{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dac0a1e3",
   "metadata": {},
   "source": [
    "# Python skills check\n",
    "\n",
    "Here we will review all the Python skills you should know by the end of this week"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "554bd33b",
   "metadata": {},
   "source": [
    "### Set up Python libraries\n",
    "\n",
    "As usual, run the code cell below to import the relevant Python libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6e215164",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set-up Python libraries - you need to run this but you don't need to change it\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as stats\n",
    "import pandas \n",
    "import seaborn as sns\n",
    "sns.set_theme()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10405553",
   "metadata": {},
   "source": [
    "### Load the data\n",
    "\n",
    "<img src=\"https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook/main/images/titanic.jpg\" width=50% alt=\"Picture of the Titanic\" />\n",
    "\n",
    "<br>\n",
    "<br>\n",
    "\n",
    "Let's load some data about the passengers of the Titanic from the file \"data/titanic.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "efd6c290",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>Unnamed: 0</th>\n",
       "      <th>PassengerId</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",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
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       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
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       "      <td>A/5 21171</td>\n",
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       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\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>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\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>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>886</td>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>887</td>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>B42</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>888</td>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>889</td>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>C148</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>890</td>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0  PassengerId  Survived  Pclass  \\\n",
       "0             0            1         0       3   \n",
       "1             1            2         1       1   \n",
       "2             2            3         1       3   \n",
       "3             3            4         1       1   \n",
       "4             4            5         0       3   \n",
       "..          ...          ...       ...     ...   \n",
       "886         886          887         0       2   \n",
       "887         887          888         1       1   \n",
       "888         888          889         0       3   \n",
       "889         889          890         1       1   \n",
       "890         890          891         0       3   \n",
       "\n",
       "                                                  Name     Sex   Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
       "..                                                 ...     ...   ...    ...   \n",
       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
       "\n",
       "     Parch            Ticket     Fare Cabin Embarked  \n",
       "0        0         A/5 21171   7.2500   NaN        S  \n",
       "1        0          PC 17599  71.2833   C85        C  \n",
       "2        0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3        0            113803  53.1000  C123        S  \n",
       "4        0            373450   8.0500   NaN        S  \n",
       "..     ...               ...      ...   ...      ...  \n",
       "886      0            211536  13.0000   NaN        S  \n",
       "887      0            112053  30.0000   B42        S  \n",
       "888      2        W./C. 6607  23.4500   NaN        S  \n",
       "889      0            111369  30.0000  C148        C  \n",
       "890      0            370376   7.7500   NaN        Q  \n",
       "\n",
       "[891 rows x 13 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic = pandas.read_csv('https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook/main/data/titanic.csv')\n",
    "display(titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e7aafdf",
   "metadata": {},
   "source": [
    "You can find some information abbout this dataset on <a href=\"https://www.kaggle.com/competitions/titanic/data\">Kaggle</a> including explanations of the less obvious column headers\n",
    "\n",
    "### Get descriptives\n",
    "\n",
    "Let's get some descriptive statistics, just for practice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b97861c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# How many people were in each class? Hint - use df.value_counts() which we saw on the page on data cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a7c6c2f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# What was the mean fare in each class? Hint- use .mean() and .groupby()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "173b1660",
   "metadata": {},
   "outputs": [],
   "source": [
    "# What was the standard deviation of fare in each class? Hint- use .std() and .groupby()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "214c7855",
   "metadata": {},
   "outputs": [],
   "source": [
    "# What was the 10th and 90th centile of age overall?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4642f6b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# display rows 400-420 of the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "8472eea7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# display only passengers under 12 years old"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bb8eb080",
   "metadata": {},
   "outputs": [],
   "source": [
    "# display only passengers whose age is unknown (NaN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "3a992d21",
   "metadata": {},
   "outputs": [],
   "source": [
    "# count how many passengers' age was unknown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "1f9ca5d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# display only passengers over 70 years old"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b46f3365",
   "metadata": {},
   "source": [
    "Wait a minute!\n",
    "\n",
    "There was something strange in that last dataframe. Maybe someone's age was mis-recorded?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "c6ac34e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Charters, Mr. David</td>\n",
       "      <td>male</td>\n",
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       "      <td>A/5. 13032</td>\n",
       "      <td>7.7333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
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       "    <tr>\n",
       "      <th>422</th>\n",
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       "      <td>423</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Zimmerman, Mr. Leo</td>\n",
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       "      <td>290.0</td>\n",
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       "      <td>7.8750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>423</td>\n",
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       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria ...</td>\n",
       "      <td>female</td>\n",
       "      <td>28.0</td>\n",
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       "      <td>1</td>\n",
       "      <td>347080</td>\n",
       "      <td>14.4000</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>424</td>\n",
       "      <td>425</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Rosblom, Mr. Viktor Richard</td>\n",
       "      <td>male</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>370129</td>\n",
       "      <td>20.2125</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0  PassengerId  Survived  Pclass  \\\n",
       "420         420          421         0       3   \n",
       "421         421          422         0       3   \n",
       "422         422          423         0       3   \n",
       "423         423          424         0       3   \n",
       "424         424          425         0       3   \n",
       "\n",
       "                                                  Name     Sex    Age  SibSp  \\\n",
       "420                             Gheorgheff, Mr. Stanio    male    NaN      0   \n",
       "421                                Charters, Mr. David    male   21.0      0   \n",
       "422                                 Zimmerman, Mr. Leo    male  290.0      0   \n",
       "423  Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria ...  female   28.0      1   \n",
       "424                        Rosblom, Mr. Viktor Richard    male   18.0      1   \n",
       "\n",
       "     Parch      Ticket     Fare Cabin Embarked  \n",
       "420      0      349254   7.8958   NaN        C  \n",
       "421      0  A/5. 13032   7.7333   NaN        Q  \n",
       "422      0      315082   7.8750   NaN        S  \n",
       "423      1      347080  14.4000   NaN        S  \n",
       "424      1      370129  20.2125   NaN        S  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replace the misrecorded age with NaN - hint - check the page on data cleaning\n",
    "\n",
    "# and display the relevant part of the dataframe to check\n",
    "titanic[420:425]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1acd658",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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