487 lines
70 KiB
Plaintext
487 lines
70 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"# -- 将数据框命名为titanic\n",
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"# -- 将PassengerId设置为索引\n",
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"# -- 绘制一个展示男女乘客比例的扇形图\n",
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"# -- 绘制一个展示船票Fare, 与乘客年龄和性别的散点图\n",
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"# -- 有多少人生还？\n",
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"# -- 绘制一个展示船票价格的直方图"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>PassengerId</th>\n",
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" <th>Survived</th>\n",
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" <th>Pclass</th>\n",
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" <th>Name</th>\n",
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" <th>Sex</th>\n",
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" <th>Age</th>\n",
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" <th>SibSp</th>\n",
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" <th>Parch</th>\n",
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" <th>Ticket</th>\n",
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" <th>Fare</th>\n",
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" <th>Cabin</th>\n",
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" <th>Embarked</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" <td>3</td>\n",
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" <td>Braund, Mr. Owen Harris</td>\n",
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" <td>male</td>\n",
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" <td>22.0</td>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" <td>A/5 21171</td>\n",
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" <td>7.2500</td>\n",
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" <td>NaN</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>2</td>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
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" <td>female</td>\n",
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" <td>38.0</td>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" <td>PC 17599</td>\n",
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" <td>71.2833</td>\n",
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" <td>C85</td>\n",
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" <td>C</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>3</td>\n",
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" <td>1</td>\n",
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" <td>3</td>\n",
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" <td>Heikkinen, Miss. Laina</td>\n",
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" <td>female</td>\n",
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" <td>26.0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>STON/O2. 3101282</td>\n",
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" <td>7.9250</td>\n",
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" <td>NaN</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>4</td>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
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" <td>female</td>\n",
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" <td>35.0</td>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" <td>113803</td>\n",
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" <td>53.1000</td>\n",
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" <td>C123</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>5</td>\n",
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" <td>0</td>\n",
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" <td>3</td>\n",
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" <td>Allen, Mr. William Henry</td>\n",
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" <td>male</td>\n",
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" <td>35.0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>373450</td>\n",
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" <td>8.0500</td>\n",
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" <td>NaN</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" PassengerId Survived Pclass \\\n",
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"0 1 0 3 \n",
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"1 2 1 1 \n",
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"2 3 1 3 \n",
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"3 4 1 1 \n",
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"4 5 0 3 \n",
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"\n",
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" Name Sex Age SibSp \\\n",
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"0 Braund, Mr. Owen Harris male 22.0 1 \n",
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"1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n",
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"2 Heikkinen, Miss. Laina female 26.0 0 \n",
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"3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n",
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"4 Allen, Mr. William Henry male 35.0 0 \n",
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"\n",
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" Parch Ticket Fare Cabin Embarked \n",
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"0 0 A/5 21171 7.2500 NaN S \n",
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"1 0 PC 17599 71.2833 C85 C \n",
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"2 0 STON/O2. 3101282 7.9250 NaN S \n",
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"3 0 113803 53.1000 C123 S \n",
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"4 0 373450 8.0500 NaN S "
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"import numpy as np\n",
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"#将数据框命名为titanic\n",
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"titanic = pd.read_csv('data/train.csv')\n",
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"titanic.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Survived</th>\n",
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" <th>Pclass</th>\n",
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" <th>Name</th>\n",
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" <th>Sex</th>\n",
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" <th>Age</th>\n",
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" <th>SibSp</th>\n",
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" <th>Parch</th>\n",
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" <th>Ticket</th>\n",
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" <th>Fare</th>\n",
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" <th>Cabin</th>\n",
