From 4f30e7334378707fd527dcde227e8595688793b4 Mon Sep 17 00:00:00 2001 From: faezakamran Date: Sun, 22 Aug 2021 16:14:47 +0500 Subject: [PATCH] Pclass wise average age calculations added --- titanic-dataset-eda.ipynb | 1469 +++++++++++++++++++++++++++++++++++++ 1 file changed, 1469 insertions(+) create mode 100644 titanic-dataset-eda.ipynb diff --git a/titanic-dataset-eda.ipynb b/titanic-dataset-eda.ipynb new file mode 100644 index 0000000..0d91c19 --- /dev/null +++ b/titanic-dataset-eda.ipynb @@ -0,0 +1,1469 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "c3712364", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", + "execution": { + "iopub.execute_input": "2021-08-20T01:43:14.788930Z", + "iopub.status.busy": "2021-08-20T01:43:14.788029Z", + "iopub.status.idle": "2021-08-20T01:43:15.691606Z", + "shell.execute_reply": "2021-08-20T01:43:15.690844Z", + "shell.execute_reply.started": "2021-08-20T00:57:12.467616Z" + }, + "papermill": { + "duration": 0.937281, + "end_time": "2021-08-20T01:43:15.691766", + "exception": false, + "start_time": "2021-08-20T01:43:14.754485", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/titanic/train.csv\n", + "/kaggle/input/titanic/test.csv\n", + "/kaggle/input/titanic/gender_submission.csv\n" + ] + } + ], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load\n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "# Input data files are available in the read-only \"../input/\" directory\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n", + "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "9b7d1704", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:15.735561Z", + "iopub.status.busy": "2021-08-20T01:43:15.734799Z", + "iopub.status.idle": "2021-08-20T01:43:15.780302Z", + "shell.execute_reply": "2021-08-20T01:43:15.779580Z", + "shell.execute_reply.started": "2021-08-20T00:57:12.477632Z" + }, + "papermill": { + "duration": 0.069009, + "end_time": "2021-08-20T01:43:15.780451", + "exception": false, + "start_time": "2021-08-20T01:43:15.711442", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
\n", + "
" + ], + "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": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train = pd.read_csv('/kaggle/input/titanic/train.csv')\n", + "train.head()" + ] + }, + { + "cell_type": "markdown", + "id": "14f9b2d2", + "metadata": { + "papermill": { + "duration": 0.01882, + "end_time": "2021-08-20T01:43:15.820403", + "exception": false, + "start_time": "2021-08-20T01:43:15.801583", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Missing Values" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "b2bdbfbd", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:15.861647Z", + "iopub.status.busy": "2021-08-20T01:43:15.861010Z", + "iopub.status.idle": "2021-08-20T01:43:15.885804Z", + "shell.execute_reply": "2021-08-20T01:43:15.886432Z", + "shell.execute_reply.started": "2021-08-20T00:57:12.536532Z" + }, + "papermill": { + "duration": 0.047108, + "end_time": "2021-08-20T01:43:15.886607", + "exception": false, + "start_time": "2021-08-20T01:43:15.839499", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalse
1FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
2FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalse
3FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
4FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalse
.......................................
886FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalse
887FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
888FalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalse
889FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
890FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalse
\n", + "

891 rows × 12 columns

\n", + "
" + ], + "text/plain": [ + " PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket \\\n", + "0 False False False False False False False False False \n", + "1 False False False False False False False False False \n", + "2 False False False False False False False False False \n", + "3 False False False False False False False False False \n", + "4 False False False False False False False False False \n", + ".. ... ... ... ... ... ... ... ... ... \n", + "886 False False False False False False False False False \n", + "887 False False False False False False False False False \n", + "888 False False False False False True False False False \n", + "889 False False False False False False False False False \n", + "890 False False False False False False False False False \n", + "\n", + " Fare Cabin Embarked \n", + "0 False True False \n", + "1 False False False \n", + "2 False True False \n", + "3 False False False \n", + "4 False True False \n", + ".. ... ... ... \n", + "886 False True False \n", + "887 False False False \n", + "888 False True False \n", + "889 False False False \n", + "890 False True False \n", + "\n", + "[891 rows x 12 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train.isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "0c42329f", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:15.930200Z", + "iopub.status.busy": "2021-08-20T01:43:15.929563Z", + "iopub.status.idle": "2021-08-20T01:43:16.150878Z", + "shell.execute_reply": "2021-08-20T01:43:16.149935Z", + "shell.execute_reply.started": "2021-08-20T00:57:12.569288Z" + }, + "papermill": { + "duration": 0.244178, + "end_time": "2021-08-20T01:43:16.151024", + "exception": false, + "start_time": "2021-08-20T01:43:15.906846", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.heatmap(train.isnull(), yticklabels=False, cbar=False, cmap='viridis')" + ] + }, + { + "cell_type": "markdown", + "id": "8dbb9133", + "metadata": { + "papermill": { + "duration": 0.020473, + "end_time": "2021-08-20T01:43:16.192297", + "exception": false, + "start_time": "2021-08-20T01:43:16.171824", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "\n", + "Roughly 20 percent of the Age data is missing. The proportion of Age missing is likely small enough for reasonable replacement with some form of imputation. Looking at the Cabin column, it looks like we are just missing too much of that data to do something useful with at a basic level. We'll probably drop this later, or change it to another feature like \"Cabin Known: 1 or 0\"\n", + "\n", + "Let's continue on by visualizing some more of the data! Check out the video for full explanations over these plots, this code is just to serve as reference." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "2196905d", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:16.240706Z", + "iopub.status.busy": "2021-08-20T01:43:16.240095Z", + "iopub.status.idle": "2021-08-20T01:43:16.391994Z", + "shell.execute_reply": "2021-08-20T01:43:16.391371Z", + "shell.execute_reply.started": "2021-08-20T00:57:12.822743Z" + }, + "papermill": { + "duration": 