notebooks/03_Pandas.ipynb

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  "metadata": {
    "colab": {
      "name": "03_Pandas",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "metadata": {
        "id": "bOChJSNXtC9g",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Pandas"
      ]
    },
    {
      "metadata": {
        "id": "OLIxEDq6VhvZ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "<img src=\"https://raw.githubusercontent.com/LisonEvf/practicalAI-cn/master/images/logo.png\" width=150>\n",
        "\n",
        "在本文中，我们将学习使用Python Pandas库进行数据分析的基础知识。\n",
        "\n",
        "<img src=\"https://raw.githubusercontent.com/LisonEvf/practicalAI-cn/master/images/pandas.png\" width=500>\n",
        "\n",
        "\n"
      ]
    },
    {
      "metadata": {
        "id": "VoMq0eFRvugb",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 下载数据"
      ]
    },
    {
      "metadata": {
        "id": "qWro5T5qTJJL",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "首先，我们要获得一些数据。我们将从下面的公共链接中下载titanic数据集。"
      ]
    },
    {
      "metadata": {
        "id": "cdg5wEFcV6qA",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import urllib"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "6FuyDUTFVY7J",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# 将数据从GitHub下载到笔记本电脑的本地磁盘\n",
        "url = \"https://raw.githubusercontent.com/LisonEvf/practicalAI-cn/master/data/titanic.csv\"\n",
        "response = urllib.request.urlopen(url)\n",
        "html = response.read()\n",
        "with open('titanic.csv', 'wb') as f:\n",
        "    f.write(html)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "TK3wsHCFhldU",
        "colab_type": "code",
        "outputId": "3c617391-f929-4956-ab76-2e53b64abdf3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "cell_type": "code",
      "source": [
        "# 检查数据是否已下载成功\n",
        "!ls -l "
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "total 96\n",
            "-rw-r--r-- 1 root root  6975 Dec 16 12:45 processed_titanic.csv\n",
            "drwxr-xr-x 1 root root  4096 Dec 10 17:34 sample_data\n",
            "-rw-r--r-- 1 root root 85153 Dec 16 12:46 titanic.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "TL4rwLUSW9hV",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 加载数据"
      ]
    },
    {
      "metadata": {
        "id": "4EOXMnGHiLxM",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "现在我们有一些数据可以使用，让我们加载到Pandas数据帧（dataframe）中。Pandas是一个很棒的python数据库分析库。"
      ]
    },
    {
      "metadata": {
        "id": "-Zd-zoyjaaw2",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "ywaEF_0aQ023",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# 从CSV读取到Pandas DataFrame\n",
        "df = pd.read_csv(\"titanic.csv\", header=0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "J79FUzZWQ-kx",
        "colab_type": "code",
        "outputId": "3ccab6de-901e-42d2-8032-9307c5448a04",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 前五项\n",
        "df.head()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "    }\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>pclass</th>\n",
              "      <th>name</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>ticket</th>\n",
              "      <th>fare</th>\n",
              "      <th>cabin</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Allen, Miss. Elisabeth Walton</td>\n",
              "      <td>female</td>\n",
              "      <td>29.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>24160</td>\n",
              "      <td>211.3375</td>\n",
              "      <td>B5</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Master. Hudson Trevor</td>\n",
              "      <td>male</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Miss. Helen Loraine</td>\n",
              "      <td>female</td>\n",
              "      <td>2.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Mr. Hudson Joshua Creighton</td>\n",
              "      <td>male</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
              "      <td>female</td>\n",
              "      <td>25.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   pclass                                             name     sex      age  \\\n",
              "0       1                    Allen, Miss. Elisabeth Walton  female  29.0000   \n",
              "1       1                   Allison, Master. Hudson Trevor    male   0.9167   \n",
              "2       1                     Allison, Miss. Helen Loraine  female   2.0000   \n",
              "3       1             Allison, Mr. Hudson Joshua Creighton    male  30.0000   \n",
              "4       1  Allison, Mrs. Hudson J C (Bessie Waldo Daniels)  female  25.0000   \n",
              "\n",
              "   sibsp  parch  ticket      fare    cabin embarked  survived  \n",
              "0      0      0   24160  211.3375       B5        S         1  \n",
              "1      1      2  113781  151.5500  C22 C26        S         1  \n",
              "2      1      2  113781  151.5500  C22 C26        S         0  \n",
              "3      1      2  113781  151.5500  C22 C26        S         0  \n",
              "4      1      2  113781  151.5500  C22 C26        S         0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "metadata": {
        "id": "qhYyM3iGRZ8W",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "他们有不同的特征: \n",
        "* pclass: class of travel\n",
        "* name: full name of the passenger\n",
        "* sex: gender\n",
        "* age: numerical age\n",
        "* sibsp: # of siblings/spouse aboard\n",
        "* parch: number of parents/child aboard\n",
