data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Аналитика базы данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Выгрузим предварительно технически предобработанные базы данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_df = pd.read_csv(\"reviews_data_base_clean.csv\")\n",
    "clean_df_company = pd.read_csv(\"rgs_reviews_data_base_clean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_df = clean_df.drop('Unnamed: 0', 1)\n",
    "clean_df_company = clean_df_company.drop('Unnamed: 0', 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Анализ показателей"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1. Общая статистика по рынку"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Опишем статистику по рынку:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>12085.000000</td>\n",
       "      <td>12085.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.906744</td>\n",
       "      <td>-0.191725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.720255</td>\n",
       "      <td>0.981489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               mark         class\n",
       "count  12085.000000  12085.000000\n",
       "mean       2.906744     -0.191725\n",
       "std        1.720255      0.981489\n",
       "min        1.000000     -1.000000\n",
       "25%        1.000000     -1.000000\n",
       "50%        3.000000     -1.000000\n",
       "75%        5.000000      1.000000\n",
       "max        5.000000      1.000000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "И по компании:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1471.000000</td>\n",
       "      <td>1471.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.486064</td>\n",
       "      <td>-0.853161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.064410</td>\n",
       "      <td>0.521825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "              mark        class\n",
       "count  1471.000000  1471.000000\n",
       "mean      1.486064    -0.853161\n",
       "std       1.064410     0.521825\n",
       "min       1.000000    -1.000000\n",
       "25%       1.000000    -1.000000\n",
       "50%       1.000000    -1.000000\n",
       "75%       1.000000    -1.000000\n",
       "max       5.000000     1.000000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df_company.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вывод:** Из данных видим, что несмотря на то, что в целом люди больше склонны оставлять негативные отзывы на услуги, разница между рынком и компанией сильная. Компания сильно отстаёт от рынка по удовлетворенности клиентов на данном сайте."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2. Средняя оценка в разрезе продукта\n",
    "Для начала рассмотрим, отзывы по скольким уникальным продуктам представлены на сайте:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Количество уникальных продуктов на рынке, на которые оставили отзывы:  14\n",
      "Количество уникальных продуктов компании, на которые оставили отзывы:  10\n"
     ]
    }
   ],
   "source": [
    "unique_arr = clean_df[\"product\"].unique()\n",
    "unique_arr_company = clean_df_company[\"product\"].unique()\n",
    "\n",
    "print(\"Количество уникальных продуктов на рынке, на которые оставили отзывы: \", unique_arr.size)\n",
    "print(\"Количество уникальных продуктов компании, на которые оставили отзывы: \", unique_arr_company.size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Теперь рассмотрим среднюю оценку в разрезе продукта для рынка:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ДМС</th>\n",
       "      <td>2.516224</td>\n",
       "      <td>-0.392330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Другое</th>\n",
       "      <td>3.222672</td>\n",
       "      <td>-0.068826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Инвестиционное страхование</th>\n",
       "      <td>2.988327</td>\n",
       "      <td>-0.182879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Каско</th>\n",
       "      <td>3.101999</td>\n",
       "      <td>-0.042729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ОСАГО</th>\n",
       "      <td>2.795063</td>\n",
       "      <td>-0.282188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Обслуживание</th>\n",
       "      <td>2.382647</td>\n",
       "      <td>-0.359288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Пенсионное страхование</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование для бизнеса</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование жизни</th>\n",
       "      <td>3.237774</td>\n",
       "      <td>-0.048904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование имущества и недвижимости</th>\n",
       "      <td>3.304082</td>\n",
       "      <td>-0.004082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ипотеки</th>\n",
       "      <td>4.105263</td>\n",
       "      <td>0.263158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ответственности</th>\n",
       "      <td>3.550000</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование финансовых рисков</th>\n",
       "      <td>2.311111</td>\n",
       "      <td>-0.644444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Туристическая страховка</th>\n",
       "      <td>3.113636</td>\n",
       "      <td>-0.074675</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          mark     class\n",
       "product                                                 \n",
       "ДМС                                   2.516224 -0.392330\n",
       "Другое                                3.222672 -0.068826\n",
       "Инвестиционное страхование            2.988327 -0.182879\n",
       "Каско                                 3.101999 -0.042729\n",
