{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1a7c05e7",
   "metadata": {},
   "source": [
    "# Plotting with Pandas\n",
    "\n",
    "The <tt>Seaborn</tt> plotting library is designed to be used with Pandas.\n",
    "\n",
    "For example, if we want to plot one variable (say age) separately based on another variable (say, which class someone travelled in), we can do it very easily with <tt>Seaborn</tt>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c691267",
   "metadata": {},
   "source": [
    "## Example: Titanic data\n",
    "\n",
    "Let's use the Titanic passenger data again!\n",
    "\n",
    "<img src=\"https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook/main/images/titanic.jpg\" width=50% alt=\"Picture of the Titanic\" />\n",
    "\n",
    "By the way you can find a description of the dataset including explanations of some of the less obvious column titles, on <a href=\"https://www.kaggle.com/c/titanic/data\">kaggle</a> - a data science website that I got the data from\n",
    "\n",
    "### Set up Python libraries\n",
    "\n",
    "As usual, run the code cell below to import the relevant Python libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2d8ecdb6",
   "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": "0f139f98",
   "metadata": {},
   "source": [
    "### Load the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "90f9152e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</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>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</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>8.0500</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\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>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>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>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>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 × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass                                               Name  \\\n",
       "0           0       3                            Braund, Mr. Owen Harris   \n",
       "1           1       1  Cumings, Mrs. John Bradley (Florence Briggs Th...   \n",
       "2           1       3                             Heikkinen, Miss. Laina   \n",
       "3           1       1       Futrelle, Mrs. Jacques Heath (Lily May Peel)   \n",
       "4           0       3                           Allen, Mr. William Henry   \n",
       "..        ...     ...                                                ...   \n",
       "886         0       2                              Montvila, Rev. Juozas   \n",
       "887         1       1                       Graham, Miss. Margaret Edith   \n",
       "888         0       3           Johnston, Miss. Catherine Helen \"Carrie\"   \n",
       "889         1       1                              Behr, Mr. Karl Howell   \n",
       "890         0       3                                Dooley, Mr. Patrick   \n",
       "\n",
       "        Sex   Age  SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
       "0      male  22.0      1      0         A/5 21171   7.2500   NaN        S  \n",
       "1    female  38.0      1      0          PC 17599  71.2833   C85        C  \n",
       "2    female  26.0      0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3    female  35.0      1      0            113803  53.1000  C123        S  \n",
       "4      male  35.0      0      0            373450   8.0500   NaN        S  \n",
       "..      ...   ...    ...    ...               ...      ...   ...      ...  \n",
       "886    male  27.0      0      0            211536  13.0000   NaN        S  \n",
       "887  female  19.0      0      0            112053  30.0000   B42        S  \n",
       "888  female   NaN      1      2        W./C. 6607  23.4500   NaN        S  \n",
       "889    male  26.0      0      0            111369  30.0000  C148        C  \n",
       "890    male  32.0      0      0            370376   7.7500   NaN        Q  \n",
       "\n",
       "[891 rows x 11 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic = pandas.read_csv('https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook/main/data/titanic_2.csv')\n",
    "display(titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11c3973c",
   "metadata": {},
   "source": [
    "### Grouping by a categorical variable\n",
    "\n",
    "Say we want to plot the distribution of age separately in each travel class on the titanic. \n",
    "\n",
    "We can do this using the \"hue\" argument in <tt>sns.histplot</tt> or <tt>sns.kdeplot</tt>:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "79565516",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Age', ylabel='Count'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data=titanic, x='Age', hue='Pclass')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a88989e6",
   "metadata": {},
   "source": [
    "Hm, that was a bit messy - it looks clearer as a kdeplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a9f0c0fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code here to produce the KDEplot version of the above"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5705f36b",
   "metadata": {},
   "source": [
    "You may notice in the KDEplot it appears as though there were many people with an age below zero.\n",
    "\n",
    "Glance back at this histogram - you will see that there are not in fact any people with age <0, but there is a big spike in the passenger counts for young children, which gets smoothed out in the KDE plot resulting in the KDE plot extending below zero.\n",
    "\n",
    "### Countplot\n",
    "\n",
    "The simple plotting function <tt>sns.countplot</tt> shows the frequencies of different categories:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d04ded5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Pclass', ylabel='count'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=titanic, x='Pclass')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ba05f43",
   "metadata": {},
   "source": [
    "... we can break the data down by a second category using the argument <tt>hue</tt> as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cbcadd2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Pclass', ylabel='count'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=titanic, x='Pclass', hue='Survived')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d211994e",
   "metadata": {},
   "source": [
    "Hm, looks like being in 3rd class was not good news on the Titanic.\n",
    "\n",
    "### Barplot\n",
    "\n",
    "If we want to plot the mean value of a variable by category (rather than just the count in each category), we can use the function <tt>barplot</tt>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6d25172f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Pclass', ylabel='Age'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=titanic, y='Age', x='Pclass')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb9ad4aa",
   "metadata": {},
   "source": [
    "However, in many cases it will be more informative to plot a <tt>boxplot</tt> or <tt>violinplot</tt>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "13f78289",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Pclass', ylabel='Age'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(data=titanic, x='Pclass', y=\"Age\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3eebe0c6",
   "metadata": {},
   "source": [
    "Once again you can use the argument <tt>hue</tt> to break the data down by another category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c3f3822e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here for a barplot of age, broken down by class, \n",
    "# and further broken down by whether the passenger survived - \n",
    "# base it on the countplot example above"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c0daf76",
   "metadata": {},
   "source": [
    "### Scatterplot\n",
    "\n",
    "We can use similar tricks in a scatterplot.\n",
    "\n",
    "Let's plot a scatterplot of age against fare paid:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1d1f6b62",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Fare', ylabel='Age'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=titanic, x='Fare', y='Age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "22f68461",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your code here to repeat the scatterplot above but plotting different classes in different colours, using 'hue'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9db57330",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}