0.179036, + "end_time": "2021-08-20T01:43:16.392141", + "exception": false, + "start_time": "2021-08-20T01:43:16.213105", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.set_style('whitegrid')\n", + "sns.countplot(x='Survived', data=train)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "b0e3d272", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:16.445462Z", + "iopub.status.busy": "2021-08-20T01:43:16.444741Z", + "iopub.status.idle": "2021-08-20T01:43:16.654052Z", + "shell.execute_reply": "2021-08-20T01:43:16.654512Z", + "shell.execute_reply.started": "2021-08-20T00:57:12.982583Z" + }, + "papermill": { + "duration": 0.240764, + "end_time": "2021-08-20T01:43:16.654689", + "exception": false, + "start_time": "2021-08-20T01:43:16.413925", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.set_style('whitegrid')\n", + "sns.countplot(x='Survived', hue='Sex', data=train, palette='RdBu_r')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "233a65d0", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:16.707280Z", + "iopub.status.busy": "2021-08-20T01:43:16.706254Z", + "iopub.status.idle": "2021-08-20T01:43:16.937277Z", + "shell.execute_reply": "2021-08-20T01:43:16.936678Z", + "shell.execute_reply.started": "2021-08-20T00:57:13.171869Z" + }, + "papermill": { + "duration": 0.260001, + "end_time": "2021-08-20T01:43:16.937420", + "exception": false, + "start_time": "2021-08-20T01:43:16.677419", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Let's check for passenger class\n", + "sns.set_style('whitegrid')\n", + "sns.countplot(x='Survived', hue='Pclass', data=train, palette='rainbow')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "6d76e11d", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:16.990637Z", + "iopub.status.busy": "2021-08-20T01:43:16.989975Z", + "iopub.status.idle": "2021-08-20T01:43:17.344513Z", + "shell.execute_reply": "2021-08-20T01:43:17.343972Z", + "shell.execute_reply.started": "2021-08-20T00:57:13.406433Z" + }, + "papermill": { + "duration": 0.383422, + "end_time": "2021-08-20T01:43:17.344654", + "exception": false, + "start_time": "2021-08-20T01:43:16.961232", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.7/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.distplot(train['Age'].dropna(),kde=False,color='darkred',bins=40)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "65e61a96", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:17.400717Z", + "iopub.status.busy": "2021-08-20T01:43:17.400068Z", + "iopub.status.idle": "2021-08-20T01:43:17.750934Z", + "shell.execute_reply": "2021-08-20T01:43:17.751414Z", + "shell.execute_reply.started": "2021-08-20T00:57:13.802719Z" + }, + "papermill": { + "duration": 0.381464, + "end_time": "2021-08-20T01:43:17.751589", + "exception": false, + "start_time": "2021-08-20T01:43:17.370125", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "train['Age'].hist(bins=30, color='darkred', alpha=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "39a6d73e", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:17.810271Z", + "iopub.status.busy": "2021-08-20T01:43:17.809257Z", + "iopub.status.idle": "2021-08-20T01:43:18.147027Z", + "shell.execute_reply": "2021-08-20T01:43:18.146368Z", + "shell.execute_reply.started": "2021-08-20T00:57:14.140942Z" + }, + "papermill": { + "duration": 