       "ОСАГО                                 2.795063 -0.282188\n",
       "Обслуживание                          2.382647 -0.359288\n",
       "Пенсионное страхование                5.000000  1.000000\n",
       "Страхование для бизнеса               5.000000  1.000000\n",
       "Страхование жизни                     3.237774 -0.048904\n",
       "Страхование имущества и недвижимости  3.304082 -0.004082\n",
       "Страхование ипотеки                   4.105263  0.263158\n",
       "Страхование ответственности           3.550000  0.200000\n",
       "Страхование финансовых рисков         2.311111 -0.644444\n",
       "Туристическая страховка               3.113636 -0.074675"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df.groupby('product').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "И для компании:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ДМС</th>\n",
       "      <td>1.487179</td>\n",
       "      <td>-0.794872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Другое</th>\n",
       "      <td>2.071429</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Инвестиционное страхование</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Каско</th>\n",
       "      <td>1.649682</td>\n",
       "      <td>-0.757962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ОСАГО</th>\n",
       "      <td>1.467197</td>\n",
       "      <td>-0.866799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Обслуживание</th>\n",
       "      <td>1.275862</td>\n",
       "      <td>-0.891626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование жизни</th>\n",
       "      <td>2.166667</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование имущества и недвижимости</th>\n",
       "      <td>1.857143</td>\n",
       "      <td>-0.785714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ответственности</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Туристическая страховка</th>\n",
       "      <td>2.125000</td>\n",
       "      <td>-0.625000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          mark     class\n",
       "product                                                 \n",
       "ДМС                                   1.487179 -0.794872\n",
       "Другое                                2.071429 -1.000000\n",
       "Инвестиционное страхование            5.000000  1.000000\n",
       "Каско                                 1.649682 -0.757962\n",
       "ОСАГО                                 1.467197 -0.866799\n",
       "Обслуживание                          1.275862 -0.891626\n",
       "Страхование жизни                     2.166667 -1.000000\n",
       "Страхование имущества и недвижимости  1.857143 -0.785714\n",
       "Страхование ответственности           1.000000 -1.000000\n",
       "Туристическая страховка               2.125000 -0.625000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df_company.groupby('product').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Теперь выведем наглядную таблицу с разницей по совпадающим продуктам:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ДМС</th>\n",
       "      <td>-1.029045</td>\n",
       "      <td>-0.402541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Другое</th>\n",
       "      <td>-1.151243</td>\n",
       "      <td>-0.931174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Инвестиционное страхование</th>\n",
       "      <td>2.011673</td>\n",
       "      <td>1.182879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Каско</th>\n",
       "      <td>-1.452317</td>\n",
       "      <td>-0.715233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ОСАГО</th>\n",
       "      <td>-1.327866</td>\n",
       "      <td>-0.584611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Обслуживание</th>\n",
       "      <td>-1.106785</td>\n",
       "      <td>-0.532338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование жизни</th>\n",
       "      <td>-1.071107</td>\n",
       "      <td>-0.951096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование имущества и недвижимости</th>\n",
       "      <td>-1.446939</td>\n",
       "      <td>-0.781633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ответственности</th>\n",
       "      <td>-2.550000</td>\n",
       "      <td>-1.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Туристическая страховка</th>\n",
       "      <td>-0.988636</td>\n",
       "      <td>-0.550325</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          mark     class\n",
       "product                                                 \n",
       "ДМС                                  -1.029045 -0.402541\n",
       "Другое                               -1.151243 -0.931174\n",
       "Инвестиционное страхование            2.011673  1.182879\n",
       "Каско                                -1.452317 -0.715233\n",
       "ОСАГО                                -1.327866 -0.584611\n",
       "Обслуживание                         -1.106785 -0.532338\n",
       "Страхование жизни                    -1.071107 -0.951096\n",
       "Страхование имущества и недвижимости -1.446939 -0.781633\n",
       "Страхование ответственности          -2.550000 -1.200000\n",
       "Туристическая страховка              -0.988636 -0.550325"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(clean_df_company.groupby('product').mean() - clean_df.groupby('product').mean()).dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вывод:** Наблюдаем отставание по всем продуктам, за исключением Инвестиционного страхования. Причем отставание более чем 1 балл из 5 (то есть 20%)!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3. Медианная оценка в разрезе продукта\n",
    "Рынок:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ДМС</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Другое</th>\n",
