{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bc24a78c-c875-4a71-897b-72c33067dc7f",
   "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>PClass</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerID</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>1st</td>\n",
       "      <td>29.00</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1st</td>\n",
       "      <td>2.00</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1st</td>\n",
       "      <td>30.00</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1st</td>\n",
       "      <td>25.00</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1st</td>\n",
       "      <td>0.92</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            PClass    Age     Sex  Survived\n",
       "PassengerID                                \n",
       "1              1st  29.00  female         1\n",
       "2              1st   2.00  female         0\n",
       "3              1st  30.00    male         0\n",
       "4              1st  25.00  female         0\n",
       "5              1st   0.92    male         1"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "titanic_filename = \"Titanic-1.csv\"\n",
    "titanic = pd.read_csv(titanic_filename, index_col=0)\n",
    "titanic.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "956394bb-983e-4642-8242-73e02dca30aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "70367e2f-cf23-4fba-a473-5fb0c8b24524",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic['Age'][4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6f3ed9bb-89b8-4796-aaac-1672aebf4d79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[4, 'Age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "288abbc1-1055-4ce5-9499-0885a2e4e736",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.iloc[3, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4677f89a-0147-4b12-a702-60a87e0a0d34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerID\n",
       "1        True\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "5        True\n",
       "        ...  \n",
       "1309    False\n",
       "1310    False\n",
       "1311    False\n",
       "1312    False\n",
       "1313    False\n",
       "Name: Survived, Length: 1313, dtype: bool"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask_survived = titanic['Survived'] == 1\n",
    "mask_survived"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9bcf5dbc-fb32-4d94-9619-27590f0e5c41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerID\n",
       "1       29.00\n",
       "5        0.92\n",
       "6       47.00\n",
       "7       63.00\n",
       "9       58.00\n",
       "        ...  \n",
       "1280    22.00\n",
       "1290      NaN\n",
       "1294    45.00\n",
       "1303      NaN\n",
       "1305    15.00\n",
       "Name: Age, Length: 450, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[mask_survived, 'Age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e2bb6ebf-2ae5-41d1-9211-4a2084d9cda3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PClass</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1st</td>\n",
       "      <td>29.0</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1st</td>\n",
       "      <td>26.0</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1st</td>\n",
       "      <td>28.0</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>1st</td>\n",
       "      <td>27.0</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>1st</td>\n",
       "      <td>27.0</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1300</th>\n",
       "      <td>3rd</td>\n",
       "      <td>27.0</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>3rd</td>\n",
       "      <td>27.0</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>3rd</td>\n",
       "      <td>27.0</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1310</th>\n",
       "      <td>3rd</td>\n",
       "      <td>26.0</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1313</th>\n",
       "      <td>3rd</td>\n",
       "      <td>29.0</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>90 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            PClass   Age     Sex  Survived\n",
       "PassengerID                               \n",
       "1              1st  29.0  female         1\n",
       "21             1st  26.0    male         1\n",
       "25             1st  28.0    male         1\n",
       "58             1st  27.0    male         1\n",
       "64             1st  27.0    male         0\n",
       "...            ...   ...     ...       ...\n",
       "1300           3rd  27.0    male         0\n",
       "1304           3rd  27.0    male         0\n",
       "1309           3rd  27.0    male         0\n",
       "1310           3rd  26.0    male         0\n",
