{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Основы программирования в Python\n",
    "*Алла Тамбовцева, НИУ ВШЭ*\n",
    "\n",
    "## Семинар 7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "На этом семинаре мы будем работать с известной [базой данных](http://campus.lakeforest.edu/frank/FILES/MLFfiles/Bio150/Titanic/TitanicMETA.pdf) по пассажирам \"Титаника\" (она часто используется в курсах по эконометрике и машинному обучению, но представляет не только статистической, но и содержательный интерес).\n",
    "\n",
    "*Переменные:*\n",
    "\n",
    "**PassengerId**  - id пассажира\n",
    "\n",
    "**Survived** - бинарный показатель, выжил пассажир или нет (1 - выжил, 0 - не выжил)\n",
    "\n",
    "**Pclass** - класс пассажира\n",
    "\n",
    "**Name** - имя пассажира \n",
    "\n",
    "**Sex**\t- пол пассажира\n",
    "\n",
    "**Age**\t- возраст пассажира\n",
    "\n",
    "**SibSp** - число родных братьев/сестер пассажира на борту корабля (или супругов) \n",
    "\n",
    "**Parch** - число родителей пассажира на борту корабля\t\n",
    "\n",
    "**Ticket**\t- номер билета\n",
    "\n",
    "**Fare** - стоимость билета\n",
    "\n",
    "**Cabin** - каюта\n",
    "\n",
    "**Embarked** - порт, в котором пассажир взошел на палубу корабля"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Загрузка и предварительная обработка"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Загрузите базу данных из файла `Titanic.csv`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/allatambov/Py-programming-3/master/28-05/Titanic.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Загрузите базу данных так из файла еще раз, но так, чтобы столбец PassengerId был идентификатором, то есть номером  строки (*index)*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "1                   0       3   \n",
       "2                   1       1   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "\n",
       "             SibSp  Parch     Ticket     Fare Cabin Embarked  \n",
       "PassengerId                                                   \n",
       "1                1      0  A/5 21171   7.2500   NaN        S  \n",
       "2                1      0   PC 17599  71.2833   C85        C  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/allatambov/Py-programming-3/master/28-05/Titanic.csv',\n",
    "                index_col = 0)\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Удалите из базы строки с пропущенными значениями и сохраните изменения в самой базе."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Описание базы данных"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выведите сводную информацию по базе данных: какие переменные в ней есть, какого они типа + сколько заполненных наблюдений в каждой столбце."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 183 entries, 2 to 890\n",
      "Data columns (total 11 columns):\n",
      "Survived    183 non-null int64\n",
      "Pclass      183 non-null int64\n",
      "Name        183 non-null object\n",
      "Sex         183 non-null object\n",
      "Age         183 non-null float64\n",
      "SibSp       183 non-null int64\n",
      "Parch       183 non-null int64\n",
      "Ticket      183 non-null object\n",
      "Fare        183 non-null float64\n",
      "Cabin       183 non-null object\n",
      "Embarked    183 non-null object\n",
      "dtypes: float64(2), int64(4), object(5)\n",
      "memory usage: 17.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выведите сводную статистическую информацию по каждому количественному показателю в базе (описательные статистике)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.672131</td>\n",
       "      <td>1.191257</td>\n",
       "      <td>35.674426</td>\n",
       "      <td>0.464481</td>\n",
       "      <td>0.475410</td>\n",
       "      <td>78.682469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.470725</td>\n",
       "      <td>0.515187</td>\n",
       "      <td>15.643866</td>\n",
       "      <td>0.644159</td>\n",
       "      <td>0.754617</td>\n",
       "      <td>76.347843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.920000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>47.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>90.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Survived      Pclass         Age       SibSp       Parch        Fare\n",
       "count  183.000000  183.000000  183.000000  183.000000  183.000000  183.000000\n",
       "mean     0.672131    1.191257   35.674426    0.464481    0.475410   78.682469\n",
       "std      0.470725    0.515187   15.643866    0.644159    0.754617   76.347843\n",
       "min      0.000000    1.000000    0.920000    0.000000    0.000000    0.000000\n",
       "25%      0.000000    1.000000   24.000000    0.000000    0.000000   29.700000\n",
       "50%      1.000000    1.000000   36.000000    0.000000    0.000000   57.000000\n",
       "75%      1.000000    1.000000   47.500000    1.000000    1.000000   90.000000\n",
       "max      1.000000    3.000000   80.000000    3.000000    4.000000  512.329200"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Постройте гистограмму для переменной *Возраст* (*Age*), сделайте ее красного цвета, подпишите оси и добавьте заголовок графика."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# импортируем библиотеку для графики\n",
    "import matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "% matplotlib inline\n",
    "\n",
    "# magic для того, чтобы график отображался прямо в ноутбуке ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f2ba3ae9978>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2ba3c23cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.Age.plot.hist(color = \"red\") # цвет red\n",