       "      <td>3.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Инвестиционное страхование</th>\n",
       "      <td>3.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Каско</th>\n",
       "      <td>3.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ОСАГО</th>\n",
       "      <td>3.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Обслуживание</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Пенсионное страхование</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование для бизнеса</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование жизни</th>\n",
       "      <td>3.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование имущества и недвижимости</th>\n",
       "      <td>3.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ипотеки</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ответственности</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование финансовых рисков</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Туристическая страховка</th>\n",
       "      <td>3.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      mark  class\n",
       "product                                          \n",
       "ДМС                                    2.0   -1.0\n",
       "Другое                                 3.0   -1.0\n",
       "Инвестиционное страхование             3.0   -1.0\n",
       "Каско                                  3.0   -1.0\n",
       "ОСАГО                                  3.0   -1.0\n",
       "Обслуживание                           1.0   -1.0\n",
       "Пенсионное страхование                 5.0    1.0\n",
       "Страхование для бизнеса                5.0    1.0\n",
       "Страхование жизни                      3.0   -1.0\n",
       "Страхование имущества и недвижимости   3.0   -1.0\n",
       "Страхование ипотеки                    5.0    1.0\n",
       "Страхование ответственности            5.0    1.0\n",
       "Страхование финансовых рисков          2.0   -1.0\n",
       "Туристическая страховка                3.0   -1.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df.groupby('product').median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Компания:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ДМС</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Другое</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Инвестиционное страхование</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Каско</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ОСАГО</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Обслуживание</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование жизни</th>\n",
       "      <td>2.5</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование имущества и недвижимости</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ответственности</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Туристическая страховка</th>\n",
       "      <td>1.5</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      mark  class\n",
       "product                                          \n",
       "ДМС                                    1.0   -1.0\n",
       "Другое                                 2.0   -1.0\n",
       "Инвестиционное страхование             5.0    1.0\n",
       "Каско                                  1.0   -1.0\n",
       "ОСАГО                                  1.0   -1.0\n",
       "Обслуживание                           1.0   -1.0\n",
       "Страхование жизни                      2.5   -1.0\n",
       "Страхование имущества и недвижимости   1.0   -1.0\n",
       "Страхование ответственности            1.0   -1.0\n",
       "Туристическая страховка                1.5   -1.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df_company.groupby('product').median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ДМС</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Другое</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Инвестиционное страхование</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Каско</th>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ОСАГО</th>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Обслуживание</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование жизни</th>\n",
       "      <td>-0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование имущества и недвижимости</th>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Страхование ответственности</th>\n",
       "      <td>-4.0</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Туристическая страховка</th>\n",
       "      <td>-1.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      mark  class\n",
       "product                                          \n",
       "ДМС                                   -1.0    0.0\n",
       "Другое                                -1.0    0.0\n",
       "Инвестиционное страхование             2.0    2.0\n",
       "Каско                                 -2.0    0.0\n",
       "ОСАГО                                 -2.0    0.0\n",
       "Обслуживание                           0.0    0.0\n",
       "Страхование жизни                     -0.5    0.0\n",
       "Страхование имущества и недвижимости  -2.0    0.0\n",
       "Страхование ответственности           -4.0   -2.0\n",
       "Туристическая страховка               -1.5    0.0"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(clean_df_company.groupby('product').median() - clean_df.groupby('product').median()).dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вывод:** Результаты сопоставимы со средним. Единственная разница – оценка обслуживания. Здесь как по рынку, так и по компании одинаково плохие результаты – 1/5."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Оценка обслуживания выбивается из общей картины. \n",