       "1313           3rd  29.0    male         0\n",
       "\n",
       "[90 rows x 4 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask_age = (titanic['Age'] > 25) & (titanic['Age'] < 30)\n",
    "titanic[mask_age]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b6e29b05-a282-44d6-9772-f99dfe8859bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Survived</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31.131670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29.359585</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Age\n",
       "Survived           \n",
       "0         31.131670\n",
       "1         29.359585"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.groupby(['Survived']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "359a6506-29e4-42b2-a8b6-246b23d01b8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PClass</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>764</th>\n",
       "      <td>3rd</td>\n",
       "      <td>0.17</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>3rd</td>\n",
       "      <td>0.33</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545</th>\n",
       "      <td>2nd</td>\n",
       "      <td>0.80</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>617</th>\n",
       "      <td>3rd</td>\n",
       "      <td>0.83</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359</th>\n",
       "      <td>2nd</td>\n",
       "      <td>0.83</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1301</th>\n",
       "      <td>3rd</td>\n",
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       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1303</th>\n",
       "      <td>3rd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>3rd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1307</th>\n",
       "      <td>3rd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>3rd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1313 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            PClass   Age     Sex  Survived\n",
       "PassengerID                               \n",
       "764            3rd  0.17  female         1\n",
       "752            3rd  0.33    male         0\n",
       "545            2nd  0.80    male         1\n",
       "617            3rd  0.83    male         1\n",
       "359            2nd  0.83    male         1\n",
       "...            ...   ...     ...       ...\n",
       "1301           3rd   NaN    male         0\n",
       "1303           3rd   NaN    male         1\n",
       "1306           3rd   NaN    male         0\n",
       "1307           3rd   NaN  female         0\n",
       "1308           3rd   NaN  female         0\n",
       "\n",
       "[1313 rows x 4 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.sort_values(['Age'], ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b4d3b2bb-f272-4e8c-ab98-dabf60f9aca7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        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>Age</th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>756.000000</td>\n",
       "      <td>1313.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>30.397989</td>\n",
       "      <td>0.342727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.259049</td>\n",
       "      <td>0.474802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.170000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>39.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>71.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Age     Survived\n",
       "count  756.000000  1313.000000\n",
       "mean    30.397989     0.342727\n",
       "std     14.259049     0.474802\n",
       "min      0.170000     0.000000\n",
       "25%     21.000000     0.000000\n",
       "50%     28.000000     0.000000\n",
       "75%     39.000000     1.000000\n",
       "max     71.000000     1.000000"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b44beeea-4a88-455c-98ed-6f2496cac8a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Sex'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic['Sex'].value_counts().plot(kind='pie', autopct='%.