01. Python y Pandas/1.4 Pandas solution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center>Practice 1. Analyzing Titanic passengers\n",
    "\n",
    "**Fill in the missing code (`\"You code here\"`) and choose answers in a [web-form](https://forms.gle/oMuDa6HYPbPUc1GQ9).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option(\"display.precision\", 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Read data into a Pandas DataFrame**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "##### DOWNLOAD DATASET. ONLY IN COLAB !!!\n",
    "#!wget -P ./../data/ https://raw.githubusercontent.com/CenticMurcia/curso-ciencia-datos/master/data/titanic_train.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('../data/titanic_train.csv', index_col='PassengerId')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**First 5 rows**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>7.25</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>71.28</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.92</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</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>53.10</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "1                   0       3   \n",
       "2                   1       1   \n",
       "3                   1       3   \n",
       "4                   1       1   \n",
       "5                   0       3   \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",
       "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "5                                     Allen, Mr. William Henry    male  35.0   \n",
       "\n",
       "             SibSp  Parch            Ticket   Fare Cabin Embarked  \n",
       "PassengerId                                                        \n",
       "1                1      0         A/5 21171   7.25   NaN        S  \n",
       "2                1      0          PC 17599  71.28   C85        C  \n",
       "3                0      0  STON/O2. 3101282   7.92   NaN        S  \n",
       "4                1      0            113803  53.10  C123        S  \n",
       "5                0      0            373450   8.05   NaN        S  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>891.00</td>\n",
       "      <td>891.00</td>\n",
       "      <td>714.00</td>\n",
       "      <td>891.00</td>\n",
       "      <td>891.00</td>\n",
       "      <td>891.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.38</td>\n",
       "      <td>2.31</td>\n",
       "      <td>29.70</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.38</td>\n",
       "      <td>32.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.49</td>\n",
       "      <td>0.84</td>\n",
       "      <td>14.53</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.81</td>\n",
       "      <td>49.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>20.12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>28.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>14.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>38.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>8.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>512.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Survived  Pclass     Age   SibSp   Parch    Fare\n",
       "count    891.00  891.00  714.00  891.00  891.00  891.00\n",
       "mean       0.38    2.31   29.70    0.52    0.38   32.20\n",
       "std        0.49    0.84   14.53    1.10    0.81   49.69\n",
       "min        0.00    1.00    0.42    0.00    0.00    0.00\n",
       "25%        0.00    2.00   20.12    0.00    0.00    7.91\n",
       "50%        0.00    3.00   28.00    0.00    0.00   14.45\n",
       "75%        1.00    3.00   38.00    1.00    0.00   31.00\n",
       "max        1.00    3.00   80.00    8.00    6.00  512.33"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891</td>\n",
       "      <td>891</td>\n",
       "      <td>891</td>\n",
       "      <td>204</td>\n",
       "      <td>889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>891</td>\n",
       "      <td>2</td>\n",
       "      <td>681</td>\n",
       "      <td>147</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Green, Mr. George Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>CA. 2343</td>\n",
       "      <td>B96 B98</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>577</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>644</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                           Name   Sex    Ticket    Cabin Embarked\n",
       "count                       891   891       891      204      889\n",
       "unique                      891     2       681      147        3\n",
       "top     Green, Mr. George Henry  male  CA. 2343  B96 B98        S\n",
       "freq                          1   577         7        4      644"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe(include=['object', 'bool'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Let's select those passengers who embarked in Cherbourg (Embarked=C) and paid > 200 pounds for their ticker (fare > 200).**\n",
    "\n",
    "Make sure you understand how actually this construction works."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Baxter, Mr. Quigg Edmond</td>\n",
       "      <td>male</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>PC 17558</td>\n",
       "      <td>247.52</td>\n",
       "      <td>B58 B60</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Ward, Miss. Anna</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17755</td>\n",
       "      <td>512.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Baxter, Mrs. James (Helene DeLaudeniere Chaput)</td>\n",
       "      <td>female</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>PC 17558</td>\n",
       "      <td>247.52</td>\n",
       "      <td>B58 B60</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Ryerson, Miss. Emily Borie</td>\n",
       "      <td>female</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>PC 17608</td>\n",
       "      <td>262.38</td>\n",
       "      <td>B57 B59 B63 B66</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Widener, Mr. Harry Elkins</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>113503</td>\n",
       "      <td>211.50</td>\n",
       "      <td>C82</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "119                 0       1   \n",
       "259                 1       1   \n",
       "300                 1       1   \n",
       "312                 1       1   \n",
       "378                 0       1   \n",
       "\n",
       "                                                        Name     Sex   Age  \\\n",
       "PassengerId                                                                  \n",
