Patron in the Coffee House  57.0  2000  \n",
       "3492660          Patron in restaurant   0.0  2010  \n",
       "3507174  Patron in Chinese Restaurant  37.0  1980  \n",
       "\n",
       "[83 rows x 7 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p=d[d.character.str.startswith(\"Patron in\")]\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "1d212676",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "character\n",
       "Patron in Art Gallery              1\n",
       "Patron in Audience                 2\n",
       "Patron in Ballroom                 1\n",
       "Patron in Bar                      4\n",
       "Patron in Billiard Parlor          5\n",
       "Patron in Black                    1\n",
       "Patron in Bookstore                1\n",
       "Patron in Cafe                     1\n",
       "Patron in Children's Nightclub     1\n",
       "Patron in Chinese Restaurant       9\n",
       "Patron in Cinema                   1\n",
       "Patron in Club                     3\n",
       "Patron in Coffee Shop              2\n",
       "Patron in Diner                    1\n",
       "Patron in Frisky Rabbit           16\n",
       "Patron in Hall #1                  1\n",
       "Patron in Hooly's                  1\n",
       "Patron in Macy's Lunchroom         1\n",
       "Patron in Night Club               1\n",
       "Patron in Pizza Place              1\n",
       "Patron in Pool Hall                1\n",
       "Patron in Quiet Bar                2\n",
       "Patron in Restaurant               3\n",
       "Patron in Store                    1\n",
       "Patron in Strip Club               1\n",
       "Patron in airport                  1\n",
       "Patron in booth                    2\n",
       "Patron in cabaret                  3\n",
       "Patron in restaurant               4\n",
       "Patron in the Coffee House         9\n",
       "Patron in the bar                  1\n",
       "Patron in video store              1\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p=p.groupby('character').year.count()\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "f23d89e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "p=p.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "8faa9055",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "character\n",
       "Patron in Frisky Rabbit         16\n",
       "Patron in Chinese Restaurant     9\n",
       "Patron in the Coffee House       9\n",
       "Patron in Billiard Parlor        5\n",
       "Patron in Bar                    4\n",
       "Patron in restaurant             4\n",
       "Patron in Club                   3\n",
       "Patron in Restaurant             3\n",
       "Patron in cabaret                3\n",
       "Patron in Audience               2\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cf96a24",
   "metadata": {},
   "source": [
    "What are the 10 most frequent roles that start with the word \"Science\"?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "d822d97b",
   "metadata": {},
   "outputs": [],
   "source": [
    "d1['character']=d1[\"character\"].str.title()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "12bb47d5",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11689</th>\n",
       "      <td>Teen Wolf Too</td>\n",
       "      <td>1987</td>\n",
       "      <td>Matthew T. Adams</td>\n",
       "      <td>actor</td>\n",
       "      <td>Science Student</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32070</th>\n",
       "      <td>Three O'Clock High</td>\n",
       "      <td>1987</td>\n",
       "      <td>Michael Alex</td>\n",
       "      <td>actor</td>\n",
       "      <td>Science Kid</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86861</th>\n",
       "      <td>Mutant Chronicles</td>\n",
       "      <td>2008</td>\n",
       "      <td>Roger Ashton-Griffiths</td>\n",
       "      <td>actor</td>\n",
       "      <td>Science Monk</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134394</th>\n",
       "      <td>The Giggles</td>\n",
       "      <td>2013</td>\n",
       "      <td>Kevin Barnstein</td>\n",
       "      <td>actor</td>\n",
       "      <td>Science Performer 3</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137589</th>\n",
       "      <td>Wilt</td>\n",
       "      <td>1990</td>\n",
       "      <td>Ian Barritt</td>\n",
       "      <td>actor</td>\n",
       "      <td>Science Teacher</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1990</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>3456787</th>\n",
       "      <td>October Sky</td>\n",
       "      <td>1999</td>\n",
       "      <td>Science Fair Student</td>\n",
       "      <td>actress</td>\n",
       "      <td>Science Fair Competition</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3501125</th>\n",
       "      <td>Hamlet A.D.D.</td>\n",
       "      <td>2014</td>\n",
       "      <td>Emily Treolo</td>\n",
       "      <td>actress</td>\n",
       "      <td>Science Officer</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3539194</th>\n",
       "      <td>A Meteorite for the Mantlepiece</td>\n",
       "      <td>2009</td>\n",
       "      <td>Natasha von Lenski</td>\n",
       "      <td>actress</td>\n",
       "      <td>Science Lover</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3553033</th>\n",
       "      <td>The End</td>\n",
       "      <td>2007</td>\n",
       "      <td>Randi Warwick</td>\n",
       "      <td>actress</td>\n",
       "      <td>Science Assistant</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3561739</th>\n",
       "      <td>EMO the Musical</td>\n",
       "      <td>2016</td>\n",
       "      <td>Marie Werrett</td>\n",
       "      <td>actress</td>\n",
       "      <td>Science Teacher</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>179 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   title  year                    name  \\\n",
       "11689                      Teen Wolf Too  1987        Matthew T. Adams   \n",
       "32070                 Three O'Clock High  1987            Michael Alex   \n",
       "86861                  Mutant Chronicles  2008  Roger Ashton-Griffiths   \n",
       "134394                       The Giggles  2013         Kevin Barnstein   \n",
       "137589                              Wilt  1990             Ian Barritt   \n",
       "...                                  ...   ...                     ...   \n",
       "3456787                      October Sky  1999    Science Fair Student   \n",
       "3501125                    Hamlet A.D.D.  2014            Emily Treolo   \n",
       "3539194  A Meteorite for the Mantlepiece  2009      Natasha von Lenski   \n",
       "3553033                          The End  2007           Randi Warwick   \n",
       "3561739                  EMO the Musical  2016           Marie Werrett   \n",
       "\n",
       "            type                 character  rank    de  \n",
       "11689      actor           Science Student   0.0  1980  \n",
       "32070      actor               Science Kid  25.0  1980  \n",
       "86861      actor              Science Monk  13.0  2000  \n",
       "134394     actor       Science Performer 3  19.0  2010  \n",
       "137589     actor           Science Teacher  22.0  1990  \n",
       "...          ...                       ...   ...   ...  \n",
       "3456787  actress  Science Fair Competition   0.0  1990  \n",
       "3501125  actress           Science Officer   0.0  2010  \n",
       "3539194  actress             Science Lover   0.0  2000  \n",
       "3553033  actress         Science Assistant   0.0  2000  \n",
       "3561739  actress           Science Teacher   0.0  2010  \n",
       "\n",
