teach_EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "61088109",
   "metadata": {},
   "source": [
    "# 使用python进行数据探索性分析"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc7b66c2",
   "metadata": {},
   "source": [
    "## 1. 课题    \n",
    "使用python进行数据探索性分析    \n",
    "    \n",
    "## 2. 课前准备    \n",
    "确保教学计算机已全部安装同一版本的anaconda。（本次使用版本Anaconda3-2023.07-2-Windows-x86_64）    \n",
    "    \n",
    "## 3. 教学目标    \n",
    "3.1 理解Python数据探索性分析的基本概念。    \n",
    "3.2 熟练使用Python进行数据探索性分析。    \n",
    "3.3 学会使用Pandas库进行数据导入、数据统计信息查看等操作。    \n",
    "3.4 学习使用Matplotlib、Seaborn等库进行数据统计信息的可视化展示。    \n",
    "3.5 对Python数据分析的实际应用场景有深入理解。    \n",
    "    \n",
    "## 4. 教学重点    \n",
    "4.1 Pandas库的数据结构（DataFrame）和数据处理方法。    \n",
    "4.2 Numpy库的数组操作和矩阵计算。    \n",
    "4.3 Matplotlib和Seaborn库的图形绘制。    \n",
    "4.4 数据探索性分析的基本流程和方法。    \n",
    "    \n",
    "## 5. 教学难点    \n",
    "5.1 Pandas数据结构的理解和使用。        \n",
    "5.2 数据统计信息查看方法的选择和应用。    \n",
    "5.3 数据统计信息的可视化展示。    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbb6c989",
   "metadata": {},
   "source": [
    "## 实施步骤    \n",
    "### 步骤 1: 启动Jupyter Notebook    \n",
    "+ 在搜索栏输入\"cmd\"命令，启动命令提示符窗口。    \n",
    "+ 输入\"jupyter notebook\"命令，并按回车键启动Jupyter Notebook。   \n",
    "    \n",
    "### 步骤 2: 创建新的Notebook    \n",
    "+ 在Jupyter的Web界面中，点击右上角的 \"New\" 按钮。    \n",
    "+ 选择 \"Python 3\"内核来创建一个新的Python 3 Notebook。    \n",
    "    \n",
    "### 步骤 3: 导入必要的库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "62e91d45",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b91d52b",
   "metadata": {},
   "source": [
    "### 步骤 4: 导入数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1a854538",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 用Pandas导入CSV文件\n",
    "data_csv = pd.read_csv('train_chinese.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abda8ba2",
   "metadata": {},
   "source": [
    "### 步骤 5: 查看数据    \n",
    "5.1 查看数据的基本信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "71d2ab67",
   "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>乘客ID</th>\n",
       "      <th>是否幸存</th>\n",
       "      <th>仓位等级</th>\n",
       "      <th>姓名</th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>兄弟姐妹个数</th>\n",
       "      <th>父母子女个数</th>\n",
       "      <th>船票信息</th>\n",
       "      <th>票价</th>\n",
       "      <th>客舱</th>\n",
       "      <th>登船港口</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",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Moran, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Master. Gosta Leonard</td>\n",
       "      <td>male</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
       "      <td>female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
       "      <td>female</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   乘客ID  是否幸存  仓位等级                                                 姓名  \\\n",
       "0     1     0     3                            Braund, Mr. Owen Harris   \n",
       "1     2     1     1  Cumings, Mrs. John Bradley (Florence Briggs Th...   \n",
       "2     3     1     3                             Heikkinen, Miss. Laina   \n",
       "3     4     1     1       Futrelle, Mrs. Jacques Heath (Lily May Peel)   \n",
       "4     5     0     3                           Allen, Mr. William Henry   \n",
       "5     6     0     3                                   Moran, Mr. James   \n",
       "6     7     0     1                            McCarthy, Mr. Timothy J   \n",
       "7     8     0     3                     Palsson, Master. Gosta Leonard   \n",
       "8     9     1     3  Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)   \n",
       "9    10     1     2                Nasser, Mrs. Nicholas (Adele Achem)   \n",
       "\n",
       "       性别    年龄  兄弟姐妹个数  父母子女个数              船票信息       票价    客舱 登船港口  \n",
       "0    male  22.0       1       0         A/5 21171   7.2500   NaN    S  \n",
       "1  female  38.0       1       0          PC 17599  71.2833   C85    C  \n",
       "2  female  26.0       0       0  STON/O2. 3101282   7.9250   NaN    S  \n",
       "3  female  35.0       1       0            113803  53.1000  C123    S  \n",
       "4    male  35.0       0       0            373450   8.0500   NaN    S  \n",
       "5    male   NaN       0       0            330877   8.4583   NaN    Q  \n",
       "6    male  54.0       0       0             17463  51.8625   E46    S  \n",
       "7    male   2.0       3       1            349909  21.0750   NaN    S  \n",