    "ax.set_title('Histogram for Age') # заголовок для объекта ax\n",
    "ax.set_xlabel('Age (in years)') # подпись для оси x\n",
    "ax.set_ylabel('number of passengers') # подпись для оси y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выведите описательные статистики для столбца *Стоимость билета* (*Fare*)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    183.000000\n",
       "mean      78.682469\n",
       "std       76.347843\n",
       "min        0.000000\n",
       "25%       29.700000\n",
       "50%       57.000000\n",
       "75%       90.000000\n",
       "max      512.329200\n",
       "Name: Fare, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Fare.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Работа со строками и столбцами базы"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выведите названия столбцов в базе данных в виде списка (объект типа *list*)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Survived',\n",
       " 'Pclass',\n",
       " 'Name',\n",
       " 'Sex',\n",
       " 'Age',\n",
       " 'SibSp',\n",
       " 'Parch',\n",
       " 'Ticket',\n",
       " 'Fare',\n",
       " 'Cabin',\n",
       " 'Embarked']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(df.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Переименуйте столбец с классом пассажира из **Pclass** в **Class**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Survived</th>\n",
       "      <th>Class</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Class  \\\n",
       "PassengerId                    \n",
       "2                   1      1   \n",
       "4                   1      1   \n",
       "7                   0      1   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "7                                      McCarthy, Mr. Timothy J    male  54.0   \n",
       "\n",
       "             SibSp  Parch    Ticket     Fare Cabin Embarked  \n",
       "PassengerId                                                  \n",
       "2                1      0  PC 17599  71.2833   C85        C  \n",
       "4                1      0    113803  53.1000  C123        S  \n",
       "7                0      0     17463  51.8625   E46        S  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = list(df.columns) # сохраним список\n",
    "cols[1] = 'Class' # изменим нужный элемент в списке\n",
    "df.columns = cols # поменяем столбцы в базе\n",
    "df.head(3) # первые 3 строки"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выберите из базы данных все строки, которые соответствуют пассажирам женского пола, и сохраните их в новую базу `female`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Survived</th>\n",
       "      <th>Class</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
       "      <td>female</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PP 9549</td>\n",
       "      <td>16.7000</td>\n",
       "      <td>G6</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Class  \\\n",
       "PassengerId                    \n",
       "2                   1      1   \n",
       "4                   1      1   \n",
       "11                  1      3   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "11                             Sandstrom, Miss. Marguerite Rut  female   4.0   \n",
       "\n",
       "             SibSp  Parch    Ticket     Fare Cabin Embarked  \n",
       "PassengerId                                                  \n",
       "2                1      0  PC 17599  71.2833   C85        C  \n",
       "4                1      0    113803  53.1000  C123        S  \n",
       "11               1      1   PP 9549  16.7000    G6        S  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "female = df[df.Sex == 'female'] # двойное =\n",
    "female.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выберите из базы данных все строки, которые соответствуют выжившим пассажирам мужского пола младше 32 лет, и сохраните их в базу `Ymale`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>Survived</th>\n",
       "      <th>Class</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sloper, Mr. William Thompson</td>\n",
       "      <td>male</td>\n",
       "      <td>28.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113788</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>A6</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Greenfield, Mr. William Bertram</td>\n",
       "      <td>male</td>\n",
       "      <td>23.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>PC 17759</td>\n",
       "      <td>63.3583</td>\n",
       "      <td>D10 D12</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Becker, Master. Richard F</td>\n",
       "      <td>male</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>230136</td>\n",
       "      <td>39.0000</td>\n",
       "      <td>F4</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Navratil, Master. Michel M</td>\n",
       "      <td>male</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>230080</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>F2</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Allison, Master. Hudson Trevor</td>\n",
       "      <td>male</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Class                             Name   Sex    Age  \\\n",
       "PassengerId                                                                  \n",
       "24                  1      1     Sloper, Mr. William Thompson  male  28.00   \n",
       "98                  1      1  Greenfield, Mr. William Bertram  male  23.00   \n",
       "184                 1      2        Becker, Master. Richard F  male   1.00   \n",
       "194                 1      2       Navratil, Master. Michel M  male   3.00   \n",