       "[179 rows x 7 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = d1[d1.character.str.startswith(\"Science\")]\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "3f172644",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "a=a.character.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "4198e1eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Science Teacher         63\n",
       "Science Student          9\n",
       "Science Fair Student     9\n",
       "Science Fair Judge       6\n",
       "Science Kid              6\n",
       "Science Club Member      5\n",
       "Science Promo Cadet      5\n",
       "Science Reporter         5\n",
       "Science                  4\n",
       "Science Officer          3\n",
       "Name: character, dtype: int64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "a.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0510ed9b",
   "metadata": {},
   "source": [
    "Plot the n-values of the roles that Judi Dench has played over her career."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "2ba1eb71",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2703455</th>\n",
       "      <td>84 Charing Cross Road</td>\n",
       "      <td>1987</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Nora Doel</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703456</th>\n",
       "      <td>A Handful of Dust</td>\n",
       "      <td>1988</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Mrs. Beaver</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703457</th>\n",
       "      <td>A Midsummer Night's Dream</td>\n",
       "      <td>1968</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Titania</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703458</th>\n",
       "      <td>A Room with a View</td>\n",
       "      <td>1985</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Eleanor Lavish, a novelist</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703459</th>\n",
       "      <td>A Study in Terror</td>\n",
       "      <td>1965</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Sally</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703460</th>\n",
       "      <td>Angelina Ballerina: Angelina Sets Sail</td>\n",
       "      <td>2006</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Miss Lilly</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703461</th>\n",
       "      <td>Casino Royale</td>\n",
       "      <td>2006</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703462</th>\n",
       "      <td>Chocolat</td>\n",
       "      <td>2000</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Armande Voizin</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703463</th>\n",
       "      <td>Dead Cert</td>\n",
       "      <td>1974</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Laura Davidson</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703464</th>\n",
       "      <td>Die Another Day</td>\n",
       "      <td>2002</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703465</th>\n",
       "      <td>Doogal</td>\n",
       "      <td>2006</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Narrator</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703466</th>\n",
       "      <td>Four in the Morning</td>\n",
       "      <td>1965</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Wife</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703467</th>\n",
       "      <td>GoldenEye</td>\n",
       "      <td>1995</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703468</th>\n",
       "      <td>Hamlet</td>\n",
       "      <td>1996</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Hecuba</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703469</th>\n",
       "      <td>He Who Rides a Tiger</td>\n",
       "      <td>1965</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Joanne</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703470</th>\n",
       "      <td>Henry V</td>\n",
       "      <td>1989</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Mistress Nell Quickly</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703471</th>\n",
       "      <td>Home on the Range</td>\n",
       "      <td>2004</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Mrs. Caloway</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703472</th>\n",
       "      <td>Iris</td>\n",
       "      <td>2001</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Iris Murdoch</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703473</th>\n",
       "      <td>J. Edgar</td>\n",
       "      <td>2011</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Annie Hoover</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703474</th>\n",
       "      <td>Jack &amp; Sarah</td>\n",
       "      <td>1995</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Margaret</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703475</th>\n",
       "      <td>Jane Eyre</td>\n",
       "      <td>2011</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Mrs. Fairfax</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703476</th>\n",
       "      <td>Kenneth Branagh Theatre Company's the Winter's...</td>\n",
       "      <td>2015</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Paulina</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703477</th>\n",
       "      <td>Ladies in Lavender</td>\n",
       "      <td>2004</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Ursula</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703478</th>\n",
       "      <td>Luther</td>\n",
       "      <td>1974</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Katherine</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703479</th>\n",
       "      <td>Miss Peregrine's Home for Peculiar Children</td>\n",
       "      <td>2016</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Miss Avocet</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703480</th>\n",
       "      <td>Mrs Brown</td>\n",
       "      <td>1997</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Queen Victoria</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703481</th>\n",
       "      <td>Mrs Henderson Presents</td>\n",
       "      <td>2005</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Mrs. Laura Henderson</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703482</th>\n",
       "      <td>Murder on the Orient Express</td>\n",
       "      <td>2017</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Princess Dragomiroff</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703483</th>\n",
       "      <td>My Week with Marilyn</td>\n",
       "      <td>2011</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Dame Sybil Thorndike</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703484</th>\n",
       "      <td>Nine</td>\n",
       "      <td>2009</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Lilli</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703485</th>\n",
       "      <td>Notes on a Scandal</td>\n",
       "      <td>2006</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Barbara Covett</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703486</th>\n",
       "      <td>Philomena</td>\n",
       "      <td>2013</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Philomena</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703487</th>\n",
       "      <td>Pirates of the Caribbean: On Stranger Tides</td>\n",
       "      <td>2011</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Society Lady</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703488</th>\n",
       "      <td>Pride &amp; Prejudice</td>\n",
       "      <td>2005</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Lady Catherine de Bourg</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703489</th>\n",
       "      <td>Quantum of Solace</td>\n",
       "      <td>2008</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703490</th>\n",
       "      <td>Rage</td>\n",