       "8  female  27.0       0       2            347742  11.1333   NaN    S  \n",
       "9  female  14.0       1       0            237736  30.0708   NaN    C  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据的前10行\n",
    "data_csv.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "44c3dfe7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['乘客ID', '是否幸存', '仓位等级', '姓名', '性别', '年龄', '兄弟姐妹个数', '父母子女个数', '船票信息',\n",
       "       '票价', '客舱', '登船港口'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据的列名\n",
    "data_csv.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e69a6b2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(891, 12)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据的维度（行数和列数）\n",
    "data_csv.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8599ed5a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 12 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   乘客ID    891 non-null    int64  \n",
      " 1   是否幸存    891 non-null    int64  \n",
      " 2   仓位等级    891 non-null    int64  \n",
      " 3   姓名      891 non-null    object \n",
      " 4   性别      891 non-null    object \n",
      " 5   年龄      714 non-null    float64\n",
      " 6   兄弟姐妹个数  891 non-null    int64  \n",
      " 7   父母子女个数  891 non-null    int64  \n",
      " 8   船票信息    891 non-null    object \n",
      " 9   票价      891 non-null    float64\n",
      " 10  客舱      204 non-null    object \n",
      " 11  登船港口    889 non-null    object \n",
      "dtypes: float64(2), int64(5), object(5)\n",
      "memory usage: 83.7+ KB\n"
     ]
    }
   ],
   "source": [
    "# 查看数据类型和缺失值\n",
    "data_csv.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9569570",
   "metadata": {},
   "source": [
    "5.2 查看数据的描述性统计信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3e471022",
   "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>乘客ID</th>\n",
       "      <th>是否幸存</th>\n",
       "      <th>仓位等级</th>\n",
       "      <th>年龄</th>\n",
       "      <th>兄弟姐妹个数</th>\n",
       "      <th>父母子女个数</th>\n",
       "      <th>票价</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             乘客ID        是否幸存        仓位等级          年龄      兄弟姐妹个数      父母子女个数  \\\n",
       "count  891.000000  891.000000  891.000000  714.000000  891.000000  891.000000   \n",
       "mean   446.000000    0.383838    2.308642   29.699118    0.523008    0.381594   \n",
       "std    257.353842    0.486592    0.836071   14.526497    1.102743    0.806057   \n",
       "min      1.000000    0.000000    1.000000    0.420000    0.000000    0.000000   \n",
       "25%    223.500000    0.000000    2.000000   20.125000    0.000000    0.000000   \n",
       "50%    446.000000    0.000000    3.000000   28.000000    0.000000    0.000000   \n",
       "75%    668.500000    1.000000    3.000000   38.000000    1.000000    0.000000   \n",
       "max    891.000000    1.000000    3.000000   80.000000    8.000000    6.000000   \n",
       "\n",
       "               票价  \n",
       "count  891.000000  \n",
       "mean    32.204208  \n",
       "std     49.693429  \n",
       "min      0.000000  \n",
       "25%      7.910400  \n",
       "50%     14.454200  \n",
       "75%     31.000000  \n",
       "max    512.329200  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 描述性统计信息\n",
    "data_csv.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5b58846",
   "metadata": {},
   "source": [
    "### 步骤 6: 数据筛选和选择    \n",
    "6.1 选择列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b546c94f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      0\n",
       "1      1\n",
       "2      1\n",
       "3      1\n",
       "4      0\n",
       "      ..\n",
       "886    0\n",
       "887    1\n",
       "888    0\n",
       "889    1\n",
       "890    0\n",
       "Name: 是否幸存, Length: 891, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 选择特定列\n",
    "label = data_csv['是否幸存']\n",
    "label"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2468fb88",
   "metadata": {},
   "source": [
    "6.2 根据条件筛选行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9b95d9cb",
   "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>乘客ID</th>\n",
       "      <th>是否幸存</th>\n",
       "      <th>仓位等级</th>\n",
       "      <th>姓名</th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>兄弟姐妹个数</th>\n",
       "      <th>父母子女个数</th>\n",
       "      <th>船票信息</th>\n",
       "      <th>票价</th>\n",
       "      <th>客舱</th>\n",