0.369245, + "end_time": "2021-08-20T01:43:18.147165", + "exception": false, + "start_time": "2021-08-20T01:43:17.777920", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEGCAYAAACKB4k+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAAZbklEQVR4nO3df2zU9eHH8denra0IFG1D72QyE0BmAwyMc6XgIBy7FoWmBakkOoSKYcuQDtE6kagEaNENsQqbW7eMVb+LblRonS5SaKFFkWGAysCb2+LYwHBXc7QUBK7c9fP9w/kOlFKuyP0oPh+JSe99n8/d66PxXvd5f+7z+Vi2bdsCAEBSQqwDAADiB6UAADAoBQCAQSkAAAxKAQBgJMU6wFfR1NSklJSUWMcAgF4lEAhozJgxXT7Xq0shJSVFmZmZsY4BAL2Kx+O56HNMHwEADEoBAGBQCgAAg1IAABiUAgDAoBQAAAalAAAwKAUAgBHRUmhra1NxcbGmTJmiu+66S/v27VNra6uKioqUk5OjoqIiHT9+XJJk27ZWrlwpt9utvLw8HTx4MJLRAABdiGgplJaW6nvf+57eeecd1dTUaOjQoaqoqFB2drZqa2uVnZ2tiooKSVJjY6MOHTqk2tparVixQsuWLbus9wycDV3BLbhy4jUXAJwrYpe5OHHihD744AM9++yzkqTk5GQlJyerrq5Or776qiSpoKBAs2fPVklJierq6lRQUCDLsjRmzBi1tbWpublZGRkZPXrflGsSdXvJK1d8e76qPT9/INYRAOCSIlYKR44cUVpampYsWaK///3vGjFihJYuXSq/328+6AcOHCi/3y9J8vl8cjqdZn2n0ymfz9dtKQQCgQuu4RHP10Lq7nojABAPIlYKwWBQH330kZ566imNHj1aK1euNFNFX7IsS5ZlXfZ79LYL4vWmrACuXjG5IJ7T6ZTT6dTo0aMlSVOmTNFHH32k9PR0NTc3S5Kam5uVlpYmSXI4HPJ6vWZ9r9crh8MRqXgAgC5ErBQGDhwop9OpTz75RJL0/vvva+jQoXK5XKqurpYkVVdXa/LkyZJkxm3bVlNTk/r379/j4wkAgK8movdTeOqpp/TYY4/p7NmzGjx4sFatWqWOjg4tWrRIVVVVGjRokMrLyyVJEydOVENDg9xut/r06aOysrJIRgMAdMGybduOdYjL5fF4upyn59dHAHBxF/vslDijGQBwDkoBAGBQCgAAg1IAABiUAgDAoBQAAAalAAAwKAUAgEEpAAAMSgEAYFAKAACDUgAAGJQCAMCgFAAABqUAADAoBQCAQSkAAAxKAQBgUAoAAINSAAAYlAIAwKAUAAAGpQAAMCgFAIBBKQAAjKRIvrjL5VLfvn2VkJCgxMREbdy4Ua2trXrkkUf06aef6hvf+IbKy8s1YMAA2bat0tJSNTQ06Nprr9Wzzz6rESNGRDIeAKCTiO8pVFZWqqamRhs3bpQkVVRUKDs7W7W1tcrOzlZFRYUkqbGxUYcOHVJtba1WrFihZcuWRToaAKCTqE8f1dXVqaCgQJJUUFCgrVu3njduWZbGjBmjtrY2NTc3RzseAHytRXT6SJLmzZsny7I0a9YszZo1S36/XxkZGZKkgQMHyu/3S5J8Pp+cTqdZz+l0yufzmWW7EggE5PF4zhvLzMyMwFZcGZ2zAkC8iWgpvPbaa3I4HPL7/SoqKtKQIUPOe96yLFmWddmvn5KSEtcl0Flvygrg6tXdF9SITh85HA5JUnp6utxut/bv36/09HQzLdTc3Ky0tDSzrNfrNet6vV6zPgAgOiJWCqdOndLJkyfN3++9955uueUWuVwuVVdXS5Kqq6s1efJkSTLjtm2rqalJ/fv373bqCABw5UVs+sjv92vBggWSpFAopGnTpmnChAkaNWqUFi1apKqqKg0aNEjl5eWSpIkTJ6qhoUFut1t9+vRRWVlZpKIBAC7Csm3bjnWIy+XxeLqcp7+95JUYpOnenp8/EOsIACDp4p+dEmc0AwDOQSkAAAxKAQBgUAoAAINSAAAYlAIAwKAUAAAGpQAAMCgFAIBBKQAADEoBAGBQCgAAg1IAABiUAgDAoBQAAAalAAAwKAUAgEEpAAAMSgEAYFAKAACDUgAAGJQCAMCgFAAABqUAADAoBQCAEfFSCIVCKigo0A9/+ENJ0uHDh1VYWCi3261Fixapvb1dktTe3q5FixbJ7XarsLBQR44ciXQ0AEAnES+FV155RUOHDjWPV69erblz52rLli1KTU1VVVWVJGnDhg1KTU3Vli1bNHfuXK1evTrS0QAAnUS0FLxer7Zv366ZM2dKkmzb1q5du5SbmytJmj59uurq6iRJ9fX1mj59uiQpNzdX77//vmzbjmQ8AEAnES2FsrIylZSUKCHhi7dpaWlRamqqkpKSJElOp1M+n0+S5PP5dOONN0qSkpKS1L9/f7W0tEQyHgCgk6RIvfC2bduUlpamkSNH6q9//WtE3iMQCMjj8Zw3lpmZGZH3uhI6ZwWAeBOxUti7d6/q6+vV2NioQCCgkydPqrS0VG1tbQoGg0pKSpLX65XD4ZAkORwOHT16VE6nU8FgUCdOnNANN9zQ7XukpKTEdQl01puyArh6dfcFNWLTR48++qgaGxtVX1+vNWvWaOzYsXr++eeVlZWlzZs3S5I2bdokl8slSXK5XNq0aZMkafPmzRo7dqwsy4pUPABAF6J+nkJJSYnWr18vt9ut1tZWFRYWSpJmzpyp1tZWud1urV+/Xo899li0owHA155l9+Kf+Hg8ni6nZG4veSUGabq35+cPxDoCAEi6+GenxBnNAIBzUAoAAINSAAAYlAIAwKAUAAAGpQAAMCgFAIBBKQAADEoBAGBQCgAAg1IAABhhlcKcOXPCGgMA9G7d3k8hEAjo9OnTamlp0fHjx83tMU+ePGnumAYAuHp0Wwqvv/66Kisr1dzcrBkzZphS6Nevn37wgx9EJSAAIHq6LYU5c+Zozpw5evXVVzV79uxoZQIAxEhYt+OcPXu29u7dq08//VShUMiMFxQURCoXACAGwiqFkpISHT58WLfeeqsSExMlSZZlUQoAcJUJqxQOHDigv/zlL9wzGQCucmH9JPWWW27RZ599FuksAIAYC2tPoaWlRVOnTtW3v/1tXXPNNWb8V7/6VcSCAQCiL6xSWLhwYaRzAADiQFil8N3vfjfSOQAAcSCsUrjtttvMQeazZ88qGAyqT58+2rt3b0TDAQCiK6xS2Ldvn/nbtm3V1dWpqakpUpkAADHS46ukWpal73//+3r33XcjkQcAEENh7SnU1taavzs6OnTgwAGlpKR0u04gEND999+v9vZ2hUIh5ebmqri4WIcPH9bixYvV2tqqESNG6Gc/+5mSk5PV3t6uxx9/XAcPHtT111+vF154QTfddNNX2zoAQI+Etaewbds288+7776rvn376pe//GW36yQnJ6uyslJvvvmmqqurtWPHDjU1NWn16tWaO3eutmzZotTUVFVVVUmSNmzYoNTUVG3ZskVz587V6tWrv/rWAQB6JKw9hVWrVvX4hS3LUt++fSVJwWBQwWBQlmVp165dev755yVJ06dP17p163Tfffepvr5eDz/8sCQpNzdXy5cvl23bnEUNAFEU1p6C1+vVggULlJ2drezsbC1cuFBer/eS64VCIeXn52vcuHEaN26cBg8erNTUVCUlfdFFTqfT3JfB5/PpxhtvlCQlJSWpf//+amlpudztAgBchrD2FJYsWaJp06bpxRdflCS9+eabWrJkidavX9/teomJiaqpqVFbW5sWLFigTz755KsnPkcgEJDH4zlvLDMz84q+x5XUOSsAxJuwSuHYsWO65557zOMZM2aosrIy7DdJTU1VVlaWmpqa1NbWpmAwqKSkJHm9XjkcDkmSw+HQ0aNH5XQ6FQwGdeLECd1www3dvm5KSkpcl0BnvSkrgKtXd19Qw5o+uv7661VTU6NQKKRQKKSamhpdf/313a5z7NgxtbW1SZLOnDmjnTt3aujQocrKytLmzZslSZs2bZLL5ZIkuVwubdq0SZK0efNmjR07luMJABBlYe0plJWVacWKFVq1apUsy9Jtt92mZ599ttt1mpub9cQTTygUCsm2bU2ZMkWTJk3SsGHD9Mgjj6i8vFyZmZkqLCyUJM2cOVMlJSVyu90aMGCAXnjhha++dQCAHgmrFF566SU999xzGjBggCSptbVVzz33XLe/Srr11ltVXV19wfjgwYPNz1DPlZKSopdeeinM2ACASAhr+ujjjz82hSB9MZ3EQVMAuPqEVQodHR06fvy4edza2nrevZoBAFeHsKaPHnzwQc2aNUtTpkyRJL3zzjv60Y9+FNFgAIDoC6sUCgoKNHLkSO3atUuStG7dOg0bNiyiwQAA0RdWKUjSsGHDKAIAuMr1+NLZAICrF6UAADAoBQCAQSkAAAxKAQBgUAoAAINSAAAYlAIAwKAUAAAGpQAAMCgFAIBBKQAADEoBAGBQCgAAg1IAABiUAgDAoBQAAAalAAAwKAUAgEEpAAAMSgEAYESsFI4eParZs2fr7rvv1tSpU1VZWSlJam1tVVFRkXJyclRUVKTjx49Lkmzb1sqVK+V2u5WXl6eDBw9GKlpcs4OBWEfoUrzmAnBlJUXqhRMTE/XEE09oxIgROnnypO655x6NHz9eGzduVHZ2tubPn6+KigpVVFSopKREjY2NOnTokGpra/Xhhx9q2bJl2rBhQ6TixS0rKUX/XT4q1jEu8M2n/xbrCACiIGJ7ChkZGRoxYoQkqV+/fhoyZIh8Pp/q6upUUFAgSSooKNDWrVslyYxblqUxY8aora1Nzc3NkYoHAOhCxPYUznXkyBF5PB6NHj1afr9fGRkZkqSBAwfK7/dLknw+n5xOp1nH6XTK5/OZZbsSCATk8XjOG8vMzIzAFlwZnbN2pbfnB9C7RbwUPv/8cxUXF+vJJ59Uv379znvOsixZlnXZr52SkhLXH6Kd9aasXent+QF8obsveBH99dHZs2dVXFysvLw85eTkSJLS09PNtFBzc7PS0tIkSQ6HQ16v16zr9XrlcDgiGQ8A0EnESsG2bS1dulRDhgxRUVGRGXe5XKqurpYkVVdXa/LkyeeN27atpqYm9e/fv9upIwDAlRex6aM9e/aopqZGw4cPV35+viRp8eLFmj9/vhYtWqSqqioNGjRI5eXlkqSJEyeqoaFBbrdbffr0UVlZWaSiAQAuImKl8J3vfEcff/xxl899ec7CuSzL0jPPPBOpOACAMHBGMwDAoBQAAAalAAAwKAUAgEEpAAAMSgEAYFAKAACDUgAAGJQCAMCgFAAABqUAADAoBQCAQSkAAAxKAQBgUAoAAINSAAAYlAIAwKAUAAAGpQAAMCgFAIBBKQAADEoBAGBQCgAAg1IAABiUAgDAiFgpLFmyRNnZ2Zo2bZoZa21tVVFRkXJyclRUVKTjx49Lkmzb1sqVK+V2u5WXl6eDBw9GKhYAoBsRK4UZM2bot7/97XljFRUVys7OVm1trbKzs1VRUSFJamxs1KFDh1RbW6sVK1Zo2bJlkYoFAOhGxErhjjvu0IABA84bq6urU0FBgSSpoKBAW7duPW/csiyNGTNGbW1tam5ujlQ0AMBFJEXzzfx+vzIyMiRJAwcOlN/vlyT5fD45nU6znNPplM/nM8teTCAQkMfjOW8sMzPzCqe+cjpn7Upvzw+gd4tqKZzLsixZlvWVXiMlJSWuP0Q7601Zu9Lb8wP4Qndf8KL666P09HQzLdTc3Ky0tDRJksPhkNfrNct5vV45HI5oRgMAKMql4HK5VF1dLUmqrq7W5MmTzxu3bVtNTU3q37//JaeOAABXXsSmjxYvXqzdu3erpaVFEyZM0MKFCzV//nwtWrRIVVVVGjRokMrLyyVJEydOVENDg9xut/r06aOysrJIxQIAdCNipbBmzZouxysrKy8YsyxLzzzzTKSiAADCxBnNAACDUgAAGJQCAMCgFAAABqUAADAoBQCAQSkAAAxKAQBgUAoAAINSAAAYlAIAwKAUAAAGpQAAMCgFAIBBKQAADEoBAGBQCgAAg1IAABiUAq6oQDAQ6whditdcQLyJ2D2a8fWUkpSi8WvHxzrGBd5b+F6sIwC9AnsKAACDUgAAGJQC8D8dgfg97hBOtuDZUBSS9Fy85kLXOKYA/E9CSooaJkyMdYwuTWxsuOQySdckat2jf45Cmp55+Pm8WEdAD7CnAAAw4qoUGhsblZubK7fbrYqKiljHAYCwdQTjc5qsp7niZvooFApp+fLlWr9+vRwOh2bOnCmXy6Vhw4bFOhqAKAi2tyspOTnWMS4Qbq6EpER5SuujkKhnMpe6erR83JTC/v37dfPNN2vw4MGSpKlTp6quro5SAL4mkpKTVfqDmbGOcYGl/1cV6whRZdm2bcc6hCS988472rFjh0pLSyVJ1dXV2r9/v55++umLrtPU1KSUlJRoRQSAq0IgENCYMWO6fC5u9hQux8U2CgBweeLmQLPD4ZDX6zWPfT6fHA5HDBMBwNdP3JTCqFGjdOjQIR0+fFjt7e16++235XL17AAJAOCriZvpo6SkJD399NN66KGHFAqFdM899+iWW26JdSwA+FqJmwPNAIDYi5vpIwBA7FEKAAAjbo4pxJPGxkaVlpaqo6NDhYWFmj9/fqwj9ciSJUu0fft2paen66233op1nB45evSoHn/8cfn9flmWpXvvvVdz5syJdaywBQIB3X///Wpvb1coFFJubq6Ki4tjHavHvjyu53A49Otf/zrWcXrE5XKpb9++SkhIUGJiojZu3BjrSGH7/e9/rw0bNsiyLA0fPlyrVq2K/rlYNs4TDAbtyZMn2//973/tQCBg5+Xl2f/85z9jHatHdu/ebR84cMCeOnVqrKP0mM/nsw8cOGDbtm2fOHHCzsnJ6VX//js6OuyTJ0/atm3b7e3t9syZM+19+/bFNtRl+N3vfmcvXrzYnj9/fqyj9NikSZNsv98f6xg95vV67UmTJtmnT5+2bdu2i4uL7TfeeCPqOZg+6uTcy20kJyeby230JnfccYcGDBgQ6xiXJSMjQyNGjJAk9evXT0OGDJHP54txqvBZlqW+fftKkoLBoILBoCzLinGqnvF6vdq+fbtmzoy/S05c7UKhkM6cOaNgMKgzZ84oIyMj6hkohU58Pp+cTqd57HA4etWH0tXkyJEj8ng8Gj16dKyj9EgoFFJ+fr7GjRuncePG9br8ZWVlKikpUUJC7/14mDdvnmbMmKE//vGPsY4SNofDoQcffFCTJk3SnXfeqX79+unOO++Meo7e+18dV7XPP/9cxcXFevLJJ9WvX79Yx+mRxMRE1dTUqKGhQfv379c//vGPWEcK27Zt25SWlqaRI0fGOsple+2117Rp0yb95je/0R/+8Ad98MEHsY4UluPHj6uurk51dXXasWOHTp8+rZqamqjnoBQ64XIbsXf27FkVFxcrLy9POTk5sY5z2VJTU5WVlaUdO3bEOkrY9u7dq/r6erlcLi1evFi7du3SY489FutYPfLl/6/p6elyu93av39/jBOFZ+fOnbrpppuUlpama665Rjk5Odq3b1/Uc1AKnXC5jdiybVtLly7VkCFDVFRUFOs4PXbs2DG1tbVJks6cOaOdO3dqyJAhMU4VvkcffVSNjY2qr6/XmjVrNHbsWK1evTrWscJ26tQpnTx50vz93nvv9ZorIwwaNEgffvihTp8+Ldu29f7772vo0KFRz8FPUju5Gi63sXjxYu3evVstLS2aMGGCFi5cqMLCwljHCsuePXtUU1Oj4cOHKz8/X9IX2zNxYnzeO7mz5uZmPfHEEwqFQrJtW1OmTNGkSZNiHetrw+/3a8GCBZK+OLYzbdo0TZgwIcapwjN69Gjl5uZq+vTpSkpKUmZmpmbNmhX1HFzmAgBgMH0EADAoBQCAQSkAAAxKAQBgUAoAAINSAMLw8ssva+rUqcrLy1N+fr4+/PBDLV26VP/6178kSbfddluX6zU1NamwsFD5+fm66667tHbt2mjGBnqM8xSAS9i3b5+2b9+uTZs2KTk5WceOHdPZs2dVWlp6yXV/+tOf6sUXX9Stt96qUCikf//731FIDFw+9hSAS/jss890ww03KDk5WZKUlpYmh8Oh2bNn629/+5tZrqysTFOnTtWcOXN07NgxSV+c4Txw4EBJX1wTadiwYZKktWvXqqSkRLNmzVJOTo7+9Kc/RXmrgK5RCsAljB8/XkePHlVubq6WLVum3bt3X7DMqVOnNHLkSL399tu64447tG7dOknSnDlzNGXKFC1YsECvv/66AoGAWefjjz9WZWWlXn/9df3iF7/garyIC5QCcAl9+/bVxo0btXz5cqWlpemRRx654G5eCQkJuvvuuyVJ+fn52rNnjyTp4Ycf1htvvKHx48frrbfe0kMPPWTWmTx5sq699lqlpaUpKyvrvL0OIFY4pgCEITExUVlZWcrKytLw4cNVXV3d7fLn3ljnm9/8pu677z7de++9ys7OVktLywXLAPGCPQXgEj755BMdOnTIPPZ4PBo0aNB5y3R0dGjz5s2SpD//+c+6/fbbJUnbt2/Xl5cX+89//qOEhASlpqZKkurq6hQIBNTS0qLdu3dr1KhRUdgaoHvsKQCXcOrUKa1cuVJtbW1KTEzUzTffrOXLl+snP/mJWea6667T/v379fLLLystLU3l5eWSpJqaGq1atUrXXnutEhMTtXr1aiUmJkqSvvWtb+mBBx5QS0uLfvzjH3PfDsQFrpIKxMDatWt13XXXad68ebGOApyH6SMAgMGeAgDAYE8BAGBQCgAAg1IAABiUAgDAoBQAAMb/Az0tWO4KFSNUAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Siblings and Spouse\n", + "sns.countplot(x='SibSp', data=train)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "143974a5", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:18.211096Z", + "iopub.status.busy": "2021-08-20T01:43:18.207564Z", + "iopub.status.idle": "2021-08-20T01:43:18.486968Z", + "shell.execute_reply": "2021-08-20T01:43:18.486293Z", + "shell.execute_reply.started": "2021-08-20T00:57:14.471086Z" + }, + "papermill": { + "duration": 0.312857, + "end_time": "2021-08-20T01:43:18.487118", + "exception": false, + "start_time": "2021-08-20T01:43:18.174261", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(x='SibSp', hue='Sex', data=train)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a53f25de", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:18.569605Z", + "iopub.status.busy": "2021-08-20T01:43:18.566457Z", + "iopub.status.idle": "2021-08-20T01:43:18.884065Z", + "shell.execute_reply": "2021-08-20T01:43:18.883385Z", + "shell.execute_reply.started": "2021-08-20T00:57:14.740834Z" + }, + "papermill": { + "duration": 0.368654, + "end_time": "2021-08-20T01:43:18.884213", + "exception": false, + "start_time": "2021-08-20T01:43:18.515559", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "train['Fare'].hist(color='green',bins=40,figsize=(8,4))" + ] + }, + { + "cell_type": "markdown", + "id": "8f93e687", + "metadata": { + "papermill": { + "duration": 0.029983, + "end_time": "2021-08-20T01:43:18.945408", + "exception": false, + "start_time": "2021-08-20T01:43:18.915425", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Data Cleaning\n", + "\n", + "We want to fill in missing age data instead of just dropping the missing age data rows. One way to do this is by filling in the mean age of all the passengers (imputation). However we can be smarter about this and check the average age by passenger