       "      <td>2009</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Mona Carvell</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703491</th>\n",
       "      <td>Run for Your Wife</td>\n",
       "      <td>2012</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Bag Lady</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703492</th>\n",
       "      <td>Schadenfreude</td>\n",
       "      <td>2016</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>The Narrator</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703493</th>\n",
       "      <td>Shakespeare in Love</td>\n",
       "      <td>1998</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Queen Elizabeth</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703494</th>\n",
       "      <td>Skyfall</td>\n",
       "      <td>2012</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703495</th>\n",
       "      <td>Spectre</td>\n",
       "      <td>2015</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703496</th>\n",
       "      <td>Stars in Shorts</td>\n",
       "      <td>2012</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Mary</td>\n",
       "      <td>29.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703497</th>\n",
       "      <td>Tea with Mussolini</td>\n",
       "      <td>1999</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Arabella</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703498</th>\n",
       "      <td>The Angelic Conversation</td>\n",
       "      <td>1985</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Shakespeare's Sonnets read by</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703499</th>\n",
       "      <td>The Best Exotic Marigold Hotel</td>\n",
       "      <td>2011</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Evelyn Greenslade</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703500</th>\n",
       "      <td>The Chronicles of Riddick</td>\n",
       "      <td>2004</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Aereon</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703501</th>\n",
       "      <td>The Importance of Being Earnest</td>\n",
       "      <td>2002</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Lady Bracknell</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703502</th>\n",
       "      <td>The Second Best Exotic Marigold Hotel</td>\n",
       "      <td>2015</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Evelyn Greenslade</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703503</th>\n",
       "      <td>The Shipping News</td>\n",
       "      <td>2001</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Agnis Hamm</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703504</th>\n",
       "      <td>The Third Secret</td>\n",
       "      <td>1964</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Miss Humphries</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703505</th>\n",
       "      <td>The World Is Not Enough</td>\n",
       "      <td>1999</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703506</th>\n",
       "      <td>Tomorrow Never Dies</td>\n",
       "      <td>1997</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>M</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703507</th>\n",
       "      <td>Tulip Fever</td>\n",
       "      <td>2017</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>The Abbess of St. Ursula</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703508</th>\n",
       "      <td>Victoria and Abdul</td>\n",
       "      <td>2017</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Queen Victoria</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703509</th>\n",
       "      <td>Wetherby</td>\n",
       "      <td>1985</td>\n",
       "      <td>Judi Dench</td>\n",
       "      <td>actress</td>\n",
       "      <td>Marcia Pilborough</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                     title  year        name  \\\n",
       "2703455                              84 Charing Cross Road  1987  Judi Dench   \n",
       "2703456                                  A Handful of Dust  1988  Judi Dench   \n",
       "2703457                          A Midsummer Night's Dream  1968  Judi Dench   \n",
       "2703458                                 A Room with a View  1985  Judi Dench   \n",
       "2703459                                  A Study in Terror  1965  Judi Dench   \n",
       "2703460             Angelina Ballerina: Angelina Sets Sail  2006  Judi Dench   \n",
       "2703461                                      Casino Royale  2006  Judi Dench   \n",
       "2703462                                           Chocolat  2000  Judi Dench   \n",
       "2703463                                          Dead Cert  1974  Judi Dench   \n",
       "2703464                                    Die Another Day  2002  Judi Dench   \n",
       "2703465                                             Doogal  2006  Judi Dench   \n",
       "2703466                                Four in the Morning  1965  Judi Dench   \n",
       "2703467                                          GoldenEye  1995  Judi Dench   \n",
       "2703468                                             Hamlet  1996  Judi Dench   \n",
       "2703469                               He Who Rides a Tiger  1965  Judi Dench   \n",
       "2703470                                            Henry V  1989  Judi Dench   \n",
       "2703471                                  Home on the Range  2004  Judi Dench   \n",
       "2703472                                               Iris  2001  Judi Dench   \n",
       "2703473                                           J. Edgar  2011  Judi Dench   \n",
       "2703474                                       Jack & Sarah  1995  Judi Dench   \n",
       "2703475                                          Jane Eyre  2011  Judi Dench   \n",
       "2703476  Kenneth Branagh Theatre Company's the Winter's...  2015  Judi Dench   \n",
       "2703477                                 Ladies in Lavender  2004  Judi Dench   \n",
       "2703478                                             Luther  1974  Judi Dench   \n",
       "2703479        Miss Peregrine's Home for Peculiar Children  2016  Judi Dench   \n",
       "2703480                                          Mrs Brown  1997  Judi Dench   \n",
       "2703481                             Mrs Henderson Presents  2005  Judi Dench   \n",
       "2703482                       Murder on the Orient Express  2017  Judi Dench   \n",
       "2703483                               My Week with Marilyn  2011  Judi Dench   \n",
       "2703484                                               Nine  2009  Judi Dench   \n",
       "2703485                                 Notes on a Scandal  2006  Judi Dench   \n",
       "2703486                                          Philomena  2013  Judi Dench   \n",
       "2703487        Pirates of the Caribbean: On Stranger Tides  2011  Judi Dench   \n",
       "2703488                                  Pride & Prejudice  2005  Judi Dench   \n",
       "2703489                                  Quantum of Solace  2008  Judi Dench   \n",
       "2703490                                               Rage  2009  Judi Dench   \n",
       "2703491                                  Run for Your Wife  2012  Judi Dench   \n",
       "2703492                                      Schadenfreude  2016  Judi Dench   \n",
       "2703493                                Shakespeare in Love  1998  Judi Dench   \n",
       "2703494                                            Skyfall  2012  Judi Dench   \n",
       "2703495                                            Spectre  2015  Judi Dench   \n",
       "2703496                                    Stars in Shorts  2012  Judi Dench   \n",
       "2703497                                 Tea with Mussolini  1999  Judi Dench   \n",
       "2703498                           The Angelic Conversation  1985  Judi Dench   \n",