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" <th>Embarked</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>PassengerId</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>0</td>\n",
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" <td>3</td>\n",
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" <td>Braund, Mr. Owen Harris</td>\n",
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" <td>male</td>\n",
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" <td>22.0</td>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" <td>A/5 21171</td>\n",
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" <td>7.2500</td>\n",
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" <td>NaN</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
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" <td>female</td>\n",
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" <td>38.0</td>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" <td>PC 17599</td>\n",
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" <td>71.2833</td>\n",
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" <td>C85</td>\n",
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" <td>C</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>1</td>\n",
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" <td>3</td>\n",
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" <td>Heikkinen, Miss. Laina</td>\n",
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" <td>female</td>\n",
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" <td>26.0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>STON/O2. 3101282</td>\n",
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" <td>7.9250</td>\n",
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" <td>NaN</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
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" <td>female</td>\n",
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" <td>35.0</td>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" <td>113803</td>\n",
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" <td>53.1000</td>\n",
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" <td>C123</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td>0</td>\n",
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" <td>3</td>\n",
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" <td>Allen, Mr. William Henry</td>\n",
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" <td>male</td>\n",
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" <td>35.0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>373450</td>\n",
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" <td>8.0500</td>\n",
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" <td>NaN</td>\n",
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" <td>S</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Survived Pclass \\\n",
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"PassengerId \n",
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"1 0 3 \n",
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"2 1 1 \n",
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"3 1 3 \n",
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"4 1 1 \n",
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"5 0 3 \n",
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"\n",
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" Name Sex Age \\\n",
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"PassengerId \n",
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"1 Braund, Mr. Owen Harris male 22.0 \n",
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"2 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 \n",
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"3 Heikkinen, Miss. Laina female 26.0 \n",
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"4 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 \n",
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"5 Allen, Mr. William Henry male 35.0 \n",
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"\n",
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" SibSp Parch Ticket Fare Cabin Embarked \n",
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"PassengerId \n",
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"1 1 0 A/5 21171 7.2500 NaN S \n",
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"2 1 0 PC 17599 71.2833 C85 C \n",
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"3 0 0 STON/O2. 3101282 7.9250 NaN S \n",
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"4 1 0 113803 53.1000 C123 S \n",
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"5 0 0 373450 8.0500 NaN S "
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"#将PassengerId设置为索引\n",
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"titanic = titanic.set_index('PassengerId')\n",
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"titanic.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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\n",
|
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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
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"source": [
|
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"#绘制一个展示男女乘客比例的扇形图\n",
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"Male = (titanic.Sex == 'male').sum()\n",
|
|
"Female = (titanic.Sex == 'female').sum()\n",
|
|
"# female = titanic.query('Sex==\"female\"')\n",
|
|
"proportions= [Male,Female]\n",
|
|
"plt.pie(proportions,labels=['Male','Female'],shadow=True,\n",
|
|
" autopct='%1.1f%%',startangle=90,explode=(0.15,0))\n",
|
|
"plt.axis('equal')\n",
|
|
"plt.title('Sex Proportion')\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(-5, 85)"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 430.5x360 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"#绘制一个展示船票Fare, 与乘客年龄和性别的散点图\n",
|
|
"lm = sns.lmplot(x='Age',y='Fare',data=titanic,hue='Sex',fit_reg=False)\n",
|
|
"lm.set(title='Fare x Age')\n",
|
|
"#设置坐标轴取值范围\n",
|
|
"axes = lm.axes\n",
|
|
"axes[0,0].set_ylim(-5,)\n",
|
|
"axes[0,0].set_xlim(-5,85)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"342"
|
|
]
|
|
},
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"#有多少人生还？\n",
|
|
"titanic.Survived.sum()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"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"
|
|
}
|
|
],
|
|
"source": [
|
|
"#绘制一个展示船票价格的直方图\n",
|
|
"df = titanic.Fare.sort_values(ascending=False)\n",
|
|
"plt.hist(df,bins=(np.arange(0,600,10)))\n",
|
|
"plt.xlabel('Fare')\n",
|
|
"plt.ylabel('Frequency')\n",
|
|
"plt.title('Fare Payed Histrogram')\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"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": "3.6.1"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|