{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6f5180f8",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "    \n",
    " \n",
    "# 🌲 Decision Tree Visualization\n",
    "    \n",
    " 👨‍🏫 **Vikesh K**      \n",
    " 📓 **Lab-08**\n",
    "  \n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d15a23d6",
   "metadata": {},
   "source": [
    " 💡  <span style='font-family:Georgia'>\n",
    "    <font color= darkred> **\"However difficult life may seem, there is always something you can do and succeed at.-Stephen Hawking\"**\n",
    "    </font> 💡   "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aad6cac7",
   "metadata": {},
   "source": [
    "## 📝Lab Agenda\n",
    "\n",
    "* Plotting of Decision Tree Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98231f78",
   "metadata": {},
   "source": [
    "## Importing modules and data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "c0c3187d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "from sklearn import tree\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import numpy as np\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "e350d844",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"https://raw.githubusercontent.com/vkoul/data/main/misc/titanic.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "ce664287",
   "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>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",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\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>2</td>\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>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>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>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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         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",
       "   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  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "675e1a84",
   "metadata": {},
   "source": [
    "## Data Prep\n",
    "\n",
    "We will focus only on Numerical columns to keep the analysis straightforward"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "f6d9bd56",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_cols = df.select_dtypes([\"int\", \"float\"]).drop(columns = ['PassengerId']).columns.to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "087761e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_num = df[num_cols].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93a4dfd1",
   "metadata": {},
   "source": [
    "**Filling in the missing value with median age**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "33e1d321",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived      0\n",
       "Pclass        0\n",
       "Age         177\n",
       "SibSp         0\n",
       "Parch         0\n",
       "Fare          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_num.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "fd3d4b72",
   "metadata": {},
   "outputs": [],
   "source": [
    "median_age = df_num['Age'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "cdee85a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_num['Age'] = df_num['Age'].fillna(median_age)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2e364bc",
   "metadata": {},
   "source": [
    "## Prepare the X and y data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "84b1fc15",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df_num.drop(columns = ['Survived'])\n",
    "y = df_num['Survived']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b65708d5",
   "metadata": {},
   "source": [
    "## Model Fitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "d62cc28a",
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = DecisionTreeClassifier(max_depth = 2) # using depth of 2 to plot it properly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "4b104520",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      ],
      "text/plain": [
       "DecisionTreeClassifier(max_depth=2)"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.fit(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8734ff2",
   "metadata": {},
   "source": [
    "## Plotting the decision tree\n",
    "\n",
    "* https://scikit-learn.org/stable/modules/generated/sklearn.tree.plot_tree.html\n",
    "* https://scikit-learn.org/stable/auto_examples/tree/plot_unveil_tree_structure.html#sphx-glr-auto-examples-tree-plot-unveil-tree-structure-py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "bb22c265",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking the depth\n",
    "dt.tree_.max_depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "ca0811a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = list(x.columns) # save the column names as features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c8130f7",
   "metadata": {},
   "source": [
    "**Decision Tree Plotting**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "1fa736b0",
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "\n",
    "tree.plot_tree(dt\n",
    "               , feature_names = features # name of the features\n",
    "               , max_depth = 5\n",
    "               , filled= True # for color\n",
    "               , fontsize= 9\n",
    "               , node_ids = True # show the node number\n",
    "               , class_names= [\"Not\", \"Survived\"]) # Names of each of the target classes in ascending numerical order.\n",
    "# show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2a432a5",
   "metadata": {},
   "source": [
    "**The chart is read, top to bottom, from left to right. Hence the Nodes are also ordered in the same manner**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8bb19e1",
   "metadata": {},
   "source": [
    "**Verification of the numbers based on the chart**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "8cfb8e54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "400"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_num.query(\"Pclass <= 2.5\").shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "548997a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "297"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_num.query(\"Pclass <= 2.5 & Parch <= 0.5\").shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "40bcf570",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_num.query(\"Pclass <= 2.5 & Parch <= 0.5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "55aefe87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "103"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_num.query(\"Pclass <= 2.5 & Parch > 0.5\").shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "a7c672fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "876"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_num.query(\"Parch <= 2.5\").shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "d9f36e68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived\n",
       "0    549\n",
       "1    342\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.value_counts()"
   ]
  }
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