    "Рассмотрим подробнее, насколько много отзывов по обслуживанию."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Рынок:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>899.000000</td>\n",
       "      <td>899.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.382647</td>\n",
       "      <td>-0.359288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.773465</td>\n",
       "      <td>0.933746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             mark       class\n",
       "count  899.000000  899.000000\n",
       "mean     2.382647   -0.359288\n",
       "std      1.773465    0.933746\n",
       "min      1.000000   -1.000000\n",
       "25%      1.000000   -1.000000\n",
       "50%      1.000000   -1.000000\n",
       "75%      5.000000    1.000000\n",
       "max      5.000000    1.000000"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df.loc[clean_df['product'] == \"Обслуживание\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Число отзывов по обслуживанию по рынку: 899\n",
      "Доля отзывов по обслуживанию по рынку: 7.44 %\n"
     ]
    }
   ],
   "source": [
    "print(\"Число отзывов по обслуживанию по рынку:\", sum(clean_df['product'] == \"Обслуживание\"))\n",
    "print(\"Доля отзывов по обслуживанию по рынку:\", round(sum(clean_df['product'] == \"Обслуживание\")/len(clean_df.index)*100, 2), \"%\" )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Компания: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mark</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>203.000000</td>\n",
       "      <td>203.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.275862</td>\n",
       "      <td>-0.891626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.913463</td>\n",
       "      <td>0.453893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             mark       class\n",
       "count  203.000000  203.000000\n",
       "mean     1.275862   -0.891626\n",
       "std      0.913463    0.453893\n",
       "min      1.000000   -1.000000\n",
       "25%      1.000000   -1.000000\n",
       "50%      1.000000   -1.000000\n",
       "75%      1.000000   -1.000000\n",
       "max      5.000000    1.000000"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df_company.loc[clean_df_company['product'] == \"Обслуживание\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Число отзывов по обслуживанию по компании: 203\n",
      "Доля отзывов по обслуживанию по компании: 13.8 %\n"
     ]
    }
   ],
   "source": [
    "print(\"Число отзывов по обслуживанию по компании:\", sum(clean_df_company['product'] == \"Обслуживание\"))\n",
    "print(\"Доля отзывов по обслуживанию по компании:\", round(sum(clean_df_company['product'] == \"Обслуживание\")/len(clean_df_company.index)*100, 2), \"%\" )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Хорошо, теперь нужно понять, много ли это. Распишем доли продуктов в рынке:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "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>product</th>\n",
       "      <th>market_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ОСАГО</td>\n",
       "      <td>0.466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Каско</td>\n",
       "      <td>0.240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Обслуживание</td>\n",
       "      <td>0.074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Туристическая страховка</td>\n",
       "      <td>0.051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Страхование жизни</td>\n",
       "      <td>0.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Страхование имущества и недвижимости</td>\n",
       "      <td>0.041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ДМС</td>\n",
       "      <td>0.028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Инвестиционное страхование</td>\n",
       "      <td>0.021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Другое</td>\n",
       "      <td>0.020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Страхование финансовых рисков</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Страхование ипотеки</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Страхование ответственности</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Страхование для бизнеса</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Пенсионное страхование</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 product  market_share\n",
       "2                                  ОСАГО         0.466\n",
       "0                                  Каско         0.240\n",
       "6                           Обслуживание         0.074\n",
       "11               Туристическая страховка         0.051\n",
       "3                      Страхование жизни         0.049\n",
       "7   Страхование имущества и недвижимости         0.041\n",
       "12                                   ДМС         0.028\n",
       "1             Инвестиционное страхование         0.021\n",
       "4                                 Другое         0.020\n",
       "10         Страхование финансовых рисков         0.004\n",
       "5                    Страхование ипотеки         0.003\n",
       "13           Страхование ответственности         0.002\n",
       "8                Страхование для бизнеса         0.000\n",
       "9                 Пенсионное страхование         0.000"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass = []\n",
    "for i in unique_arr:\n",
    "    mass.append(round(sum(clean_df['product'] == i)/len(clean_df.index), 3))\n",
    "    \n",
    "d = {\"product\" : unique_arr, \"market_share\":mass}\n",
    "df = pd.DataFrame(d)\n",