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c75620ea-331a-44d8-9afc-72bbd0e9b4ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='PClass'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OMv7qgzttDZ41mF1P7aL6lGpa1rbgr/BTOqSU0uGltKxtIdGWQAYIzSuaqQhk/c+pI9sNHCrVk/i3k9+2ADdlr5xeNaGh7tYworsu9L+46iL/84lpsiFQKvEjcMeg9+rc5lhlIYRa/MLYS8dS/+N6TMIw9MyhlI8rZ/fT7oWwYXOGUTmzksbljaz+6mp8ZT7GX+WGfuDkgQw+aTBvffstxC+UTyxn6NlZH06Q81D3uOyOiDj0cJxhjDk2G0V1JxCKrEVHau1XTlvLXN+SlQv8ixpO8q0aU0HbFJH0hsQ2iTSedsT4gbgdi1TmvOIEnZNz2WBve+oP5qSK1BX1ebWQSJwsb755ccminWf7lu07L87I5dtKY6oqjHmzRaSb80uVpu25brC3UJcCo4wxL3R9UETOBLZkraruFV2oj5Qtby/wL9ow37e4dILsmNrTeXF/zWhr3/FaRbmGOrN25LrB3kJ9K/CNwzzekvzZhzJcT28ac9xezg2lYfeF/hdWXeR/vnN6H8+L+2tuLFb6WkV5LpoqJnm3pw4YY5Yf+qAx5lURCWSnpB55LtRltLfO9S359wL/wqaTfKtGDaRtqgin2ahlbnPLpB8Ot9Gyp+VdqHt627ZxFXqjhTYzSkgkTpJVqy4uWbT9bN+y6uE0TO/6ebFNo+Px0SXGbOh0B+yozMi7UL8iIp8xxtzd9UERuQp4LXtldWuVhTb7bZJs2bDA/+zb832LSybK9mk+YTow3XZdhzOpo2PjmgEDNNSZk3fn1NcBj4jIJRwI8Ym4AysuymJd3XnTQpt9NpSG3f/hf3HVh/3Pd86QtwOlEp8IFERQzo61JNYM0HEzGbQ51w32GGpjzHbgfSLyfuDo5MMRY8zTWa/s8PIy1GW0t87xLV25wL8oeopv5eiB7ufFVs6L+2tec2zc3UN0hGuGtAFrc91ob51PyoGrgaMAB7jHGNOZo9oOKxCK7MbyrKJCInGirF69wL9o+xz/0qrhNMwQ6fH6Q0E5NjBhlxHRS2b997oTdGblutHeDr9/jdvN7TngfNzzwOuyXFNvVgGn5rrRgGzduMD/bP183+KSI2T7VJ+YaYAnP9MdHY+v3VpSoqHuP8dGo72FeoYx5hgAEbkHeDn7JfXqTXIQ6iE07rnA7Ufd8V6pPyJ5Xjwh2+3mg/fFWlseGlxpuwwveMNGo72Fen9ndGNMZz+GeGZSVs6rB9DRNse35N8X+xc1nux7c+QgWqeK5P6IIB+c19xco6HOiLzcU88UkYbk9wJUJO8L7pDPwVmt7vAy9LGWMSfI6lUX+xdum+NfNriG6PRM9aMudCe0tk3BmBZEdERc/+TfntoYk48jdl5J94lHyLZNC/yL1s/3LS4JyPYpXj4v7o9SKB2SSKzY6/fPtF1LAdvjBJ0NvW+WeSlPZ5Qv6utqNyeHYE7ubdtqmvZe4H/xzYv8z3ccLesnJvtRW1kzuNAc19q295kCGF+dxxbZarjgQp20iMOEegAdbe/3LV1xsX9Rwym+lSMG0TqtWM+L++vc5lilhrpfnrLVcKGGeiFwJRhzvKxZfbF/4dYP+JfuOy8+znZxXjA71vIejEkgkuqMs+pgtjpoFWaoZ8map28pvfPFgGyb6hMzFZhquyavqTJmcIUxq1pE9Hfbd1udoLPCVuMF+S786A+u23ykb+sQnxjtIJFF09vbcz7CyCOs7aWhQEOd9DfbBXjd3OYWG4sgeoG182ko7FD/3XYBXje3ORawXUMBMsCTNgso5FA/iwdnQsknY+LxMSXGFPzEFDn2LyfoWP2dFW6ow9F24E+2y/C6SR0dVjpQFLDf2i6gIK9+d3E/cKXtIrzsrCxMmtC+q53Nd2+mM9oJAkPPHkrNvBqiL0fZ8egO2ra2MfnGyVRMencv1e6eC7D9ke3sWbSHkir3z3rUR0dRNTOn6yp2An/MZYOHU+ihfh53EHqvvctUeuY1x8b+KsOTJohfGP3x0VQEKoi3xFkbXkvleyspG1/GxGsnsvn+7icL6e655ePc4ew159ZQc35Nt8/PsiedoLPTVuP7FO7hN0A4aoD/sV2Gl01r7zhSjNmdydcsHVK6fw0rf4WfsrFldO7ppHxsOWVjytJ6bp6wfugNhR5q169Jd5FG1SsBGRWPv5Wt12/f2U7r261UTO77gLDDPXfXk7tY8601bLpnE/HmeCZL7U0L8EguG+xO4Yc6HH0bi53ni8H7Wlpj2XjdeGucDbdtYPQnR+Ov6NuAwMM9d/ic4Uz50RSO+s5RlFaXsvX3W7NRdncedoJOXqwgU/ihdt1vuwAvO68plvGTVNNp2HjbRoacNoTqE/t2zt7dc0uqSxCfID5h6FlDaVnXkumye3JLLhvriVdC/Wdgr+0ivOqE1lZ30oQMMcaw+d7NlI0po+a8vr1f9PTcjr0HVo1tWNKw/+JZDix0gs6SXDXWmx5nEy0o4eqbgBttl+FVZ0wc93o0Q5MmNK9uZv3311M2vox9U2SN+ugoTKdhywNbiDfG8Q30UTGxgsBXAnTs6WDzfZsJ/Feg2+dWzaxi4y830rqxFYABNQMYe/lYSofkpKfrh5yg83guGkqFl0I9FHgbyOkHk8Xi2pE1ixYOGniW7Try0JvADCfo5E2QvHL4DeHoHuA222V41bnNsUG2a8hTP82nQIOXQu26BWi2XYQXzW5JTpqgunqHPOwn4a1Qh6PvAHfaLsOLBidMdbkxWfu8ukD9wAk6rbaLOJS3Qu36MZB3v2gvmN7evs12DXlkPXl6ulfofb/fLRzdRrj6buBa26XsszGa4FOPtrCtyeAT+OzxpXzp1APdIX/8Yhs3/LONnTdUUjPw3e+zgVsbqSoT/AIlPnj1s+5E+zf8o5X/Xd3JAD9MHubjvgsqGFKevQUX5ja3lC4t98ySYf31DSfotNsu4nC8uKcG+C6wx3YR+5T44Cfzyln5hUpeumoQt7/SwYqdbhfGjdEE/1zXycTqnsP4THAgy66u3B9ogHMml/DGfw5i+ecrmTLMxw+ea8vqv+McnTRhn5edoPN720V0x5uhDkd3Al+3XcY+Y6p8HD/G7cpYVSZMH+Fjc4N7wfT6J1q5eW456exf500uocTnPvPU8X42NWb3OtaYeHyM35hNWW2kMHzFdgE98WaoXXcBL9ku4lD1exMs3RrnlPF+HlvVwbgqHzNH99zvWQTm/SbGCXc1cddrhz/iu3dZB+cflf2zqUkdHW9nvZH89qgTdJ6zXURPvBtqd1jm54GcDtXpSVO74SN/jHHreeWU+OB7z7Xxnff3PNQQ4IUrB7Hkc5X87ZKB3P5KO8++ffBQw+8920aJDy45Jvu9p86KtRTzx1otwA22i+iNd0MNEI4uA/7bdhkAHXE30JccU8qHp5eydneC9XsMM+9sInBrI5saDMf/spltTe/OzNgq979p5CAfF00r4eXNB96nfr2sncfXdPLghyvIxaqk85pjY7PeSP76phN08v5jPW+H2nUj0P1UGjlgjOGqx1qZXuPnv05z98zHjPKz44Yq6q9zb+MHC0s+N4jRlQf/lzS3GxrbzP7v/7E2ztEj3cP1v7/VyQ9faOexj1cwsDQ3ywxPdydNyJuLkDn0PPAz20WkwvuhDkcbgettlvDCxji/Wd7B0+s7mXVnE7PubOKvazq63X5LY4L5D7pDmLc3G864r5mZdzZx8q+aqX1PCeclz52v+WsLje2Gc34TY9adTVz9ePaHGmZ70oQ81QJc6QSdgjj18M6Ajt6Eq38PfMx2GV5wY82whY9UVZ5tu44cut4JOrfaLiJV3t9TH/AZYI3tIrzgvObMT5qQx54Hfm67iL4onlC7h+EL0C6k/XZiS+sUjCmG32MDcHmhHHbvUzyhBghHXwe+ZLuMQjcABlQnEqtt15EDlztBZ63tIvqquEINEI7eRZ5M5VrIZrW1ef0K+E+coJMXs4P2VfGF2vU5YJXtIgqZxydNeAYI2S4iXcUZ6nC0CfgoOqFC2s6KeXbShHXAAifo5M0KAX1VnKEGCEffAD4CdP+BseqWRydNaAIucILOrt42FJEJIvKMiKwUkX+LSJ+u1YjIQhE5Me1Ke1C8oQYIR58AgugKH2mZ1t7hpUkT2oGPOkHnjRS37wS+bIyZDpwKfEFEZmStuj4o7lADhKO/Q6+Ip2Vuc8wrk2zEgU84QeeJVJ9gjNlqjFmS/L4RWAmMS+6BfygiL4vIahE5E0BEKkTk9yKyXET+APR9naEUaagBwtH/xp1YQfXBObHYJNs1ZIDB7QL6cLovICIB4DhgcfKhEmPMycB1wLeTj30eiBljjgW+B5yQbnu90VDvE47eiE5a2CdjOz0xacK1TtBJe0ZQEakEHgKuM8Y0JB/e9wbxGhBIfj8beADAGLMcWJ5um73RUB/sC8CfbBdRSAIdHRts19AP33SCzu3pPllESnED/aAxpuueft+8UnEOngcwJ9duNNRdhaMJ4JPognspOyvWmjeTUPTRTU7Q+X66TxZ38Po9wEpjTCqL4z0LXJJ87tHAsem23RsN9aHC0U7C0SuAH9gupRDMa46NsV1DH8WBq52gE+7n65wOXAbMEZFlydv8Hra/A6gUkeXAV4GX+9l+t4pn6GU6wtXX4A6M1ze/bhgwMwMTokZkiO1aUtCKe5X7UduFZJP+sfYkHL0N+DgHzpHUIQRkZDxeCENa9wBzvR5o0FD3Lhz9E3A+7jA8dRintbTme3fbjcAZTtB5wXYhuaChTkU4+gzuRxLrbJeSj85tjg23XUMPXgBOdYLOCtuF5IqGOlXuWOzj0Y+83uXkltapeThpggF+BJztBJ0ttovJJb1Qlo5w9eeAWwFdWCrp9Injljf4/Vn7mKaPdgNBJ+g8brsQG3RPnY5w9JfAybj9fRUwq609XyZNeBk4vlgDDRrq9IWjDnAS2lEFgHObYwMtl5AAbgHOdIJOUS8NpIffmRCu/iTujJP5fMEoq6I+iZ4xcXwVIjZ2FMuBzzhBJ2sdOgqJ7qkzIRz9LTAVuM92KbZUJ0x1mTG5nqSvBXd10xM00AfonjrTwtWzcbsE5sWA+Vy6dMyoZ18vL5udo+aexO3uWXCzfWab7qkzLRx9FpiJO/FCvlw8yokPxHIyacIG4FNO0DlHA314uqfOpnD1cOA7uKuDZH+dWcs2lfi3nD9hXLZWxdyOO7nAL52gc/hFuhWgoc6NcPVE4CvAp8niNDb5YFZgwua4yLgMvuQe3E4kP3OCTiyDr+tZGuokEbkX+CCwwxhzdA/bnQ20G2Ne7HMj4eoRuIflXwCGpFNnvrtg3JgX1w0ofV8GXqoBd23xHzlBJ5qB1ysaek59wP3AeSlsdzaQ3h9tOLqTcPRbwBHA1wAvzcYJwOxYS38nTViB+6Y3zgk639JA953uqbtITiD3+L49tYh8EbgadzrYFbirNryEO9B+J3CtMea5tBsMV5fjDrS/nHTfKPLMGwMGrPnEuNHv6ePT4sBfgNucoPNMFsoqKhrqLg4T6i3AJGNMm4gMMcbsFZEw0GSM+XFGGw9XHwlcmrz1NRR5w4A5NjChAZHqFDZfC/wOuMsJOhuzXFrR8Mq8zdmyHHhQRB4FHs1qS+HoOtwr5d8hXH0Kbrg/BozIarsZlpw0YfWOkpKTutlkJe5kfQ85QWdZ7iorHhrqntXijqP+D+D/ich7c9JqOLoYWEy4+npgDvCB5NfjAH9OauiHU1tamx+rqtx31wCv406b+1AxjWu2RQ+/u+h6+C1uH+aJxpj65FSwm3C7gl4FDDbGfLuHl8qOcHU17pvMHOD9uDNSSs7r6Fn8hYryyNWjR24AFgKLnKDzjuWaioqGOklEfod7ZbsGt6PDd3EvYlXjBucBY0ydiEwB/ow7Kqh/F8r6y+3ccgZul9RpydtU3JpzoQH3vHgt7sT1LwGvEI7m+/RGnqah9qJw9RgOhHwK7htV9SG3IcBgDv5YM447SCLW5WsMN7zrccO7LnlbSzja6+qQKvc01MUsXC1AJW6wWwhHtfulB2iolfIY7VGmlMdoqJXyGA21Uh6joVbKYzTUSnmMhlopj9FQK+UxGmqlPEZDrZTHaKiV8hgNtVIeo6FWymM01Ep5jIZaKY/RUCvlMRpqpTxGQ62Ux2iolfIYDbVSHqOhVspjNNRKeYyGWimP0VAr5TEaaqU8RkOtlMdoqJXyGA21Uh7zf/ZTcpQ+niavAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic['PClass'].value_counts().plot(kind='pie', autopct='%.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "20ff9ccf-e02c-4823-9c63-3d2f9758704a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='PClass'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic.PClass.value_counts().plot.pie(autopct='%.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "089e622e-6d7c-4de0-a53f-6f1697262229",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Age')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "titanic.Age.plot.hist(bins=10)\n",
    "plt.title(\"Titanic - Age Info\")\n",
    "plt.xlabel('Age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8f24a12a-9f0d-49bd-9991-cb78fb49175d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Age')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PqSYMdN03yAqCBZz6snRGFqrw6i4b02FCRyCDoxTI9XqeA5T5eoyIxOIJjd+p6otexxwXkSznmCzAVsUxZyivDZ4FnPoyOSOJiWOG84o1V5kQEsjg2ATki0ieiMQBy4HV3Y5ZDdzq9K6aD9SqarmICPAYsEdVf9rDObc5398GrArcRzCh6mjXGI4g7lUFnjU6lszIZH1xlS0pa0JGwIJDVduBu4FX8dzcfl5Vd4nIShFZ6Ry2BigGioBHgC852y8GPgtcISJbncc1zr77gMUish9Y7Dw35kPKa5oRgYyR7i/g1J9rzx9LR6eyxnpXmRAR48tBIvIC8Djwsqp2+vriqroGTzh4b3vI63sF7urhvHfo+f4HqnoSuNLXGkxkKqtpYkxSPPEx0W6X0q9pWcnkpyfxl61lfHb+eLfLMaZfvl5xPAh8CtgvIveJyNQA1mTMWSurbWJskN8Y7yIiXDdzLBsPVZ1uYjMmmPkUHKr6uqp+GpgDHAJeE5F/iMjnnJvYxgSVspomskcF9/0Nb9fNGgvAS9u69x8xJvj4fI9DREYDtwN3AluAX+AJktcCUpkxA6SqnsF/QX5j3Nv40cOZmZvCqq0WHCb4+RQcIvIi8DaQCHxMVa9T1edU9ctAUiALNMZfNY1tNLV1BH1X3O6umzmW3eV1FFXUu12KMX3y9YrjUVWdrqr/t2vUtojEA6hqQcCqM2YAymo99wmyg3ieqp587PwsRGC1XXWYIOdrcPxHD9veHcxCjBkspxdwCrErjvQRCVw0aTR/3lpGZ2f3SRaMCR59BoeIZIrIBcAwEZktInOcxyI8zVbGBJ1gXTLWFzfOyeFIVSMbDla5XYoxvepvHMfVeG6I5wDeI7jrge8GqCZjzkpZTRNxMVGMHh7ndil+Wzoji39btYvnC0tYMGm02+UY06M+rzhU9QlVvRy4XVUv93pc123+KGOChmcBpwQ8M9eElmFx0Vw3ayxrdpRT29TmdjnG9Ki/pqrPON9OEJFvdH8MQX3G+K28tjkkm6m63Dw3l5b2TlbbmA4TpPq7OT7c+ZoEJPfwMCbolNU0hXRwnJc9kqmZyTy/qaT/g41xQZ/3OFT1f52vPxyacow5O20dnRyvaw6Z6UZ6IiLcPDeXH/5lN7vKajl37Ei3SzLmQ3wdAPgjERkhIrEislZETng1YxkTNI7XNdOpodmjytvHZ+cwLDaaJ/5xyO1SjDmDr+M4PuKswHctnsWXJgP/HLCqjBmgUFnAqT8jE2O58YJs/ry1jBO2TocJMr4GR9dEhtcAz6iqdTI3QSmUx3B0d/tFebS2d/L7DUfcLsWYD/E1OP4iInuBAmCtiKQBzYEry5iBOb3yX4hNN9KTc9KTWDQljSffPUxLe4fb5Rhzmq/Tqt8DLAAKVLUNOAUsC2RhxgxEWU0TKYmxJMb5tEZZ0Ftx6URONLTwnPWwMkHEn5+uaXjGc3if8+Qg12PMWSmraQ76dcb9sWDSaOZNSOWBN4u4qSCXhNjgX9HQhD9fe1U9BfwEuASY6zxsVlwTdEJ9DEd3IsLXFudzvK6FZzfavQ4THHy94igApjtrhBsTtMpqmrgwL9XtMgbVRZPGcGFeKr968wA3XpBDcoItumnc5evN8Z1AZiALMeZs1Te3UdfcTlYYXXF0+c410zjR0MIv3yhyuxRjfA6OMcBuEXlVRFZ3Pfo7SUSWiMg+ESkSkXt62C8icr+zf7uIzPHa97iIVIjIzm7n3CsiR0Vkq/O4xsfPYMJcqK7D4YtZuSncXJDL4+8ctBUCjet8baq6198XFpFo4AFgMZ5Bg5tEZLWq7vY6bCmQ7zwuBB50vgL8FvgVPd+A/5mq/sTfmkx4K6lqBCB3VPgFB8C3l0zhlV3H+OYftvPHlQuIjfb17z5jBpev3XHXAYeAWOf7TcB7/Zw2DyhS1WJVbQWe5cwuvMuAJ9VjPZAiIlnOe/4NsIGGxmcl1U5wpIbnGmOjk+L5zxtmsK2khl9Zk5Vxka+9qr4A/BH4X2dTNvDnfk7LBrw7n5c62/w9pid3O01bj4vIqF5qXiEihSJSWFlZ6cNLmlBXUtXEsNjokFzAyVfXnj+WG2Zn88s39vPmvgq3yzERytdr3buAi4E6AFXdD6T3c05Pq+h075XlyzHdPQhMAmYB5cD/9HSQqj6sqgWqWpCWltbPS5pwUFLdSG7qsJBcwMkf/3nDDKZmjuArv9/C/uN2v8MMPV+Do8VpbgLAGQTY3y/4UiDX63kO0H1lGl+O+RBVPa6qHaraCTyCp0nMGEqqGskZFZ7NVN4S42J49LYC4mOjuf03myh1muiMGSq+Bsc6EfkuMExEFgN/AP7SzzmbgHwRyROROGA50L0n1mrgVqd31XygVlXL+3rRrnsgjhvwdBU2EU5VOVrdFLY3xrsbmzKM335uLvXNbdzyyPrTkzsaMxR8DY57gEpgB/BPwBrg+32doKrtwN3Aq8Ae4HlV3SUiK0VkpXPYGqAYKMJz9fClrvNF5BngXWCKiJSKyB3Orh+JyA4R2Q5cDnzdx89gwlhtUxv1Le1he2O8JzOyR/LUHRdSc6qNTz2ynmO1Nu+oGRri62BwZ0ZcVDXk7jQXFBRoYWGh22WYANpRWsvHfvUOD33mApbMiKyxqu8dqebWxzaSlhzPsyvmkzEi9GcGNsFBRDar6hnTS/V5xeE0Id0rIieAvcA+EakUkX8NVKHGDMQHXXEjo6nK25xxo3ji83OpqGvmlofXU1FnVx4msPprqvoant5Uc1V1tKqm4hmgd7GIWBORCRpdg/8i4eZ4Ty4Yn8oTn5/Hsbpmlj+ynpO2aqAJoP6C41bgFlU92LVBVYuBzzj7jAkKpdVNjEiIYeSwyJ0AsGBCKr/93DyOVjfxxaffo7W90+2STJjqLzhiVfVE943OfY7I/Qk1QcczhiMyrza8zctL5SefnMnGQ1X866qd2ITWJhD6C47WAe4zZkiVVDWSG6HNVN19bOZY7r78HJ7dVMKqrX0OizJmQPoLjpkiUtfDox44bygKNKY/nZ1KaXUTOREyhsMXX188mYLxo/jBqp2n12E3ZrD0GRyqGq2qI3p4JKuqNVWZoFBe10xLeyd5acPdLiVoREcJP71pFp2dyndf3GFNVmZQ2bzMJuQdOnEKgLzRFhzexo1