Quartiles.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quartiles and IQR\n",
    "Quartiles, as the name suggests divide the sample into 4 parts.\n",
    "\n",
    "- Sort the data\n",
    "- Find median (Mark this as quartile Q2)\n",
    "- Find median of left sample (Mark this as quartile Q1)\n",
    "- Find median of right sample (Mark this as quartile Q3)\n",
    "\n",
    "An important measure associated with this is the IQR (inter quartile range) which is given by :\n",
    "> IQR = Q3 - Q1\n",
    "\n",
    "IQR gives a general idea of the range and localization of our sample. Better than these banal numbers, we plot interesting graphs called - box and whisker plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import datasets\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score\n",
    "sns.set_style('dark')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "iris = datasets.load_iris()\n",
    "X = pd.DataFrame(iris.data)\n",
    "y = iris.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature 0 \n",
      " Q1: 5.1 \t Q2: 5.8 \t Q3: 6.4 \t IQR: 1.3000000000000007\n",
      "Feature 1 \n",
      " Q1: 2.8 \t Q2: 3.0 \t Q3: 3.3 \t IQR: 0.5\n",
      "Feature 2 \n",
      " Q1: 1.6 \t Q2: 4.35 \t Q3: 5.1 \t IQR: 3.4999999999999996\n",
      "Feature 3 \n",
      " Q1: 0.3 \t Q2: 1.3 \t Q3: 1.8 \t IQR: 1.5\n"
     ]
    }
   ],
   "source": [
    "for i, col in enumerate(X.columns):\n",
    "    q1, q2, q3 = X[col].quantile(0.25),\\\n",
    "                              X[col].quantile(0.5),\\\n",
    "                              X[col].quantile(0.75)\n",
    "    IQR = q3 - q1\n",
    "    print(f\"Feature {col} \\n Q1: {q1} \\t Q2: {q2} \\t Q3: {q3} \\t IQR: {IQR}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Box plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, col in enumerate(X.columns):\n",
    "    plt.figure(i)\n",
    "    sns.boxplot(X[col], palette=\"inferno\")\n",
    "    plt.title(f\"Feature: {col}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Box plot with histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, col in enumerate(X.columns):\n",
    "    plt.figure(i)\n",
    "    f, (ax_box, ax_hist) = plt.subplots(2, sharex=True, gridspec_kw={\"height_ratios\": (1, 4)})\n",
    "    plt.title(f\"Feature: {col}\")\n",
    "    sns.boxplot(X[col], palette=\"coolwarm\", ax=ax_box)\n",
    "    ax_box.set(xlabel='')\n",
    "    sns.distplot(X[col], ax=ax_hist)\n",
    "    ax_hist.set(xlabel='')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}