       "306                 1      1   Allison, Master. Hudson Trevor  male   0.92   \n",
       "\n",
       "             SibSp  Parch    Ticket      Fare    Cabin Embarked  \n",
       "PassengerId                                                      \n",
       "24               0      0    113788   35.5000       A6        S  \n",
       "98               0      1  PC 17759   63.3583  D10 D12        C  \n",
       "184              2      1    230136   39.0000       F4        S  \n",
       "194              1      1    230080   26.0000       F2        S  \n",
       "306              1      2    113781  151.5500  C22 C26        S  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# обратите внимание на круглые скобки вокруг каждого условия - они необходимы!\n",
    "# одновременное выполнение условий - поэтому &\n",
    "\n",
    "Ymale = df[(df.Survived == 1) & (df.Sex == 'male') & (df.Age < 32)]\n",
    "Ymale.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выберите из базы данных все строки, которые соответствуют пассажирам 1 или 2 класса."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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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>Survived</th>\n",
       "      <th>Class</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
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       "      <th>Cabin</th>\n",
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       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Bonnell, Miss. Elizabeth</td>\n",
       "      <td>female</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>C103</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Beesley, Mr. Lawrence</td>\n",
       "      <td>male</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248698</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>D56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Class  \\\n",
       "PassengerId                    \n",
       "2                   1      1   \n",
       "4                   1      1   \n",
       "7                   0      1   \n",
       "12                  1      1   \n",
       "22                  1      2   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "7                                      McCarthy, Mr. Timothy J    male  54.0   \n",
       "12                                    Bonnell, Miss. Elizabeth  female  58.0   \n",
       "22                                       Beesley, Mr. Lawrence    male  34.0   \n",
       "\n",
       "             SibSp  Parch    Ticket     Fare Cabin Embarked  \n",
       "PassengerId                                                  \n",
       "2                1      0  PC 17599  71.2833   C85        C  \n",
       "4                1      0    113803  53.1000  C123        S  \n",
       "7                0      0     17463  51.8625   E46        S  \n",
       "12               0      0    113783  26.5500  C103        S  \n",
       "22               0      0    248698  13.0000   D56        S  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# здесь одно из условий верно, или 1, или 2 класс, поэтому |\n",
    "# одновременно быть в 1 и 2 классе невозможно\n",
    "\n",
    "class1_2 = df[(df.Class == 1) | (df.Class == 2)]\n",
    "class1_2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выберите из базы данных все строки, которые соответствуют выжившим пассажирам 1 или 2 класса."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>Survived</th>\n",
       "      <th>Class</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Bonnell, Miss. Elizabeth</td>\n",
       "      <td>female</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>C103</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Beesley, Mr. Lawrence</td>\n",
       "      <td>male</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248698</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>D56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sloper, Mr. William Thompson</td>\n",
       "      <td>male</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113788</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>A6</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Class  \\\n",
       "PassengerId                    \n",
       "2                   1      1   \n",
       "4                   1      1   \n",
       "12                  1      1   \n",
       "22                  1      2   \n",
       "24                  1      1   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "12                                    Bonnell, Miss. Elizabeth  female  58.0   \n",
       "22                                       Beesley, Mr. Lawrence    male  34.0   \n",
       "24                                Sloper, Mr. William Thompson    male  28.0   \n",
       "\n",
       "             SibSp  Parch    Ticket     Fare Cabin Embarked  \n",
       "PassengerId                                                  \n",
       "2                1      0  PC 17599  71.2833   C85        C  \n",
       "4                1      0    113803  53.1000  C123        S  \n",
       "12               0      0    113783  26.5500  C103        S  \n",
       "22               0      0    248698  13.0000   D56        S  \n",
       "24               0      0    113788  35.5000    A6        S  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# обратите внимание на порядок круглых скобок: здесь как в арифметике - учитывается порядок действий\n",
    "\n",
    "surv1_2 = df[(df.Survived == 1) & ((df.Class == 1) | (df.Class == 2))]\n",
    "surv1_2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Добавьте в датафрейм столбец *Female*, состоящий из значений 0 и 1, где 1 соответствует пассажирам женского пола."