O5JsfmcK69yt5dddxt8sxYcSCw4S8g05wTBhjwdHdrQvGMzUzmX9/aTdNrR1ul2PChAWHCXmHTpwiPiaKTBsxfYaY6Cjuve5cjtY08eS7h9wux4QJCw4T8g6dPMWE0cOJigrv6dQHav7E0SycnMaD6w5Q39zmdjkmDFhwmJB38MQpJoyxrrh9+dZHplDT2Majbx/s/2Bj+mHBYUJaR6dSUtVE3pgkt0sJaufljOSa8zJ57J2D1DbaVYc5OxYcJqSV1TTR2tFJnl1x9Ovuy/NpaGnn6Q2H3S7FhDgLDhPSirt6VFlX3H5NHzuCRVPSePydgzS3WQ8rM3AWHCaknR7DYV1xffLFhZM4eaqVPxSWuF2KCWEWHCakFVU0kBwfQ1pyvNulhIR5eanMHpfCw28X095hs+eagbHgMCHt/eP15GckIWJdcX0hIqxcOImSqiZe3nnM7XJMiLLgMCFLVXn/eD1TMpPdLiWkLJ6WQd6Y4Tz6drHNYWUGxILDhKwTDa1UN7aRn27B4Y+oKOGOS/LYVlrLxoNVbpdjQpAFhwlZ+4/XAzA5w4LDXzfOySF1eByPvF3sdikmBAU0OERkiYjsE5EiEbmnh/0iIvc7+7eLyByvfY+LSIWI7Ox2TqqIvCYi+52vowL5GUzwev90cNjgP38Ni4vms/PH8/qeCg5UNrhdjgkxAQsOEYkGHgCWAtOBW0RkerfDlgL5zmMF8KDXvt8CS3p46XuAtaqaD6x1npsI9H5FAymJsdajaoA+u2A8cTFRNg2J8VsgrzjmAUWqWqyqrcCzwLJuxywDnlSP9UCKiGQBqOrfgJ4aYJcBTzjfPwFcH4jiTfDbf7yeyenJ1qNqgMYkxXPjnBxeeK+UEw0tbpdjQkgggyMb8B5lVOps8/eY7jJUtRzA+Zre00EiskJECkWksLKy0q/CTfDz9KhqIN+aqc7KnZfm0dreyVPv2jQkxneBDI6e/gzs3vfPl2MGRFUfVtUCVS1IS0sbjJc0QeRoTRO1TW1MyxrhdikhbVJaEldNS+ep9YdtGhLjs0AGRymQ6/U8BygbwDHdHe9qznK+VpxlnSYE7SitBeC87JEuVxL6vnDpRKpOtfLCe6Vul2JCRCCDYxOQLyJ5IhIHLAdWdztmNXCr07tqPlDb1QzVh9XAbc73twGrBrNoExp2HK0lJkps8N8gmJeXysyckTz69kE6O21AoOlfwIJDVduBu4FXgT3A86q6S0RWishK57A1QDFQBDwCfKnrfBF5BngXmCIipSJyh7PrPmCxiOwHFjvPTYTZcbSWyRnJJMRGu11KyBMR7rx0IgdPnOL1PcfdLseEgJhAvriqrsETDt7bHvL6XoG7ejn3ll62nwSuHMQyTYhRVXYereUj0zPdLiVsLJ2RSXbKMB59+yAfOdf+u5q+2chxE3KO1jRR3djGjBy7vzFYYqKj+PwleWw8VMWWI9Vul2OCnAWHCTmbD3t+sc3OTXG3kDBz89xckhNibECg6ZcFhwk5mw5VkRQfY11xB1lSfAyfvnA8L+8sp6Sq0e1yTBCz4DAhZ9PBauaMH0V0lI0YH2y3XzSBmKgofvnGfrdLMUHMgsOElOpTrew7Xs+8CTa3ZSBkjkzgswvG88fNpadnHzamOwsOE1IKnfsbcyekulxJ+Lrr8nMYHhfDj17d53YpJkhZcJiQ8s7+ShJio5hpN8YDJnV4HCsXTeK13cfZdMgWejJnsuAwIUNVeWNfBZecM8YG/gXY5y6eQMaIeO5dvYv2jk63yzFBxoLDhIyiigZKqpq4fGqPEyKbQZQYF8O/Xnsuu8rqeMJmzjXdWHCYkPHGXs98lpdPseAYCtecl8miKWn89K/7KK9tcrscE0QsOEzIWLPzGOeOHcHYlGFulxIRRIR/XzaDDlW+/6edeGYIMsaCw4SIA5UNbCup4fpZ/a3zZQZTbmoi3756Kmv3VvD0hiNul2OChAWHCQl/3FxKlMCyWWPdLiXi3H7RBC6bnMZ/vLTbxnYYwILDhIDG1nZ+v+EIV03LIH1EgtvlRJyoKOEnnzyfpPgY7v79Fk61tLtdknGZBYcJes9uLKG2qY0vXDbR7VIiVnpyAj+7eRb7K+r55vPbbMGnCGfBYYJabWMb97+xn4smjaZgvE0z4qbLJqfx3Wum8cquY/zyjSK3yzEuCuhCTsZ019zWQUtbJ8Pjo4mJ7vvvFlXl+6t2UtfUxvc/Oh0Rm9TQbXdcksfusjp+9vr7TEwbzsdm2j2nSGTBYQJOVXlpezmPvXOQ7aU1dCrExURxfvZIlszIZOl5WWR362Lb2an8+K/7+Mu2Mv756ilMH2tTqAcDEeG/Pn4epdVNfOP5raQOj+Pic8a4XZYZYhIJfbMLCgq0sLDQ7TIiUnNbB994fitrdhwjPz2JpTMySUmMo7y2iX8cOMmusjoAZmSP4Iop6UxMS6K+uY0Xtxxly5EaPnXhOP5j2QyibAr1oFLb1MZND73L0Zomnl0xnxnZthpjOBKRzapacMZ2Cw4TKK3tndz+m428W3ySf1kylS9cOvGMNTQOnTjFyzuPsXbPcd47Uk3XPdecUcP4yhX5fLIgx5qogtSx2mZufPAftLR38sIXFzB+9HC3SzKDzILDgmPIfefFHTyz8Qg/+eRMPnFBTr/Hn2ppp7y2mYTYKLJThllghICiigY++dA/GDEslj+uvIi05Hi3SzKDqLfgCGivKhFZIiL7RKRIRO7pYb+IyP3O/u0iMqe/c0XkXhE5KiJbncc1gfwMZmBe3lHOMxuPsHLhJJ9CA2B4fAznpCeRMyrRQiNEnJOexOO3z6WiroXbf7OR+uY2t0syQyBgwSEi0cADwFJgOnCLiEzvdthSIN95rAAe9PHcn6nqLOexJlCfwQxMTWMrP1i1k3PHjuCbH5nsdjkmwGaPG8WDn5nDvmP1rHhyM81tHW6XZAIskFcc84AiVS1W1VbgWWBZt2OWAU+qx3ogRUSyfDzXBKmfv76fqlOt/PgTM4ntp8utCQ+LpqTzk0/O5N3ik3zt2a102ADBsBbIn+psoMTreamzzZdj+jv3bqdp63ER6XFUmIisEJFCESmsrKwc6Gcwfjp04hRPrz/MzXNzrQtthLl+djY/uHY6r+w6xg9W2Wy64SyQwdFTI3X3f0m9HdPXuQ8Ck4BZQDnwPz29uao+rKoFqlqQlpbmU8Hm7P34r/uIi4ni61dZE1UkuuOSPL64aBK/33CEn72+3+1yTIAEcgBgKZDr9TwHKPPxmLjezlXV410bReQR4KXBK9mcjaKKBtbsKOdLiybZZIQR7NtXT+FkQwv3r93PmKQ4bl0wwe2SzCAL5BXHJiBfRPJEJA5YDqzudsxq4Fand9V8oFZVy/s617kH0uUGYGcAP4Pxw0PrDhAfE8XnL85zuxTjIhHhv244j6umZfBvq3fxys5yt0sygyxgwaGq7cDdwKvAHuB5Vd0lIitFZKVz2BqgGCgCHgG+1Ne5zjk/EpEdIrIduBz4eqA+g/Hd0Zom/rzlKMvnjmN0kvXlj3Qx0VH86lOzmZWbwtee28qO0lq3SzKDyAYAmkFx7+pdPL3+MOu+ffkZ806ZyFVZ38L1D/yd9s5OVt11CZkjrQkzlLgyANBEhpMNLTy76Qg3zM620DAfkpYcz2O3F9DQ3M6dT26isdUWgQoHFhzmrD357mGa2zr5p4WT3C7FBKGpmSP45adms7usjm88Z4tAhQMLDnNWmts6eGr9Ya6als456Ulul2OC1BVTM/jeRz1jPH7y131ul2POkq3HYc7KC++VUnWqlS9casu6mr59/uIJFFU08Ou3DpA3ZjifLMjt/yQTlCw4zIB1diqPvn2QmTkjmZeX6nY5JsiJCP9n2bmUVDXy3T/tIHvUMC6aZItAhSJrqjID9vqe4xw8cYo7L51os9kan8RGR/HAp+cwYfRwVj61maKKBrdLMgNgwWEG7JG3i8lOGcbSGZlul2JCyMhhsTx++1xio6P4/G83cbKhxe2SjJ8sOMyAbDlSzaZD1dxxSR4xNgOu8VNuaiKP3FbA8bpmVjxlU7GHGvuJNwPy0LoDJCfEcNNcu8FpBmbOuFH89KZZbD5czVee2UJbR6fbJRkfWXAYv+0uq+PVXcf53MV5JMVb/wozcB89P4t7Pzadv+4+zjee32breIQI+6k3frt/7X6S42O4wyYzNIPg9ovzaG7v5L6X9xIfE8WPbjyfqCjrbBHMLDiMX/aU1/HKrmN8+YpzGJkY63Y5JkysXDiJ5rYOfv76fpraOvjpTTOJj4l2uyzTCwsO45f7Xt7rudq4xK42zOD66pX5JMZF819r9nKyoYWHby1gRIL9cRKM7B6H8dlb+ypY934lX7kyn5TEOLfLMWFGRFhx2SR+fvMsCg9Vc/0Df2ffsXq3yzI9sOAwPmlp7+A//t8exo9O5NaLxrtdjglj18/O5uk7L6SuqZ1lD7zDC5tLbf3yIGPBYXzyy7VFFFU08G8fm25tzybg5k8czZqvXML5OSl88w/bWPn0Zirqmt0uyzgsOEy/tpXU8OC6A9w4J4crpma4XY6JEOkjEvj9nRdyz9KpvLmvkqt+uo7nNh2xadmDgAWH6VNlfQtffHozGcnx/Ou1090ux0SYmOgoVi6cxMtfvZQpmcn8yws7uO6Bd1hffNLt0iKaBYfp1amWdv7pqUKqGlt55LYC635rXDMpLYnnVizgF8tnUdXQyvKH13PnE4XsPGprmbvBgsP0qLaxjdt/s5FtpbX87KZZnDt2pNslmQgXFSUsm5XNG99axD9fPYWNB09y7S/f4XO/2ch7R6rdLi+iSCT0VigoKNDCwkK3ywgZmw9X8/XntlJe28TPb57NR8/