       "2703499                     The Best Exotic Marigold Hotel  2011  Judi Dench   \n",
       "2703500                          The Chronicles of Riddick  2004  Judi Dench   \n",
       "2703501                    The Importance of Being Earnest  2002  Judi Dench   \n",
       "2703502              The Second Best Exotic Marigold Hotel  2015  Judi Dench   \n",
       "2703503                                  The Shipping News  2001  Judi Dench   \n",
       "2703504                                   The Third Secret  1964  Judi Dench   \n",
       "2703505                            The World Is Not Enough  1999  Judi Dench   \n",
       "2703506                                Tomorrow Never Dies  1997  Judi Dench   \n",
       "2703507                                        Tulip Fever  2017  Judi Dench   \n",
       "2703508                                 Victoria and Abdul  2017  Judi Dench   \n",
       "2703509                                           Wetherby  1985  Judi Dench   \n",
       "\n",
       "            type                      character  rank    de  \n",
       "2703455  actress                      Nora Doel   3.0  1980  \n",
       "2703456  actress                    Mrs. Beaver  13.0  1980  \n",
       "2703457  actress                        Titania  16.0  1960  \n",
       "2703458  actress     Eleanor Lavish, a novelist   7.0  1980  \n",
       "2703459  actress                          Sally   8.0  1960  \n",
       "2703460  actress                     Miss Lilly   2.0  2000  \n",
       "2703461  actress                              M   4.0  2000  \n",
       "2703462  actress                 Armande Voizin  18.0  2000  \n",
       "2703463  actress                 Laura Davidson   2.0  1970  \n",
       "2703464  actress                              M   6.0  2000  \n",
       "2703465  actress                       Narrator   7.0  2000  \n",
       "2703466  actress                           Wife   2.0  1960  \n",
       "2703467  actress                              M   6.0  1990  \n",
       "2703468  actress                         Hecuba  12.0  1990  \n",
       "2703469  actress                         Joanne   2.0  1960  \n",
       "2703470  actress          Mistress Nell Quickly  26.0  1980  \n",
       "2703471  actress                   Mrs. Caloway   7.0  2000  \n",
       "2703472  actress                   Iris Murdoch   3.0  2000  \n",
       "2703473  actress                   Annie Hoover  13.0  2010  \n",
       "2703474  actress                       Margaret   3.0  1990  \n",
       "2703475  actress                   Mrs. Fairfax  18.0  2010  \n",
       "2703476  actress                        Paulina   0.0  2010  \n",
       "2703477  actress                         Ursula   1.0  2000  \n",
       "2703478  actress                      Katherine   7.0  1970  \n",
       "2703479  actress                    Miss Avocet   4.0  2010  \n",
       "2703480  actress                 Queen Victoria   1.0  1990  \n",
       "2703481  actress           Mrs. Laura Henderson   1.0  2000  \n",
       "2703482  actress           Princess Dragomiroff   0.0  2010  \n",
       "2703483  actress           Dame Sybil Thorndike  23.0  2010  \n",
       "2703484  actress                          Lilli   6.0  2000  \n",
       "2703485  actress                 Barbara Covett   1.0  2000  \n",
       "2703486  actress                      Philomena   1.0  2010  \n",
       "2703487  actress                   Society Lady  16.0  2010  \n",
       "2703488  actress        Lady Catherine de Bourg  20.0  2000  \n",
       "2703489  actress                              M   4.0  2000  \n",
       "2703490  actress                   Mona Carvell   0.0  2000  \n",
       "2703491  actress                       Bag Lady  40.0  2010  \n",
       "2703492  actress                   The Narrator   0.0  2010  \n",
       "2703493  actress                Queen Elizabeth  12.0  1990  \n",
       "2703494  actress                              M   2.0  2010  \n",
       "2703495  actress                              M   0.0  2010  \n",
       "2703496  actress                           Mary  29.0  2010  \n",
       "2703497  actress                       Arabella   2.0  1990  \n",
       "2703498  actress  Shakespeare's Sonnets read by   3.0  1980  \n",
       "2703499  actress              Evelyn Greenslade   1.0  2010  \n",
       "2703500  actress                         Aereon   4.0  2000  \n",
       "2703501  actress                 Lady Bracknell   5.0  2000  \n",
       "2703502  actress              Evelyn Greenslade   5.0  2010  \n",
       "2703503  actress                     Agnis Hamm   3.0  2000  \n",
       "2703504  actress                 Miss Humphries  12.0  1960  \n",
       "2703505  actress                              M   6.0  1990  \n",
       "2703506  actress                              M   9.0  1990  \n",
       "2703507  actress       The Abbess of St. Ursula   0.0  2010  \n",
       "2703508  actress                 Queen Victoria   0.0  2010  \n",
       "2703509  actress              Marcia Pilborough   3.0  1980  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = d[d.name==\"Judi Dench\"]\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "e07f6468",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='character'>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "s.groupby(\"character\")['rank'].count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9ebc8669",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "c72cff14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='year'>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "s.groupby(\"year\")['rank'].count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "485a2bd9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "9d991c51",
   "metadata": {},
   "source": [
    "Plot the n-values of Cary Grant's roles through his career."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "22857279",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>840334</th>\n",
       "      <td>Alice in Wonderland</td>\n",
       "      <td>1933</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Mock Turtle</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840335</th>\n",
       "      <td>An Affair to Remember</td>\n",
       "      <td>1957</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Nickie Ferrante</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840336</th>\n",
       "      <td>Arsenic and Old Lace</td>\n",
       "      <td>1944</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Mortimer Brewster</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840337</th>\n",
       "      <td>Big Brown Eyes</td>\n",
       "      <td>1936</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Danny Barr</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840338</th>\n",
       "      <td>Blonde Venus</td>\n",
       "      <td>1932</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Nick Townsend</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1930</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>840411</th>\n",
       "      <td>Walk Don't Run</td>\n",
       "      <td>1966</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Sir William Rutland</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840412</th>\n",
       "      <td>Wedding Present</td>\n",
       "      <td>1936</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Charlie Mason</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840413</th>\n",
       "      <td>When You're in Love</td>\n",
       "      <td>1937</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Jimmy Hudson</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840414</th>\n",
       "      <td>Wings in the Dark</td>\n",
       "      <td>1935</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Ken Gordon</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840415</th>\n",
