DAY24Titanic-AIML.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TITANIC DATASET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import tree\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"titanic_eda/train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": true
   },
   "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": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29.69911764705882"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Age\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_age=np.where(df[\"Age\"].isnull(),29,df[\"Age\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Age\"]=new_age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_encoder=preprocessing.LabelEncoder()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "encoded_sex=label_encoder.fit_transform(df[\"Sex\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "tree_model=tree.DecisionTreeClassifier()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier()"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " tree_model.fit(X=pd.DataFrame(encoded_sex),y=df[\"Survived\"])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "# with open (\"DTree4.dot\",\"w\") as f:\n",
    "#     f=tree.export_graphviz(tree_model,feature_names=[\"Age\"],out_file=f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "predict=pd.DataFrame([encoded_sex,df[\"Age\"],df[\"Fare\"]]).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "tree_model=tree.DecisionTreeClassifier(max_depth=6)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(max_depth=6)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_model.fit(X=predict,y=df[\"Survived\"]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open (\"DTree4.dot\",\"w\") as f:\n",
    "    f=tree.export_graphviz(tree_model,feature_names=[\"Age\",\"Sex\",\"Fare\"],out_file=f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8249158249158249"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_model.score(X=predict,y=df[\"Survived\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test=pd.read_csv(\"titanic_eda/test.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_age=np.where(df_test[\"Age\"].isnull(),29,df_test[\"Age\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35.627188489208635"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test[\"Age\"]=new_age\n",
    "df_test[\"Fare\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_fare=np.where(df_test[\"Fare\"].isnull(),35,df_test[\"Fare\"])\n",
    "df_test[\"Fare\"]=new_fare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "encoded_sexx=label_encoder.fit_transform(df_test[\"Sex\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_features=pd.DataFrame([encoded_sexx,df_test[\"Age\"],df_test[\"Fare\"]]).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_predict=tree_model.predict(X=test_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "predict_output=pd.DataFrame({\"PassengerId\":df_test[\"PassengerId\"],\"Survived\":test_predict})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "predict_output.to_csv(\"output_assignment.csv\",index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(\"titanicdataset_output.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}