class. For example:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "19f65c92", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:19.013901Z", + "iopub.status.busy": "2021-08-20T01:43:19.011313Z", + "iopub.status.idle": "2021-08-20T01:43:19.253768Z", + "shell.execute_reply": "2021-08-20T01:43:19.253256Z", + "shell.execute_reply.started": "2021-08-20T00:57:15.053293Z" + }, + "papermill": { + "duration": 0.278652, + "end_time": "2021-08-20T01:43:19.253927", + "exception": false, + "start_time": "2021-08-20T01:43:18.975275", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 7))\n", + "sns.boxplot(x='Pclass',y='Age',data=train,palette='winter')" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "f1411c1e", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:19.323535Z", + "iopub.status.busy": "2021-08-20T01:43:19.322500Z", + "iopub.status.idle": "2021-08-20T01:43:19.327981Z", + "shell.execute_reply": "2021-08-20T01:43:19.327333Z", + "shell.execute_reply.started": "2021-08-20T01:34:28.731272Z" + }, + "papermill": { + "duration": 0.043894, + "end_time": "2021-08-20T01:43:19.328131", + "exception": false, + "start_time": "2021-08-20T01:43:19.284237", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pclass\n", + "1 38.233441\n", + "2 29.877630\n", + "3 25.140620\n", + "Name: Age, dtype: float64\n" + ] + } + ], + "source": [ + "# Pclass wise average age\n", + "data = train.copy()\n", + "pclass_avrg = [data.groupby(feature)['Age'].mean() for feature in data if feature == 'Pclass']\n", + "\n", + "print(pclass_avrg[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "57c6e705", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:19.399020Z", + "iopub.status.busy": "2021-08-20T01:43:19.398208Z", + "iopub.status.idle": "2021-08-20T01:43:19.403368Z", + "shell.execute_reply": "2021-08-20T01:43:19.402525Z", + "shell.execute_reply.started": "2021-08-20T01:38:33.015669Z" + }, + "papermill": { + "duration": 0.04158, + "end_time": "2021-08-20T01:43:19.403555", + "exception": false, + "start_time": "2021-08-20T01:43:19.361975", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pclass 1 Average Age: 38\n", + "Pclass 2 Average Age: 29\n", + "Pclass 3 Average Age: 25\n" + ] + } + ], + "source": [ + "pclass1_avg_age = int(pclass_avrg[0][1])\n", + "pclass2_avg_age = int(pclass_avrg[0][2])\n", + "pclass3_avg_age = int(pclass_avrg[0][3])\n", + "\n", + "print('Pclass 1 Average Age: ', pclass1_avg_age)\n", + "print('Pclass 2 Average Age: ', pclass2_avg_age)\n", + "print('Pclass 3 Average Age: ', pclass3_avg_age)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "a6401dc8", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:19.473120Z", + "iopub.status.busy": "2021-08-20T01:43:19.472207Z", + "iopub.status.idle": "2021-08-20T01:43:19.475211Z", + "shell.execute_reply": "2021-08-20T01:43:19.475651Z", + "shell.execute_reply.started": "2021-08-20T01:38:42.286718Z" + }, + "papermill": { + "duration": 0.040295, + "end_time": "2021-08-20T01:43:19.475823", + "exception": false, + "start_time": "2021-08-20T01:43:19.435528", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "def impute_age(cols):\n", + " Age = cols[0]\n", + " Pclass = cols[1]\n", + " \n", + " if pd.isnull(Age):\n", + "\n", + " if Pclass == 1:\n", + " return pclass1_avg_age\n", + "\n", + " elif Pclass == 2:\n", + " return pclass2_avg_age\n", + "\n", + " else:\n", + " return pclass3_avg_age\n", + "\n", + " else:\n", + " return