PcrskY85Q19zGU+8e5tG3i6lubGNmzkg+feF4rp2ZRWKcDVEbDCKyWVULztgeyOAQkSXAL4Bo4FFVva/bfnH2XwM0Arer6nt9nSsiqcBzwATgEHCTqvb554YFh292ldXy2NsHeXHLUbJGJvCrT83hgvGj3C7LmD6damnnD4Ul/G7DEfZXNJAYF83CyWlcfW4ml+aPYXRSvNslhqwhDw4RiQbeBxYDpcAm4BZV3e11zDXAl/EEx4XAL1T1wr7OFZEfAVWqep+I3AOMUtV/6asWC44Pa27roKaxjeN1zRRVNLCzrJa395+gqKKBhNgoblswgS9fmW8TGJqQoqpsOlTNqq1HeW33cSrqPet8jB+dyKzcFPLTkxg3eji5o4YxKjGOkcNiGTEslmibF6tXvQVHIH8zzAOKVLXYKeBZYBmw2+uYZcCT6kmv9SKSIiJZeK4mejt3GbDIOf8J4C2gz+AYqPvX7mf1trLTg49OR6x+6MsZ+/X0fj39vHs++3JOT/vpdX8vr9dte1tHJ81tH56+Oi4migvzUvn0heP4+OwcuwluQpKIMC8vlXl5qfz7shlsK61hw8EqthypZkNxFau2lvV43rDYaGKihdjoKGKiPF9jo+WMVS3PiBfp/Wm/5w6h//r4ecydMLhLOwcyOLKBEq/npXiuKvo7JrufczNUtRxAVctFJL2nNxeRFcAKgHHjxg3oA6QnxzMlI9l5wQ99Of0P44Pnfe//4Hzp4dgP9n3oebeTfT6vWw14HR8TJaQkxjEqMY4xSXFMTEti/OhEYm0xJhNGoqKE2eNGMXvcB02tja3tlFQ1UVrdSE1jG7VNnkdjazttHUp7ZyftHUprh+ert+7tMt1barTXJx/8MeiWYbGDP2A3kMHRU8h2/y/Y2zG+nNsnVX0YeBg8TVX+nNtl+bxxLJ83sNAxxgSXxLgYpmQmMyUz2e1SQl4g/8wsBbyXh8sBul8r9nZMX+ced5qzcL5WDGLNxhhj+hHI4NgE5ItInojEAcuB1d2OWQ3cKh7zgVqnGaqvc1cDtznf3wasCuBnMMYY003AmqpUtV1E7gZexdOl9nFV3SUiK539DwFr8PSoKsLTHfdzfZ3rvPR9wPMicgdwBPhkoD6DMcaYM9kAQGOMMT3qrTuudaUxxhjjFwsOY4wxfrHgMMYY4xcLDmOMMX6JiJvjIlIJHO62eQxwwoVyBsJqDQyrNTCs1sBwo9bxqprWfWNEBEdPRKSwp94CwchqDQyrNTCs1sAIplqtqcoYY4xfLDiMMcb4JZKD42G3C/CD1RoYVmtgWK2BETS1Ruw9DmOMMQMTyVccxhhjBsCCwxhjjF8iMjhE5FsioiIyxmvbd0SkSET2icjVbtbn1PNjEdkrIttF5E8ikuK1L6hqBRCRJU49Rc5a8EFDRHJF5E0R2SMiu0Tkq872VBF5TUT2O19H9fdaQ0VEokVki4i85DwPylqd5Z7/6Pxb3SMiC4K41q87//93isgzIpIQLLWKyOMiUiEiO7229Vqb278DIi44RCQXWIxnSvaubdPxrPlxLrAE+LWIDP56i/55DZihqucD7wPfgeCs1Xn/B4ClwHTgFqfOYNEOfFNVpwHzgbuc+u4B1qpqPrDWeR4svgrs8XoerLX+AnhFVacCM/HUHHS1ikg28BWgQFVn4FmuYTnBU+tv8fw8e+uxtmD4HRBxwQH8DPg2H16KdhnwrKq2qOpBPOuDzHOjuC6q+ldVbXeersezCiIEYa3O+xeparGqtgLP4qkzKKhquaq+53xfj+eXWzaeGp9wDnsCuN6VArsRkRzgo8CjXpuDrlYRGQFcBjwGoKqtqlpDENbqiAGGiUgMkIhnVdGgqFVV/wZUddvcW22u/w6IqOAQkeuAo6q6rduubKDE63mpsy1YfB542fk+GGsNxpp6JCITgNnABiDDWXES52u6i6V5+zmeP246vbYFY60TgUrgN06z2qMiMpwgrFVVjwI/wdPSUI5ntdG/EoS1eumtNtd/3gK2AqBbROR1ILOHXd8Dvgt8pKfTetgW8H7KfdWqqqucY76Hp6nld12n9XC8232qg7GmM4hIEvAC8DVVrRPpqWx3ici1QIWqbhaRRS6X058YYA7wZVXdICK/IAiapXri3B9YBuQBNcAfROQzrhY1cK7/vIVdcKjqVT1tF5Hz8Pyj2eb8wsgB3hOReXgSO9fr8Bw8l7EB1VutXUTkNuBa4Er9YMCNK7X2Ixhr+hARicUTGr9T1RedzcdFJEtVy0UkC6hwr8LTLgauE5FrgARghIg8TXDWWgqUquoG5/kf8QRHMNZ6FXBQVSsBRORF4CKCs9YuvdXm+s9bxDRVqeoOVU1X1QmqOgHPf/w5qnoMWA0sF5F4EckD8oGNLpaLiCwB/gW4TlUbvXYFXa3AJiBfRPJEJA7PjbvVLtd0mnj+UngM2KOqP/XatRq4zfn+NmDVUNfWnap+R1VznH+jy4E3VPUzBGetx4ASEZnibLoS2E0Q1oqniWq+iCQ6/x6uxHOvKxhr7dJbbe7/DlDViHwAh4AxXs+/BxwA9gFLg6C+IjztmFudx0PBWqtT0zV4en8dwNPU5npNXrVdgudSfrvXf89rgNF4eqvsd76mul1rt7oXAS853wdlrcAsoND5b/tnYFQQ1/pDYC+wE3gKiA+WWoFn8Nx7acPzR+0dfdXm9u8Am3LEGGOMXyKmqcoYY8zgsOAwxhjjFwsOY4wxfrHgMMYY4xcLDmOMMX6x4DAmwETkBvHMxjzV7VqMGQwWHMYE3i3AO3gG9BkT8iw4jAkgZ36si/EM6FrubIsSkV87a0O8JCJrROQTzr4LRGSdiGwWkVedqSaMCSoWHMYE1vV41qt4H6gSkTnAx4EJwHnAncACOD2f1i+BT6jqBcDjwH+6ULMxfQq7SQ6NCTK34JkmHTzrlNwCxAJ/UNVO4JiIvOnsnwLMAF5zJuKMxjMNhTFBxYLDmAARkdHAFcAMEVE8QaDAn3o7BdilqguGqERjBsSaqowJnE8AT6rqePXMypwLHAROADc69zoy8ExmCJ4J69JE5HTTlYic60bhxvTFgsOYwLmFM68uXgDG4pkBdSfwv3hWI6xVz7K7nwD+W0S24ZnF96Ihq9YYH9nsuMa4QESSVLXBac7aCFysnvUtjAl6do/DGHe8JCIpQBzw7xYaJpTYFYcxxhi/2D0OY4wxfrHgMMYY4xcLDmOMMX6x4DDGGOMXCw5jjDF++f/4ASl23cE0fAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic.Age.plot.density()\n",
    "plt.xlabel('Age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "eb66bc49-9803-4367-bb35-e592e58d60c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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T7Ot+fhWwGtiTBMa+cerInE4r9cCA67yX5BXA24DVSYqxIBfwuTO9BHiwqt48RyNKZ8UtFC0E7wE+UVWvrqqBqnoV8Ahjv33wt7q98OXAW7vnfxPoT/L8lkqSX5yPwaUXY8C1EKzn9KvtzwKXA48DDwD/ANwH/LCqnmYs+n+Z5OvA/cAvz9m0Uo+8lV4LWpKXVtWPu22WLwPXVtV353suqRfugWuhuyvJxcCFwF8Yb7XEK3BJapR74JLUKAMuSY0y4JLUKAMuSY0y4JLUqP8DMvDGPZEWDEQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic.Age.plot.box()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2038c603-c540-4107-986d-2edfac5e281b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Age'}, xlabel='Survived'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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j4gFJX6MXXTYRsQBYAMW1cVpaWvpSp+3O8mV4vVpD8TY74Crps38OeC4iHkjvb6MI/42SxgCk5021KdHMzPqrx7CPiA3As5KOTYOmAo8DS4EZadgM4I6aVGhmZv1W6fXsLwa+JWlP4CngIooviiWSZgJrgXNrU6KZmfVXRWEfEQ8Bu1wfmWIv38zMBjmfQWtmlgGHvZlZBhz2ZmYZcNibmWXAYW9mlgGHvZlZBhz2ZmYZcNibmWXAYW9mlgGHvZlZBhz2ZmYZcNibmWXAYW9mlgGHvZlZBhz2ZmYZcNibmWXAYW9mlgGHvZlZBiq6LaGkNcBrwA5ge0Q0SxoF3AqMA9YA50XES7Up08zM+qM3e/ZTIuKkiOi4F+0coC0ixgNt6b2ZmQ1C/enGaQUWpdeLgHP6XY2ZmdVEpWEfwApJqyXNSsOaImI9QHoeXYsCzcys/yrqswdOi4h1kkYDKyX9stIG0pfDLICmpiZKpVLvq7Qeeb1ao/E2O7AqCvuIWJeeN0m6HTgF2ChpTESslzQG2NTNvAuABQDNzc3R0tJSlcKtzPJleL1aQ/E2O+B67MaRtJ+k/TteA+8FHgWWAjPSZDOAO2pVpJmZ9U8le/ZNwO2SOqb/dkQsl/QgsETSTGAtcG7tyjQzs/7oMewj4ilgUhfDNwNTa1GUmZlVl8+gNTPLgMPezCwDDnszsww47M3MMuCwNzPLgMPezCwDDnszsww47M3MMuCwNzPLgMPezCwDDnszsww47M3MMuCwNzPLgMPezCwDDnszsww47M3MMuCwNzPLgMPezCwDDnszswxUHPaShkv6uaQfpPejJK2U9ER6Pqh2ZZqZWX/0Zs/+EqC97P0coC0ixgNt6b2ZmQ1CFYW9pMOBM4H/Vza4FViUXi8CzqlqZWZmVjWV7tn/M/AZ4A9lw5oiYj1Aeh5d3dLMzKxaRvQ0gaSzgE0RsVpSS28bkDQLmAXQ1NREqVTq7SKsAl6v1mi8zQ6sHsMeOA14v6T3AXsDfyLpZmCjpDERsV7SGGBTVzNHxAJgAUBzc3O0tLRUp3J70/JleL1aQ/E2O+AUEZVPXOzZfyoizpJ0JbA5IuZLmgOMiojP7G7+5ubmWLVqVX/qHfImfWEFr7z+Rs3bOWCfPXj48++teTs29HmbHVwkrY6I5s7DK9mz7858YImkmcBa4Nx+LMuSV15/gzXzz+zVPKVSqdd7SePmLOvV9Gbd8TbbGHoV9hFRAkrp9WZgavVLMjOzavMZtGZmGXDYm5llwGFvZpYBh72ZWQYc9mZmGXDYm5llwGFvZpYBh72ZWQYc9mZmGXDYm5llwGFvZpYBh72ZWQYc9mZmGXDYm5llwGFvZpYBh72ZWQYc9mZmGXDYm5llwGFvZpaBHsNe0t6SfirpYUmPSfpCGj5K0kpJT6Tng2pfrpmZ9UUle/bbgP8SEZOAk4AzJP05MAdoi4jxQFt6b2Zmg1CPYR+FLentHukRQCuwKA1fBJxTiwLNzKz/RlQykaThwGrgGODqiHhAUlNErAeIiPWSRncz7yxgFkBTUxOlUqkqhQ9lvV1HW7Zs6dN69b+FVYu32cGvorCPiB3ASZIOBG6XNLHSBiJiAbAAoLm5OVpaWvpQZkaWL6O366hUKvV6nr60Y9Ylb7MNoVdH40TEy0AJOAPYKGkMQHreVO3izMysOio5GuctaY8eSfsA7wZ+CSwFZqTJZgB31KhGMzPrp0q6ccYAi1K//TBgSUT8QNJ9wBJJM4G1wLk1rNPMzPqhx7CPiF8Af9bF8M3A1FoUZWZm1aWIGLDGmpubY9WqVQPWXiM6cdGJA9bWIzMeGbC2bOjyNju4SFodEc2dh1d0NI4NnNfa57Nm/pm9mqcvRzaMm7OsV9ObdcfbbGPwtXHMzDLgsDczy4DD3swsAw57M7MMOOzNzDLgsDczy4DD3swsAw57M7MMOOzNzDLgsDczy4DD3swsAw57M7MMOOzNzDLgsDczy4AvcTwI9elSrst7N88B++zR+zbMrGE57AeZ3l4XHIovh77MZ2b5qOSG40dIuktSu6THJF2Sho+StFLSE+n5oNqXa2ZmfVFJn/124H9GxATgz4FPSDoemAO0RcR4oC29NzOzQajHsI+I9RHxs/T6NaAdOAxoBRalyRYB59SoRjMz66deHY0jaRzwZ8ADQFNErIfiCwEYXfXqzMysKir+gVbSSOC7wKUR8aqkSuebBcwCaGpqolQq9aFM64nXq9VTb7e/LVu29Gmb9XbedxWFvaQ9KIL+WxHxr2nwRkljImK9pDHApq7mjYgFwAKA5ubm6O0d5a0Cy5fh9Wp104ftr1Qq9X6b9XbeL5UcjSNgIdAeEVeVjVoKzEivZwB3VL88MzOrhkr27E8DPgQ8IumhNOwfgPnAEkkzgbXAuTWp0MwGPZ8IOPj1GPYRcQ/QXQf91OqWY2aNxicCNgZfG8fMLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDDjszcwy0GPYS7pe0iZJj5YNGyVppaQn0vNBtS3TzMz6o5I9+xuBMzoNmwO0RcR4oC29NzOzQarHsI+Iu4EXOw1uBRal14uAc6pblpmZVVNf++ybImI9QHoeXb2SzMys2kbUugFJs4BZAE1NTZRKpVo3mSWvV2s03mYHVl/DfqOkMRGxXtIYYFN3E0bEAmABQHNzc7S0tPSxSevW8mV4vVpD8TY74PrajbMUmJFezwDuqE45ZmZWC5UcerkYuA84VtJzkmYC84H3SHoCeE96b2Zmg1SP3TgRMb2bUVOrXIuZmdWIz6A1M8uAw97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOezOzDPQr7CWdIelXkp6UNKdaRZmZWXX1OewlDQeuBv4SOB6YLun4ahVmZmbV0589+1OAJyPiqYj4PXAL0FqdsszMrJpG9GPew4Bny94/B7yr80SSZgGzAJqamiiVSv1oMm9Tpkzpdpy+3P18d911Vw2qMeuZt9nBoz9hry6GxS4DIhYACwCam5ujpaWlH03mLWKX1QtAqVTC69UGI2+zg0d/unGeA44oe384sK5/5ZiZWS30J+wfBMZLequkPYHzgaXVKcvMzKqpz904EbFd0t8CPwSGA9dHxGNVq8zMzKqmP332RMS/Af9WpVrMzKxGfAatmVkGHPZmZhlw2JuZZcBhb2aWAXV30kNNGpOeB54ZsAbzcQjwQr2LMOsFb7O1c1REvKXzwAENe6sNSasiornedZhVytvswHM3jplZBhz2ZmYZcNgPDQvqXYBZL3mbHWDuszczy4D37M3MMuCwb3C+D7A1EknXS9ok6dF615Ibh30D832ArQHdCJxR7yJy5LBvbL4PsDWUiLgbeLHedeTIYd/YuroP8GF1qsXMBjGHfWOr6D7AZmYO+8bm+wCbWUUc9o3N9wE2s4o47BtYRGwHOu4D3A4s8X2AbTCTtBi4DzhW0nOSZta7plz4DFozswx4z97MLAMOezOzDDjszcwy4LA3M8uAw97MLAMOexsyJM2V9JikX0h6SNK7qrDM91fraqKStlRjOWZ94UMvbUiQdCpwFdASEdskHQLsGRE9nlEsaUQ6Z6HWNW6JiJG1bsesK96zt6FiDPBCRGwDiIgXImKdpDUp+JHULKmUXl8haYGkFcBNkh6QdELHwiSVJJ0s6UJJ/yLpgLSsYWn8vpKelbSHpKMlLZe0WtJPJB2XpnmrpPskPSjpiwO8Psx24rC3oWIFcISkX0v6hqTTK5jnZKA1Ij5AcXno8wAkjQHGRsTqjgkj4hXgYaBjuWcDP4yINyjup3pxRJwMfAr4Rprma8D/jYh3Ahv6/QnN+sFhb0NCRGyhCO9ZwPPArZIu7GG2pRHxenq9BDg3vT4P+E4X098K/HV6fX5qYyTwn4DvSHoIuJbirwyA04DF6fU3e/N5zKptRL0LMKuWiNgBlICSpEeAGcB23typ2bvTLFvL5v2NpM2S/pQi0D/aRRNLgf8taRTFF8udwH7AyxFxUndl9e3TmFWX9+xtSJB0rKTxZYNOAp4B1lAEM8Bf9bCYW4DPAAdExCOdR6a/Hn5K0T3zg4jYERGvAk9LOjfVIUmT0iz/TvEXAMAFvf5QZlXksLehYiSwSNLjkn5BcU/eK4AvAF+T9BNgRw/LuI0inJfsZppbgQ+m5w4XADMlPQw8xpu3hrwE+ISkB4EDevdxzKrLh16amWXAe/ZmZhlw2JuZZcBhb2aWAYe9mVkGHPZmZhlw2JuZZcBhb2aWAYe9mVkG/j+HhzYqY9IVRgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic.dropna().boxplot(column='Age', by='Survived')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b04ec649-789d-49e7-96a2-ccd1de540bf1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Age'}, xlabel='Sex'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic.dropna().boxplot(column='Age', by='Sex')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29f56706-df9c-4800-8908-861311b9b36a",
   "metadata": {},
   "source": [
    "### Titanic Survival Rates by Sex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "72431628-eb92-4dc9-ae1b-2d908e5edf94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sex_count = titanic.dropna().Sex.value_counts()\n",
    "\n",
    "mask_sex_f = titanic['Sex'] == 'female'\n",
    "mask_sex_m = titanic['Sex'] == 'male'\n",
    "\n",
    "f_survaval = titanic.loc[mask_sex_f, 'Survived'].value_counts()[1]\n",
    "m_survaval = titanic.loc[mask_sex_m, 'Survived'].value_counts()[1]\n",
    "\n",
    "rate = [f_survaval / float(sex_count['female']),\n",
    "        m_survaval / float(sex_count['male'])]\n",
    "plt.bar(list(range(2)), rate, color='blue', align='center')\n",
    "plt.xticks(list(range(2)), ['male', 'female'])\n",