       "      <td>Without Reservations</td>\n",
       "      <td>1946</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>actor</td>\n",
       "      <td>Cary Grant</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1940</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        title  year        name   type            character  \\\n",
       "840334    Alice in Wonderland  1933  Cary Grant  actor          Mock Turtle   \n",
       "840335  An Affair to Remember  1957  Cary Grant  actor      Nickie Ferrante   \n",
       "840336   Arsenic and Old Lace  1944  Cary Grant  actor    Mortimer Brewster   \n",
       "840337         Big Brown Eyes  1936  Cary Grant  actor           Danny Barr   \n",
       "840338           Blonde Venus  1932  Cary Grant  actor        Nick Townsend   \n",
       "...                       ...   ...         ...    ...                  ...   \n",
       "840411         Walk Don't Run  1966  Cary Grant  actor  Sir William Rutland   \n",
       "840412        Wedding Present  1936  Cary Grant  actor        Charlie Mason   \n",
       "840413    When You're in Love  1937  Cary Grant  actor         Jimmy Hudson   \n",
       "840414      Wings in the Dark  1935  Cary Grant  actor           Ken Gordon   \n",
       "840415   Without Reservations  1946  Cary Grant  actor           Cary Grant   \n",
       "\n",
       "        rank    de  \n",
       "840334  10.0  1930  \n",
       "840335   1.0  1950  \n",
       "840336   1.0  1940  \n",
       "840337   1.0  1930  \n",
       "840338   3.0  1930  \n",
       "...      ...   ...  \n",
       "840411   1.0  1960  \n",
       "840412   2.0  1930  \n",
       "840413   2.0  1930  \n",
       "840414   2.0  1930  \n",
       "840415   0.0  1940  \n",
       "\n",
       "[82 rows x 7 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f =d[d.name==\"Cary Grant\"] \n",
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "28e248dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='character'>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "f.groupby(\"character\")['rank'].count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb1eae00",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "cd19c099",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='year'>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "f.groupby(\"year\")['rank'].count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "337b6783",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2b97bff0",
   "metadata": {},
   "source": [
    "Plot the n-value of the roles that Sidney Poitier has acted over the years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "f77d568b",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1751059</th>\n",
       "      <td>A Patch of Blue</td>\n",
       "      <td>1965</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Gordon Ralfe</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751060</th>\n",
       "      <td>A Piece of the Action</td>\n",
       "      <td>1977</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Manny Durrell</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751061</th>\n",
       "      <td>A Raisin in the Sun</td>\n",
       "      <td>1961</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Walter Lee Younger</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751062</th>\n",
       "      <td>A Warm December</td>\n",
       "      <td>1973</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Dr. Matt Younger</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751063</th>\n",
       "      <td>All the Young Men</td>\n",
       "      <td>1960</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Sgt. Eddie Towler</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751064</th>\n",
       "      <td>Band of Angels</td>\n",
       "      <td>1957</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Rau-Ru</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751065</th>\n",
       "      <td>Blackboard Jungle</td>\n",
       "      <td>1955</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Gregory W. Miller</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751066</th>\n",
       "      <td>Brother John</td>\n",
       "      <td>1971</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>John Kane</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751067</th>\n",
       "      <td>Buck and the Preacher</td>\n",
       "      <td>1972</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Buck</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751068</th>\n",
       "      <td>Cry, the Beloved Country</td>\n",
       "      <td>1951</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Reverend Msimangu</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751069</th>\n",
       "      <td>Duel at Diablo</td>\n",
       "      <td>1966</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Toller</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751070</th>\n",
       "      <td>Edge of the City</td>\n",
       "      <td>1957</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Tommy Tyler</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751071</th>\n",
       "      <td>For Love of Ivy</td>\n",
       "      <td>1968</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Jack Parks</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751072</th>\n",
       "      <td>Go Man Go</td>\n",
       "      <td>1954</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Inman Jackson</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751073</th>\n",
       "      <td>Good-bye, My Lady</td>\n",
       "      <td>1956</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Gates Watson</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751074</th>\n",
       "      <td>Guess Who's Coming to Dinner</td>\n",
       "      <td>1967</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>John Prentice</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751075</th>\n",
       "      <td>In the Heat of the Night</td>\n",
       "      <td>1967</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Virgil Tibbs</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751076</th>\n",
       "      <td>Let's Do It Again</td>\n",
       "      <td>1975</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Clyde Williams</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751077</th>\n",
       "      <td>Lilies of the Field</td>\n",
       "      <td>1963</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Homer Smith</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751078</th>\n",
       "      <td>Little Nikita</td>\n",
       "      <td>1988</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Roy Parmenter</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751079</th>\n",
       "      <td>No Way Out</td>\n",
       "      <td>1950</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Dr. Luther Brooks</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751080</th>\n",
       "      <td>Paris Blues</td>\n",
       "      <td>1961</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Eddie Cook</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751081</th>\n",
       "      <td>Porgy and Bess</td>\n",
       "      <td>1959</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Porgy</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751082</th>\n",
       "      <td>Pressure Point</td>\n",
       "      <td>1962</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Doctor</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751083</th>\n",
       "      <td>Red Ball Express</td>\n",
       "      <td>1952</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Robertson</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751084</th>\n",
       "      <td>Sepia Cinderella</td>\n",