       "      <th>登船港口</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>E46</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Palsson, Master. Gosta Leonard</td>\n",
       "      <td>male</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>349909</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
       "      <td>female</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Sandstrom, Miss. Marguerite Rut</td>\n",
       "      <td>female</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PP 9549</td>\n",
       "      <td>16.7000</td>\n",
       "      <td>G6</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Bonnell, Miss. Elizabeth</td>\n",
       "      <td>female</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113783</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>C103</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>852</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Svensson, Mr. Johan</td>\n",
       "      <td>male</td>\n",
       "      <td>74.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>347060</td>\n",
       "      <td>7.7750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>853</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Boulos, Miss. Nourelain</td>\n",
       "      <td>female</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2678</td>\n",
       "      <td>15.2458</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>857</th>\n",
       "      <td>858</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Daly, Mr. Peter Denis</td>\n",
       "      <td>male</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113055</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>E17</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869</th>\n",
       "      <td>870</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnson, Master. Harold Theodor</td>\n",
       "      <td>male</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879</th>\n",
       "      <td>880</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)</td>\n",
       "      <td>female</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11767</td>\n",
       "      <td>83.1583</td>\n",
       "      <td>C50</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>142 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     乘客ID  是否幸存  仓位等级                                             姓名      性别  \\\n",
       "6       7     0     1                        McCarthy, Mr. Timothy J    male   \n",
       "7       8     0     3                 Palsson, Master. Gosta Leonard    male   \n",
       "9      10     1     2            Nasser, Mrs. Nicholas (Adele Achem)  female   \n",
       "10     11     1     3                Sandstrom, Miss. Marguerite Rut  female   \n",
       "11     12     1     1                       Bonnell, Miss. Elizabeth  female   \n",
       "..    ...   ...   ...                                            ...     ...   \n",
       "851   852     0     3                            Svensson, Mr. Johan    male   \n",
       "852   853     0     3                        Boulos, Miss. Nourelain  female   \n",
       "857   858     1     1                         Daly, Mr. Peter Denis     male   \n",
       "869   870     1     3                Johnson, Master. Harold Theodor    male   \n",
       "879   880     1     1  Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)  female   \n",
       "\n",
       "       年龄  兄弟姐妹个数  父母子女个数     船票信息       票价    客舱 登船港口  \n",
       "6    54.0       0       0    17463  51.8625   E46    S  \n",
       "7     2.0       3       1   349909  21.0750   NaN    S  \n",
       "9    14.0       1       0   237736  30.0708   NaN    C  \n",
       "10    4.0       1       1  PP 9549  16.7000    G6    S  \n",
       "11   58.0       0       0   113783  26.5500  C103    S  \n",
       "..    ...     ...     ...      ...      ...   ...  ...  \n",
       "851  74.0       0       0   347060   7.7750   NaN    S  \n",
       "852   9.0       1       1     2678  15.2458   NaN    C  \n",
       "857  51.0       0       0   113055  26.5500   E17    S  \n",
       "869   4.0       1       1   347742  11.1333   NaN    S  \n",
       "879  56.0       0       1    11767  83.1583   C50    C  \n",
       "\n",
       "[142 rows x 12 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 筛选出年龄大于50岁或者小于15岁的行\n",
    "filtered_data = data_csv[(data_csv['年龄'] > 50)|(data_csv['年龄'] < 15)]\n",
    "filtered_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "227dca34",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}