    "plt.xlabel('Sex')\n",
    "plt.ylabel('propution Survived')\n",
    "plt.title('Titanic Survival Rates by Sex')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3449c3dd-3fcb-4094-be06-a66ebe9f03d3",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### Scatterplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ec12f950-981a-469d-8bdd-bf011c754572",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6e4eb41a-51cf-4e94-a40e-bab1668f1050",
   "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>speal_lengh</th>\n",
       "      <th>speal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   speal_lengh  speal_width  petal_length  petal_width       target\n",
       "0          5.1          3.5           1.4          0.2  Iris-setosa\n",
       "1          4.9          3.0           1.4          0.2  Iris-setosa\n",
       "2          4.7          3.2           1.3          0.2  Iris-setosa\n",
       "3          4.6          3.1           1.5          0.2  Iris-setosa\n",
       "4          5.0          3.6           1.4          0.2  Iris-setosa"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_filename = 'datasets-uci-iris.csv'\n",
    "iris = pd.read_csv(iris_filename, header=None,\n",
    "                   names=['speal_lengh', 'speal_width',\n",
    "                          'petal_length', 'petal_width', 'target'])\n",
    "iris.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "40e774df-e21c-4b00-9faa-27b1365cab89",
   "metadata": {},
   "outputs": [],
   "source": [
    "v = iris.target.unique()\n",
    "m_1 = iris['target'] == v[0]\n",
    "m_2 = iris['target'] == v[1]\n",
    "m_3 = iris['target'] == v[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b21b9082-bbf7-4749-9de6-39e146b63267",
   "metadata": {},
   "outputs": [],
   "source": [
    "iris.loc[m_1, 'target'] = 0\n",
    "iris.loc[m_2, 'target'] = 1\n",
    "iris.loc[m_3, 'target'] = 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "867857da-6e61-4bdf-82ba-f9c22329e296",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    50\n",
       "1    50\n",
       "2    50\n",
       "Name: target, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.target.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "702923cd-2d15-4e17-a365-a691151accba",
   "metadata": {},
   "outputs": [],
   "source": [
    "colour_palette = {0: 'red', 1: 'blue', 2: 'green'}\n",
    "colours = [colour_palette[c] for c in iris['target']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f0219627-97cd-40cb-95af-f524e205a404",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "iris.plot.scatter(x=0, y=1, c=colours)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e4f49ce5-ee6e-4cc8-8863-7dc1eb96ca2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='speal_lengh', ylabel='speal_width'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "iris.plot.hexbin(x=0, y=1, gridsize=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "38ca07ef-a9bd-4ef0-998c-933ac4e09af9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:xlabel='speal_lengh', ylabel='speal_lengh'>,\n",
       "        <AxesSubplot:xlabel='speal_width', ylabel='speal_lengh'>,\n",
       "        <AxesSubplot:xlabel='petal_length', ylabel='speal_lengh'>,\n",
       "        <AxesSubplot:xlabel='petal_width', ylabel='speal_lengh'>],\n",
       "       [<AxesSubplot:xlabel='speal_lengh', ylabel='speal_width'>,\n",
       "        <AxesSubplot:xlabel='speal_width', ylabel='speal_width'>,\n",
       "        <AxesSubplot:xlabel='petal_length', ylabel='speal_width'>,\n",
       "        <AxesSubplot:xlabel='petal_width', ylabel='speal_width'>],\n",
       "       [<AxesSubplot:xlabel='speal_lengh', ylabel='petal_length'>,\n",
       "        <AxesSubplot:xlabel='speal_width', ylabel='petal_length'>,\n",
       "        <AxesSubplot:xlabel='petal_length', ylabel='petal_length'>,\n",
       "        <AxesSubplot:xlabel='petal_width', ylabel='petal_length'>],\n",
       "       [<AxesSubplot:xlabel='speal_lengh', ylabel='petal_width'>,\n",
       "        <AxesSubplot:xlabel='speal_width', ylabel='petal_width'>,\n",
       "        <AxesSubplot:xlabel='petal_length', ylabel='petal_width'>,\n",
       "        <AxesSubplot:xlabel='petal_width', ylabel='petal_width'>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x1152 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import scatter_matrix\n",
    "\n",
    "scatter_matrix(iris, alpha=0.2, figsize=(16, 16), c=colours, diagonal='hist')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6562c70-58bb-47eb-9ce2-328ea6a66f5c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9 (XPython)",
   "language": "python",
   "name": "xpython"
  },
  "language_info": {
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "version": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}