       "      <td>1947</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Night Club Extra</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751085</th>\n",
       "      <td>Shoot to Kill</td>\n",
       "      <td>1988</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Warren Stantin</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751086</th>\n",
       "      <td>Sneakers</td>\n",
       "      <td>1992</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Donald Crease</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751087</th>\n",
       "      <td>Something of Value</td>\n",
       "      <td>1957</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Kimani Wa Karanja</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751088</th>\n",
       "      <td>The Bedford Incident</td>\n",
       "      <td>1965</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Ben Munceford</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751089</th>\n",
       "      <td>The Defiant Ones</td>\n",
       "      <td>1958</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Noah Cullen</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751090</th>\n",
       "      <td>The Greatest Story Ever Told</td>\n",
       "      <td>1965</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Simon of Cyrene</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751091</th>\n",
       "      <td>The Jackal</td>\n",
       "      <td>1997</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>FBI Deputy Director Carter Preston</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751092</th>\n",
       "      <td>The Long Ships</td>\n",
       "      <td>1964</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Aly Mansuh</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751093</th>\n",
       "      <td>The Lost Man</td>\n",
       "      <td>1969</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Jason Higgs</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751094</th>\n",
       "      <td>The Mark of the Hawk</td>\n",
       "      <td>1957</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Obam</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751095</th>\n",
       "      <td>The Organization</td>\n",
       "      <td>1971</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Virgil Tibbs</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751096</th>\n",
       "      <td>The Slender Thread</td>\n",
       "      <td>1965</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Alan Newell</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751097</th>\n",
       "      <td>The Wilby Conspiracy</td>\n",
       "      <td>1975</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Shack Twala</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751098</th>\n",
       "      <td>They Call Me Mister Tibbs!</td>\n",
       "      <td>1970</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Virgil Tibbs</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751099</th>\n",
       "      <td>To Sir, with Love</td>\n",
       "      <td>1967</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Mark Thackeray</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751100</th>\n",
       "      <td>Uptown Saturday Night</td>\n",
       "      <td>1974</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Steve Jackson</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1751101</th>\n",
       "      <td>Virgin Island</td>\n",
       "      <td>1958</td>\n",
       "      <td>Sidney Poitier</td>\n",
       "      <td>actor</td>\n",
       "      <td>Marcus</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                title  year            name   type  \\\n",
       "1751059               A Patch of Blue  1965  Sidney Poitier  actor   \n",
       "1751060         A Piece of the Action  1977  Sidney Poitier  actor   \n",
       "1751061           A Raisin in the Sun  1961  Sidney Poitier  actor   \n",
       "1751062               A Warm December  1973  Sidney Poitier  actor   \n",
       "1751063             All the Young Men  1960  Sidney Poitier  actor   \n",
       "1751064                Band of Angels  1957  Sidney Poitier  actor   \n",
       "1751065             Blackboard Jungle  1955  Sidney Poitier  actor   \n",
       "1751066                  Brother John  1971  Sidney Poitier  actor   \n",
       "1751067         Buck and the Preacher  1972  Sidney Poitier  actor   \n",
       "1751068      Cry, the Beloved Country  1951  Sidney Poitier  actor   \n",
       "1751069                Duel at Diablo  1966  Sidney Poitier  actor   \n",
       "1751070              Edge of the City  1957  Sidney Poitier  actor   \n",
       "1751071               For Love of Ivy  1968  Sidney Poitier  actor   \n",
       "1751072                     Go Man Go  1954  Sidney Poitier  actor   \n",
       "1751073             Good-bye, My Lady  1956  Sidney Poitier  actor   \n",
       "1751074  Guess Who's Coming to Dinner  1967  Sidney Poitier  actor   \n",
       "1751075      In the Heat of the Night  1967  Sidney Poitier  actor   \n",
       "1751076             Let's Do It Again  1975  Sidney Poitier  actor   \n",
       "1751077           Lilies of the Field  1963  Sidney Poitier  actor   \n",
       "1751078                 Little Nikita  1988  Sidney Poitier  actor   \n",
       "1751079                    No Way Out  1950  Sidney Poitier  actor   \n",
       "1751080                   Paris Blues  1961  Sidney Poitier  actor   \n",
       "1751081                Porgy and Bess  1959  Sidney Poitier  actor   \n",
       "1751082                Pressure Point  1962  Sidney Poitier  actor   \n",
       "1751083              Red Ball Express  1952  Sidney Poitier  actor   \n",
       "1751084              Sepia Cinderella  1947  Sidney Poitier  actor   \n",
       "1751085                 Shoot to Kill  1988  Sidney Poitier  actor   \n",
       "1751086                      Sneakers  1992  Sidney Poitier  actor   \n",
       "1751087            Something of Value  1957  Sidney Poitier  actor   \n",
       "1751088          The Bedford Incident  1965  Sidney Poitier  actor   \n",
       "1751089              The Defiant Ones  1958  Sidney Poitier  actor   \n",
       "1751090  The Greatest Story Ever Told  1965  Sidney Poitier  actor   \n",
       "1751091                    The Jackal  1997  Sidney Poitier  actor   \n",
       "1751092                The Long Ships  1964  Sidney Poitier  actor   \n",
       "1751093                  The Lost Man  1969  Sidney Poitier  actor   \n",
       "1751094          The Mark of the Hawk  1957  Sidney Poitier  actor   \n",
       "1751095              The Organization  1971  Sidney Poitier  actor   \n",
       "1751096            The Slender Thread  1965  Sidney Poitier  actor   \n",
       "1751097          The Wilby Conspiracy  1975  Sidney Poitier  actor   \n",
       "1751098    They Call Me Mister Tibbs!  1970  Sidney Poitier  actor   \n",
       "1751099             To Sir, with Love  1967  Sidney Poitier  actor   \n",
       "1751100         Uptown Saturday Night  1974  Sidney Poitier  actor   \n",
       "1751101                 Virgin Island  1958  Sidney Poitier  actor   \n",
       "\n",
       "                                  character  rank    de  \n",
       "1751059                        Gordon Ralfe   1.0  1960  \n",
       "1751060                       Manny Durrell   1.0  1970  \n",
       "1751061                  Walter Lee Younger   1.0  1960  \n",
       "1751062                    Dr. Matt Younger   1.0  1970  \n",
       "1751063                   Sgt. Eddie Towler   2.0  1960  \n",
       "1751064                              Rau-Ru   3.0  1950  \n",
       "1751065                   Gregory W. Miller  10.0  1950  \n",
       "1751066                           John Kane   1.0  1970  \n",
       "1751067                                Buck   1.0  1970  \n",
       "1751068                   Reverend Msimangu   3.0  1950  \n",