       "119                                 Baxter, Mr. Quigg Edmond    male  24.0   \n",
       "259                                         Ward, Miss. Anna  female  35.0   \n",
       "300          Baxter, Mrs. James (Helene DeLaudeniere Chaput)  female  50.0   \n",
       "312                               Ryerson, Miss. Emily Borie  female  18.0   \n",
       "378                                Widener, Mr. Harry Elkins    male  27.0   \n",
       "\n",
       "             SibSp  Parch    Ticket    Fare            Cabin Embarked  \n",
       "PassengerId                                                            \n",
       "119              0      1  PC 17558  247.52          B58 B60        C  \n",
       "259              0      0  PC 17755  512.33              NaN        C  \n",
       "300              0      1  PC 17558  247.52          B58 B60        C  \n",
       "312              2      2  PC 17608  262.38  B57 B59 B63 B66        C  \n",
       "378              0      2    113503  211.50              C82        C  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['Embarked'] == 'C') & (data.Fare > 200)].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**We can sort these people by Fare in descending order.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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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>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>259</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Ward, Miss. Anna</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17755</td>\n",
       "      <td>512.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>680</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cardeza, Mr. Thomas Drake Martinez</td>\n",
       "      <td>male</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>PC 17755</td>\n",
       "      <td>512.33</td>\n",
       "      <td>B51 B53 B55</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>738</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Lesurer, Mr. Gustave J</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17755</td>\n",
       "      <td>512.33</td>\n",
       "      <td>B101</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Ryerson, Miss. Emily Borie</td>\n",
       "      <td>female</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>PC 17608</td>\n",
       "      <td>262.38</td>\n",
       "      <td>B57 B59 B63 B66</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Ryerson, Miss. Susan Parker \"Suzette\"</td>\n",
       "      <td>female</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>PC 17608</td>\n",
       "      <td>262.38</td>\n",
       "      <td>B57 B59 B63 B66</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass                                   Name     Sex  \\\n",
       "PassengerId                                                                    \n",
       "259                 1       1                       Ward, Miss. Anna  female   \n",
       "680                 1       1     Cardeza, Mr. Thomas Drake Martinez    male   \n",
       "738                 1       1                 Lesurer, Mr. Gustave J    male   \n",
       "312                 1       1             Ryerson, Miss. Emily Borie  female   \n",
       "743                 1       1  Ryerson, Miss. Susan Parker \"Suzette\"  female   \n",
       "\n",
       "              Age  SibSp  Parch    Ticket    Fare            Cabin Embarked  \n",
       "PassengerId                                                                  \n",
       "259          35.0      0      0  PC 17755  512.33              NaN        C  \n",
       "680          36.0      0      1  PC 17755  512.33      B51 B53 B55        C  \n",
       "738          35.0      0      0  PC 17755  512.33             B101        C  \n",
       "312          18.0      2      2  PC 17608  262.38  B57 B59 B63 B66        C  \n",
       "743          21.0      2      2  PC 17608  262.38  B57 B59 B63 B66        C  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['Embarked'] == 'C') & \n",
    "     (data['Fare'] > 200)].sort_values(by='Fare',\n",
    "                               ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Let's create a new feature.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def age_category(age):\n",
    "    '''\n",
    "    < 30 -> 1\n",
    "    >= 30, <55 -> 2\n",
    "    >= 55 -> 3\n",
    "    '''\n",
    "    if age < 30:\n",
    "        return 1\n",
    "    elif age < 55:\n",
    "        return 2\n",
    "    elif age >= 55:\n",
    "        return 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "age_categories = [age_category(age) for age in data.Age]\n",
    "data['Age_category'] = age_categories"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Another way is to do it with `apply`.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Age_category'] = data['Age'].apply(age_category)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. How many men/women were there onboard?\n",
    "- 412 men and 479 women\n",
    "- 314 men and 577 women\n",
    "- 479 men and 412 women\n",
    "- **<font color='green'>577 men and 314 women</font>**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "male      577\n",
       "female    314\n",
       "Name: Sex, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Option 1\n",
    "data['Sex'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(577, 314)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Option 2\n",
    "(data['Sex']=='male').sum(), (data['Sex']=='female').sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. How many men from second class were there onboard?\n",
    "\n",
    "**Tip: Print the distribution of the `Pclass` feature with the `Sex` feature.**\n",
    "- 104\n",
    "- **<font color='green'>108</font>**\n",
    "- 112\n",
    "- 125"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "108"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Solution with filters and then count rows\n",
    "len( data[(data.Sex==\"male\") & (data['Pclass']==2)] )"
   ]
  },
  {
   "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",
       "    }\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>Sex</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pclass</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>94</td>\n",
       "      <td>122</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>76</td>\n",
       "      <td>108</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>144</td>\n",
       "      <td>347</td>\n",
       "      <td>491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>314</td>\n",
       "      <td>577</td>\n",