Age" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "3aa934ea", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:19.544003Z", + "iopub.status.busy": "2021-08-20T01:43:19.543014Z", + "iopub.status.idle": "2021-08-20T01:43:19.563143Z", + "shell.execute_reply": "2021-08-20T01:43:19.562550Z", + "shell.execute_reply.started": "2021-08-20T01:39:58.870020Z" + }, + "papermill": { + "duration": 0.056559, + "end_time": "2021-08-20T01:43:19.563279", + "exception": false, + "start_time": "2021-08-20T01:43:19.506720", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Impute age for null values\n", + "train['Age'] = train[['Age','Pclass']].apply(impute_age,axis=1)" + ] + }, + { + "cell_type": "markdown", + "id": "a36ee30d", + "metadata": { + "papermill": { + "duration": 0.03111, + "end_time": "2021-08-20T01:43:19.625169", + "exception": false, + "start_time": "2021-08-20T01:43:19.594059", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "Now let's check that heat map again!" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "8f795339", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:19.710538Z", + "iopub.status.busy": "2021-08-20T01:43:19.709412Z", + "iopub.status.idle": "2021-08-20T01:43:19.950468Z", + "shell.execute_reply": "2021-08-20T01:43:19.949811Z", + "shell.execute_reply.started": "2021-08-20T01:40:37.399955Z" + }, + "papermill": { + "duration": 0.29485, + "end_time": "2021-08-20T01:43:19.950604", + "exception": false, + "start_time": "2021-08-20T01:43:19.655754", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.heatmap(train.isnull(),yticklabels=False,cbar=False,cmap='viridis')" + ] + }, + { + "cell_type": "markdown", + "id": "577c64ae", + "metadata": { + "papermill": { + "duration": 0.033257, + "end_time": "2021-08-20T01:43:20.016237", + "exception": false, + "start_time": "2021-08-20T01:43:19.982980", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "Cabin column has a lot of missing values so we are going to drop this column" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "5bbdf275", + "metadata": { + "execution": { + "iopub.execute_input": "2021-08-20T01:43:20.098710Z", + "iopub.status.busy": "2021-08-20T01:43:20.085507Z", + "iopub.status.idle": "2021-08-20T01:43:20.103610Z", + "shell.execute_reply": "2021-08-20T01:43:20.103113Z", + "shell.execute_reply.started": "2021-08-20T01:42:19.878524Z" + }, + "papermill": { + "duration": 0.055447, + "end_time": "2021-08-20T01:43:20.103747", + "exception": false, + "start_time": "2021-08-20T01:43:20.048300", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500S
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250S
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000S
4503Allen, Mr. William Henrymale35.0003734508.0500S
\n", + "
" + ], + "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 Embarked \n", + "0 0 A/5 21171 7.2500 S \n", + "1 0 PC 17599 71.2833 C \n", + "2 0 STON/O2. 3101282 7.9250 S \n", + "3 0 113803 53.1000 S \n", + "4 0 373450 8.0500 S " + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train.drop('Cabin',axis=1,inplace=True)\n", + "train.head()" + ] + } + ], + "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": "3.7.10" + }, + "papermill": { + "default_parameters": {}, + "duration": 14.837901, + "end_time": "2021-08-20T01:43:21.606786", + "environment_variables": {}, + "exception": null, + "input_path": "__notebook__.ipynb", + "output_path": "__notebook__.ipynb", + "parameters": {}, + "start_time": "2021-08-20T01:43:06.768885", + "version": "2.3.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}