       "1751069                              Toller   2.0  1960  \n",
       "1751070                         Tommy Tyler   2.0  1950  \n",
       "1751071                          Jack Parks   1.0  1960  \n",
       "1751072                       Inman Jackson   3.0  1950  \n",
       "1751073                        Gates Watson   4.0  1950  \n",
       "1751074                       John Prentice   2.0  1960  \n",
       "1751075                        Virgil Tibbs   1.0  1960  \n",
       "1751076                      Clyde Williams   1.0  1970  \n",
       "1751077                         Homer Smith   1.0  1960  \n",
       "1751078                       Roy Parmenter   1.0  1980  \n",
       "1751079                   Dr. Luther Brooks   4.0  1950  \n",
       "1751080                          Eddie Cook   3.0  1960  \n",
       "1751081                               Porgy   1.0  1950  \n",
       "1751082                              Doctor   1.0  1960  \n",
       "1751083                           Robertson   5.0  1950  \n",
       "1751084                    Night Club Extra   0.0  1940  \n",
       "1751085                      Warren Stantin   1.0  1980  \n",
       "1751086                       Donald Crease   4.0  1990  \n",
       "1751087                   Kimani Wa Karanja  13.0  1950  \n",
       "1751088                       Ben Munceford   2.0  1960  \n",
       "1751089                         Noah Cullen   2.0  1950  \n",
       "1751090                     Simon of Cyrene  21.0  1960  \n",
       "1751091  FBI Deputy Director Carter Preston   3.0  1990  \n",
       "1751092                          Aly Mansuh   2.0  1960  \n",
       "1751093                         Jason Higgs   1.0  1960  \n",
       "1751094                                Obam   2.0  1950  \n",
       "1751095                        Virgil Tibbs   1.0  1970  \n",
       "1751096                         Alan Newell   1.0  1960  \n",
       "1751097                         Shack Twala   1.0  1970  \n",
       "1751098                        Virgil Tibbs   1.0  1970  \n",
       "1751099                      Mark Thackeray   1.0  1960  \n",
       "1751100                       Steve Jackson   1.0  1970  \n",
       "1751101                              Marcus   3.0  1950  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = d[d.name==\"Sidney Poitier\"]\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "56ddae45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='character'>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(20,10))\n",
    "g.groupby(\"character\")['rank'].count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "329d53ca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "492802c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='year'>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "g.groupby(\"year\")['rank'].count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfea9351",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "9334586a",
   "metadata": {},
   "source": [
    "How many leading (n=1) roles were available to actors, and how many to actresses, in the 1950s?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "3c786b27",
   "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>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>rank</th>\n",
       "      <th>de</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Live Freaky Die Freaky</td>\n",
       "      <td>2006</td>\n",
       "      <td>Nick 13</td>\n",
       "      <td>actor</td>\n",
       "      <td>TV Reporter #1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>All Things Fall Apart</td>\n",
       "      <td>2011</td>\n",
       "      <td>50 Cent</td>\n",
       "      <td>actor</td>\n",
       "      <td>Deon</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>Freelancers</td>\n",
       "      <td>2012</td>\n",
       "      <td>50 Cent</td>\n",
       "      <td>actor</td>\n",
       "      <td>Malo</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Get Rich or Die Tryin'</td>\n",
       "      <td>2005</td>\n",
       "      <td>50 Cent</td>\n",
       "      <td>actor</td>\n",
       "      <td>Marcus</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Gun</td>\n",
       "      <td>2010</td>\n",
       "      <td>50 Cent</td>\n",
       "      <td>actor</td>\n",
       "      <td>Rich</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</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>3610999</th>\n",
       "      <td>Doyumsuz</td>\n",
       "      <td>1990</td>\n",
       "      <td>Bahar ?ztan</td>\n",
       "      <td>actress</td>\n",
       "      <td>Bahar</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611010</th>\n",
       "      <td>Kadife</td>\n",
       "      <td>2012</td>\n",
       "      <td>Ayta? ?ztuna</td>\n",
       "      <td>actress</td>\n",
       "      <td>Kadife Ana</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611053</th>\n",
       "      <td>Dig og mig</td>\n",
       "      <td>2008</td>\n",
       "      <td>Julie R. ?lgaard</td>\n",
       "      <td>actress</td>\n",
       "      <td>Stephanie</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611073</th>\n",
       "      <td>Mimi og madammerne</td>\n",
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       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611080</th>\n",
       "      <td>Ved vejen</td>\n",
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       "      <td>Tammi ?st</td>\n",
       "      <td>actress</td>\n",
       "      <td>Katinka</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>147045 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          title  year              name     type  \\\n",
       "102      Live Freaky Die Freaky  2006           Nick 13    actor   \n",
       "137       All Things Fall Apart  2011           50 Cent    actor   \n",
       "142                 Freelancers  2012           50 Cent    actor   \n",
       "143      Get Rich or Die Tryin'  2005           50 Cent    actor   \n",
       "144                         Gun  2010           50 Cent    actor   \n",
       "...                         ...   ...               ...      ...   \n",
       "3610999                Doyumsuz  1990       Bahar ?ztan  actress   \n",
       "3611010                  Kadife  2012      Ayta? ?ztuna  actress   \n",
       "3611053              Dig og mig  2008  Julie R. ?lgaard  actress   \n",
       "3611073      Mimi og madammerne  1998         Tammi ?st  actress   \n",
       "3611080               Ved vejen  1988         Tammi ?st  actress   \n",
       "\n",
       "              character  rank    de  \n",
       "102      TV Reporter #1   1.0  2000  \n",
       "137                Deon   1.0  2010  \n",
       "142                Malo   1.0  2010  \n",
       "143              Marcus   1.0  2000  \n",
       "144                Rich   1.0  2010  \n",
       "...                 ...   ...   ...  \n",
       "3610999           Bahar   1.0  1990  \n",
       "3611010      Kadife Ana   1.0  2010  \n",
       "3611053       Stephanie   1.0  2000  \n",
       "3611073            Mimi   1.0  1990  \n",
       "3611080         Katinka   1.0  1980  \n",
       "\n",
       "[147045 rows x 7 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h = d[d['rank']==1]\n",
    "h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "06ed0a26",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Abbott and Costello Meet Dr. Jekyll and Mr. Hyde</td>\n",
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       "    <tr>\n",
       "      <th>3608812</th>\n",
       "      <td>Marianela</td>\n",
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      "text/plain": [
       "                                                    title  year  \\\n",
       "1630                                    Bir qalanin sirri  1959   \n",