       "      <td>891</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sex     female  male  All\n",
       "Pclass                   \n",
       "1           94   122  216\n",
       "2           76   108  184\n",
       "3          144   347  491\n",
       "All        314   577  891"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Solution crosstab\n",
    "pd.crosstab(data['Pclass'], data['Sex'], margins=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. What are median and standard deviation of `Fare`?\n",
    "- **<font color='green'>median is  14.45, standard deviation is 49.69</font>**\n",
    "- median is 15.1, standard deviation is 12.15\n",
    "- median is 13.15, standard deviation is 35.3\n",
    "- median is  17.43, standard deviation is 39.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fare median: 14.45\n",
      "Fare std:    49.69\n"
     ]
    }
   ],
   "source": [
    "print(\"Fare median:\", round( data['Fare'].median(), 2))\n",
    "print(\"Fare std:   \", round( data['Fare'].std(),    2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. Is the mean age of survived people higher than people who died?\n",
    "- Yes, the mean age of survived people is higher.\n",
    "- **<font color='green'>No, the mean age of survived people is lower.</font>**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Died people, mean age:     30.62617924528302\n",
      "Survived people, mean age: 28.343689655172415\n"
     ]
    }
   ],
   "source": [
    "# Solution simple\n",
    "print(\"Died people, mean age:    \", data[data['Survived'] == 0].Age.mean() )\n",
    "print(\"Survived people, mean age:\", data[data['Survived'] == 1].Age.mean() )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived\n",
       "0    30.63\n",
       "1    28.34\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Solution with group by\n",
    "data.groupby('Survived')['Age'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. What are the percentages of survived passengers for:\n",
    "## a) younger than 30 y.o.\n",
    "## b) older than 60 y.o.\n",
    "\n",
    "- 22.7% among young and 40.6% among old\n",
    "- **<font color='green'>40.6% among young and 22.7% among old</font>**\n",
    "- 35.3% among young and 27.4% among old\n",
    "- 27.4% among young and  35.3% among old"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Survived young people: 40.6 %\n",
      "Survived old people:   22.7 %\n"
     ]
    }
   ],
   "source": [
    "young = data[data['Age'] < 30]\n",
    "old   = data[data['Age'] > 60]\n",
    "\n",
    "print(\"Survived young people:\", round(100 * young.Survived.mean(), 1), \"%\")\n",
    "print(\"Survived old people:  \", round(100 * old.Survived.mean(), 1), \"%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6. Is that true that women survived more frequently than men? What are the percentages?\n",
    "- 30.2% among men and 46.2% among women\n",
    "- 35.7% among men and 74.2% among women\n",
    "- 21.1% among men and 46.2% among women\n",
    "- **<font color='green'>18.9% among men and 74.2% among women</font>**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Survived women: 74.2 %\n",
      "Survived men:   18.9 %\n"
     ]
    }
   ],
   "source": [
    "# Solution simple\n",
    "women = data[data['Sex']==\"female\"]\n",
    "men   = data[data['Sex']==\"male\"]\n",
    "\n",
    "print(\"Survived women:\", round(100 * women.Survived.mean(), 1), \"%\")\n",
    "print(\"Survived men:  \", round(100 * men.Survived.mean(), 1), \"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sex\n",
       "female    0.74\n",
       "male      0.19\n",
       "Name: Survived, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Solution with group by\n",
    "data.groupby('Sex')['Survived'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7. What's the most popular first name among male passengers?\n",
    "- Charles\n",
    "- Thomas\n",
    "- **<font color='green'>William</font>**\n",
    "- John"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getNameFunction(fullname):\n",
    "    return fullname.split(\",\")[1].split(\" \")[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "William    35\n",
       "John       25\n",
       "George     14\n",
       "Thomas     13\n",
       "Charles    13\n",
       "Name: Name, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "men = data[data['Sex'] == 'male']\n",
    "men[\"Name\"].apply(getNameFunction).value_counts().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 8. How is average age for men/women dependent on `Pclass`?\n",
    "### Choose all correct statements:\n",
    "- **<font color='green'>On average, men of 1 class are older than 40</font>**\n",
    "- On average, women of 1 class are older than 40\n",
    "- **<font color='green'>Men of all classes are on average older than women of the same class</font>**\n",
    "- **<font color='green'> On average, passengers ofthe first class are older than those of the 2nd class who are older than passengers of the 3rd class</font>**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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></th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pclass</th>\n",
       "      <th>Sex</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>female</th>\n",
       "      <td>34.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>41.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
       "      <th>female</th>\n",
       "      <td>28.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>30.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <th>female</th>\n",
       "      <td>21.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Age\n",
       "Pclass Sex          \n",
       "1      female  34.61\n",
       "       male    41.28\n",
       "2      female  28.72\n",
       "       male    30.74\n",
       "3      female  21.75"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.pivot_table(['Age'], ['Pclass', \"Sex\"], aggfunc='mean').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Sex</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pclass</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34.61</td>\n",
       "      <td>41.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28.72</td>\n",
       "      <td>30.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21.75</td>\n",
       "      <td>26.51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sex     female   male\n",
       "Pclass               \n",
       "1        34.61  41.28\n",
       "2        28.72  30.74\n",
       "3        21.75  26.51"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['Pclass'], data['Sex'], values=data['Age'], aggfunc='mean')"
   ]
  }
 ],
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