    "df.sort_values('market_share', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "И доли продуктов в компании:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>product</th>\n",
       "      <th>company_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ОСАГО</td>\n",
       "      <td>0.684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Обслуживание</td>\n",
       "      <td>0.138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Каско</td>\n",
       "      <td>0.107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ДМС</td>\n",
       "      <td>0.027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Страхование имущества и недвижимости</td>\n",
       "      <td>0.019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Туристическая страховка</td>\n",
       "      <td>0.011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Другое</td>\n",
       "      <td>0.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Страхование жизни</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Страхование ответственности</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Инвестиционное страхование</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                product  company_share\n",
       "0                                 ОСАГО          0.684\n",
       "7                          Обслуживание          0.138\n",
       "4                                 Каско          0.107\n",
       "9                                   ДМС          0.027\n",
       "2  Страхование имущества и недвижимости          0.019\n",
       "6               Туристическая страховка          0.011\n",
       "1                                Другое          0.010\n",
       "3                     Страхование жизни          0.004\n",
       "5           Страхование ответственности          0.001\n",
       "8            Инвестиционное страхование          0.001"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_company = []\n",
    "for i in unique_arr_company:\n",
    "    mass_company.append(round(sum(clean_df_company['product'] == i)/len(clean_df_company.index), 3))\n",
    "    \n",
    "d_company = {\"product\" : unique_arr_company, \"company_share\":mass_company}\n",
    "df_company = pd.DataFrame(d_company)\n",
    "df_company.sort_values('company_share', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "То есть в обоих случаях «Обслуживание» входит в топ-3 показателей по частоте оставления отзывов. Показатели и там, и там плохие. Можно выделить это как потенциально важная для клиента зона роста."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.4. Общая статистика: отрицательные и положительные отзывы. Рынок и компания."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>company</th>\n",
       "      <th>city</th>\n",
       "      <th>product</th>\n",
       "      <th>header</th>\n",
       "      <th>review</th>\n",
       "      <th>mark</th>\n",
       "      <th>date</th>\n",
       "      <th>link</th>\n",
       "      <th>full_review</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>-1.0</th>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "      <td>7201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "      <td>4884</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       company  city  product  header  review  mark  date  link  full_review\n",
       "class                                                                       \n",
       "-1.0      7201  7201     7201    7201    7201  7201  7201  7201         7201\n",
       " 1.0      4884  4884     4884    4884    4884  4884  4884  4884         4884"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df.groupby(\"class\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Доля негативных отзывов на рынке: 59.599999999999994 %\n",
      "Доля позитивных отзывов на рынке: 40.400000000000006 %\n"
     ]
    }
   ],
   "source": [
    "print(\"Доля негативных отзывов на рынке:\",round(sum(clean_df['class'] == -1.0)/len(clean_df.index),3)*100,\"%\")\n",
    "print(\"Доля позитивных отзывов на рынке:\",round(sum(clean_df['class'] == 1.0)/len(clean_df.index),3)*100,\"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>company</th>\n",
       "      <th>city</th>\n",
       "      <th>product</th>\n",
       "      <th>header</th>\n",
       "      <th>review</th>\n",
       "      <th>mark</th>\n",
       "      <th>date</th>\n",
       "      <th>link</th>\n",
       "      <th>full_review</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>-1.0</th>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "      <td>1363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       company  city  product  header  review  mark  date  link  full_review\n",
       "class                                                                       \n",
       "-1.0      1363  1363     1363    1363    1363  1363  1363  1363         1363\n",
       " 1.0       108   108      108     108     108   108   108   108          108"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df_company.groupby(\"class\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Доля негативных отзывов на рынке: 92.7 %\n",
      "Доля позитивных отзывов на рынке: 7.3 %\n"
     ]
    }
   ],
   "source": [
    "print(\"Доля негативных отзывов на рынке:\",round(sum(clean_df_company['class'] == -1.0)/len(clean_df_company.index),3)*100,\"%\")\n",
    "print(\"Доля позитивных отзывов на рынке:\",round(sum(clean_df_company['class'] == 1.0)/len(clean_df_company.index),3)*100,\"%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Вывод:** Как мы видим, ситуация на рынке сильно лучше, чем у компании. Такое количество негативных отзывов говорит о том, что надо срочно заняться вопросом удовлетворенности клиентов."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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