   ]
  },
  {
   "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",
       "    }\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>Survived</th>\n",
       "      <th>Class</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Female</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Class  \\\n",
       "PassengerId                    \n",
       "2                   1      1   \n",
       "4                   1      1   \n",
       "7                   0      1   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "7                                      McCarthy, Mr. Timothy J    male  54.0   \n",
       "\n",
       "             SibSp  Parch    Ticket     Fare Cabin Embarked  Female  \n",
       "PassengerId                                                          \n",
       "2                1      0  PC 17599  71.2833   C85        C       1  \n",
       "4                1      0    113803  53.1000  C123        S       1  \n",
       "7                0      0     17463  51.8625   E46        S       0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# сначала проверяем условие через ==, получаем набор из True и False\n",
    "# потом в списковом включении преобразуем логический тип в целочисленный (int)\n",
    "\n",
    "df['Female'] = [int(s) for s in df.Sex == 'female']\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Группировка \n",
    "Выведите на экран все уникальные значения в столбце *Embarked*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['C', 'S', 'Q'], dtype=object)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Embarked.unique() # array - массив, не список"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сгруппируйте строки в датафрейме в соответствии со значениями переменной *Survived* и выведите средние значения всех количественных переменных по группам."
   ]
  },
  {
   "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",
       "    }\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>Class</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Female</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Survived</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>0</th>\n",
       "      <td>1.216667</td>\n",
       "      <td>41.350000</td>\n",
       "      <td>0.366667</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>64.048262</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.178862</td>\n",
       "      <td>32.905854</td>\n",
       "      <td>0.512195</td>\n",
       "      <td>0.487805</td>\n",
       "      <td>85.821107</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Class        Age     SibSp     Parch       Fare    Female\n",
       "Survived                                                              \n",
       "0         1.216667  41.350000  0.366667  0.450000  64.048262  0.100000\n",
       "1         1.178862  32.905854  0.512195  0.487805  85.821107  0.666667"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# сначала группируем\n",
    "# потом получаем сводную информацию по агрегированным данным - задаем функцию mean для среднего\n",
    "\n",
    "df.groupby('Survived').agg('mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сгруппируйте строки в датафрейме в соответствии со значениями переменной *Sex* и сохраните в отдельный датафрейм таблицу со средними и медианными значениями переменной *Age* по группам (мужчины и женщины)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>mean</th>\n",
       "      <th>median</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>32.676136</td>\n",
       "      <td>32.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>38.451789</td>\n",
       "      <td>37.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             mean  median\n",
       "Sex                      \n",
       "female  32.676136   32.25\n",
       "male    38.451789   37.00"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# сначала группируем по Sex\n",
    "# потом забираем столбец Age\n",
    "# применяем нужные функции в agg(их несколько - не забудьте оформить в виде списка)\n",
    "\n",
    "age_agg = df.groupby('Sex').Age.agg(['mean', 'median'])\n",
    "age_agg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Выгрузка базы в файл\n",
    "Приведите все названия столбцов в датафрейме к нижнему регистру и сохраните изменения."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>survived</th>\n",
       "      <th>class</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>ticket</th>\n",
       "      <th>fare</th>\n",
       "      <th>cabin</th>\n",
       "      <th>embarked</th>\n",
       "      <th>female</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>S</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
       "      <td>female</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PP 9549</td>\n",
       "      <td>16.7000</td>\n",
       "      <td>G6</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Bonnell, Miss. Elizabeth</td>\n",
       "      <td>female</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>C103</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             survived  class  \\\n",
       "PassengerId                    \n",
       "2                   1      1   \n",
       "4                   1      1   \n",
       "7                   0      1   \n",
       "11                  1      3   \n",
       "12                  1      1   \n",
       "\n",
       "                                                          name     sex   age  \\\n",
       "PassengerId                                                                    \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "7                                      McCarthy, Mr. Timothy J    male  54.0   \n",
       "11                             Sandstrom, Miss. Marguerite Rut  female   4.0   \n",
       "12                                    Bonnell, Miss. Elizabeth  female  58.0   \n",
       "\n",
       "             sibsp  parch    ticket     fare cabin embarked  female  \n",
       "PassengerId                                                          \n",
       "2                1      0  PC 17599  71.2833   C85        C       1  \n",
       "4                1      0    113803  53.1000  C123        S       1  \n",
       "7                0      0     17463  51.8625   E46        S       0  \n",
       "11               1      1   PP 9549  16.7000    G6        S       1  \n",
       "12               0      0    113783  26.5500  C103        S       1  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = [c.lower() for c in df.columns]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выгрузите итоговый датафрейм в файл `Titanic-new.csv`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Titanic-new.csv')"
   ]
  }
 ],
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