       "1873                       Abbott and Costello Go to Mars  1953   \n",
       "1874            Abbott and Costello in the Foreign Legion  1950   \n",
       "1875                Abbott and Costello Meet Captain Kidd  1952   \n",
       "1876     Abbott and Costello Meet Dr. Jekyll and Mr. Hyde  1953   \n",
       "...                                                   ...   ...   \n",
       "3606779                    Mit siebzehn beginnt das Leben  1953   \n",
       "3608805                                  El vampiro negro  1953   \n",
       "3608806                                  El vampiro negro  1953   \n",
       "3608812                                         Marianela  1955   \n",
       "3608813                                         Valentina  1950   \n",
       "\n",
       "                    name     type                  character  rank    de  \n",
       "1630     Gyunduz Abbasov    actor                      Elsan   1.0  1950  \n",
       "1873          Bud Abbott    actor                     Lester   1.0  1950  \n",
       "1874          Bud Abbott    actor                  Bud Jones   1.0  1950  \n",
       "1875          Bud Abbott    actor          Rocky Stonebridge   1.0  1950  \n",
       "1876          Bud Abbott    actor                       Slim   1.0  1950  \n",
       "...                  ...      ...                        ...   ...   ...  \n",
       "3606779    Sonja Ziemann  actress            Madelien de Jeu   1.0  1950  \n",
       "3608805     Olga Zubarry  actress                     Amalia   1.0  1950  \n",
       "3608806     Olga Zubarry  actress                       Rita   1.0  1950  \n",
       "3608812     Olga Zubarry  actress                  Marianela   1.0  1950  \n",
       "3608813     Olga Zubarry  actress  Valentina Gonz?lez Garc?a   1.0  1950  \n",
       "\n",
       "[9552 rows x 7 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
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    }
   ],
   "source": [
    "h1 = h[h['de']==1950]\n",
    "h1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "44303421",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "actor      6599\n",
       "actress    2953\n",
       "Name: type, dtype: int64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h1.type.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0730c40e",
   "metadata": {},
   "source": [
    "How many supporting (n=2) roles were available to actors, and how many to actresses, in the 1950s?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "67ef9a86",
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   "outputs": [
    {
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      "text/plain": [
       "                               title  year           name     type  \\\n",
       "98                         Big Apple  2002    Angel 11:11    actor   \n",
       "122              Asad wa arbaa qutat  2007         4 Cats    actor   \n",
       "243      The Return of Flutter Green  2017      Sergey A.    actor   \n",
       "262                             Suli  2016  Pragathi A.S.    actor   \n",
       "308                       Sarrainodu  2016          Aadhi    actor   \n",
       "...                              ...   ...            ...      ...   \n",
       "3611146                     Kavgamiz  1989       Nil ?nal  actress   \n",
       "3611147               Sevimli Hirsiz  1988       Nil ?nal  actress   \n",
       "3611156                Das Geheimnis  1995      Idil ?ner  actress   \n",
       "3611157                       Dealer  1999      Idil ?ner  actress   \n",
       "3611163              Urban Guerillas  2004      Idil ?ner  actress   \n",
       "\n",
       "              character  rank    de  \n",
       "98                Angel   2.0  2000  \n",
       "122          Themselves   2.0  2000  \n",
       "243            Demichev   2.0  2010  \n",
       "262             Shabana   2.0  2010  \n",
       "308      Vairam Dhanush   2.0  2010  \n",
       "...                 ...   ...   ...  \n",
       "3611146          Cemile   2.0  1980  \n",
       "3611147           Selma   2.0  1980  \n",
       "3611156           Sarah   2.0  1990  \n",
       "3611157            Jale   2.0  1990  \n",
       "3611163          Madlen   2.0  2000  \n",
       "\n",
       "[137561 rows x 7 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
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    }
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   "source": [
    "j = d[d['rank']==2]\n",
    "j"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "a4514ae7",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Mono gia mia nyhta</td>\n",
       "      <td>1958</td>\n",
       "      <td>Voula Zouboulaki</td>\n",
       "      <td>actress</td>\n",
       "      <td>Anna</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3608803</th>\n",
       "      <td>El honorable inquilino</td>\n",
       "      <td>1951</td>\n",
       "      <td>Olga Zubarry</td>\n",
       "      <td>actress</td>\n",
       "      <td>Ana Mar?a</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3610130</th>\n",
       "      <td>El puma</td>\n",
       "      <td>1959</td>\n",
       "      <td>Sof?a ?lvarez</td>\n",
       "      <td>actress</td>\n",
       "      <td>Norte?a</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3611137</th>\n",
       "      <td>Akdeniz korsanlari</td>\n",
       "      <td>1950</td>\n",
       "      <td>Muazzez ?lkerer</td>\n",
       "      <td>actress</td>\n",
       "      <td>Maria</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9094 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     title  year                 name  \\\n",
       "1123                          Bashi-Achuki  1956       Dodo Abashidze   \n",
       "2135                     The Invisible Boy  1957        Philip Abbott   \n",
       "7072                  A los cuatro vientos  1955  Miguel Aceves Mej?a   \n",
       "7077                          Cuatro copas  1958  Miguel Aceves Mej?a   \n",
       "9875                    Private's Progress  1956          Ronald Adam   \n",
       "...                                    ...   ...                  ...   \n",
       "3608657  Karagiozis, o adikimenos tis zois  1959     Voula Zouboulaki   \n",
       "3608658                 Mono gia mia nyhta  1958     Voula Zouboulaki   \n",
       "3608803             El honorable inquilino  1951         Olga Zubarry   \n",
       "3610130                            El puma  1959        Sof?a ?lvarez   \n",
       "3611137                 Akdeniz korsanlari  1950      Muazzez ?lkerer   \n",
       "\n",
       "            type          character  rank    de  \n",
       "1123       actor       Abdoushahili   2.0  1950  \n",
       "2135       actor   Dr. Tom Merrinoe   2.0  1950  \n",
       "7072       actor       Pablo G?lvez   2.0  1950  \n",
       "7077       actor             Miguel   2.0  1950  \n",
       "9875       actor  Doctor at Medical   2.0  1950  \n",
       "...          ...                ...   ...   ...  \n",
       "3608657  actress             Marika   2.0  1950  \n",
       "3608658  actress               Anna   2.0  1950  \n",
       "3608803  actress          Ana Mar?a   2.0  1950  \n",
       "3610130  actress            Norte?a   2.0  1950  \n",
       "3611137  actress              Maria   2.0  1950  \n",
       "\n",
       "[9094 rows x 7 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "j1 = j[j['de']==1950]\n",
    "j1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "d786b3f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "actor      4550\n",
       "actress    4544\n",
       "Name: type, dtype: int64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "j1.type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d1bfbba",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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