        "* ticket: ticket number\n",
        "* fare: cost of the ticket\n",
        "* cabin: location of room\n",
        "* emarked: port that the passenger embarked at (C - Cherbourg, S - Southampton, Q = Queenstown)\n",
        "* survived: survial metric (0 - died, 1 - survived)"
      ]
    },
    {
      "metadata": {
        "id": "NBx5VP8K_y6N",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 探索性分析"
      ]
    },
    {
      "metadata": {
        "id": "DD14WJ1G_zum",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "我们将使用Pandas库，看看如何探索和处理我们的数据。"
      ]
    },
    {
      "metadata": {
        "id": "thR28yTmASRr",
        "colab_type": "code",
        "outputId": "798b1a62-eb6a-46d5-e527-449fc7f32bb2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "cell_type": "code",
      "source": [
        "# 描述性统计\n",
        "df.describe()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\n",
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              "    }\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>pclass</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1309.000000</td>\n",
              "      <td>1046.000000</td>\n",
              "      <td>1309.000000</td>\n",
              "      <td>1309.000000</td>\n",
              "      <td>1308.000000</td>\n",
              "      <td>1309.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2.294882</td>\n",
              "      <td>29.881135</td>\n",
              "      <td>0.498854</td>\n",
              "      <td>0.385027</td>\n",
              "      <td>33.295479</td>\n",
              "      <td>0.381971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.837836</td>\n",
              "      <td>14.413500</td>\n",
              "      <td>1.041658</td>\n",
              "      <td>0.865560</td>\n",
              "      <td>51.758668</td>\n",
              "      <td>0.486055</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.166700</td>\n",
              "      <td>0.000000</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>2.000000</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>7.895800</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\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",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>39.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>31.275000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>512.329200</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            pclass          age        sibsp        parch         fare  \\\n",
              "count  1309.000000  1046.000000  1309.000000  1309.000000  1308.000000   \n",
              "mean      2.294882    29.881135     0.498854     0.385027    33.295479   \n",
              "std       0.837836    14.413500     1.041658     0.865560    51.758668   \n",
              "min       1.000000     0.166700     0.000000     0.000000     0.000000   \n",
              "25%       2.000000    21.000000     0.000000     0.000000     7.895800   \n",
              "50%       3.000000    28.000000     0.000000     0.000000    14.454200   \n",
              "75%       3.000000    39.000000     1.000000     0.000000    31.275000   \n",
              "max       3.000000    80.000000     8.000000     9.000000   512.329200   \n",
              "\n",
              "          survived  \n",
              "count  1309.000000  \n",
              "mean      0.381971  \n",
              "std       0.486055  \n",
              "min       0.000000  \n",
              "25%       0.000000  \n",
              "50%       0.000000  \n",
              "75%       1.000000  \n",
              "max       1.000000  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "metadata": {
        "id": "Mn5HqS3XmzJs",
        "colab_type": "code",
        "outputId": "bb849441-d178-4559-bb7a-e3d9ef3caefb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        }
      },
      "cell_type": "code",
      "source": [
        "# 直方图\n",
        "df[\"age\"].hist()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff8acc5c4a8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<matplotlib.figure.Figure at 0x7ff8accabf60>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "7illbHR1nLEF",
        "colab_type": "code",
        "outputId": "38dd59af-3901-485d-8335-8d9aef4cb204",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# 唯一值\n",
        "df[\"embarked\"].unique()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['S', 'C', nan, 'Q'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "metadata": {
        "id": "BG1IMeV_hrqV",
        "colab_type": "code",
        "outputId": "5499f70f-9a64-4371-b185-e1f56b62bbb9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 118
        }
      },
      "cell_type": "code",
      "source": [
        "# 根据特征选择数据\n",
        "df[\"name\"].head()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0                      Allen, Miss. Elisabeth Walton\n",
              "1                     Allison, Master. Hudson Trevor\n",
              "2                       Allison, Miss. Helen Loraine\n",
              "3               Allison, Mr. Hudson Joshua Creighton\n",
              "4    Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\n",
              "Name: name, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "metadata": {
        "id": "wPrRGLDtiZSp",
        "colab_type": "code",
        "outputId": "7e32434d-0a96-44c0-e54d-2dc45e04c5c7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 筛选\n",
        "df[df[\"sex\"]==\"female\"].head() # 只有女性数据出现"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>pclass</th>\n",
              "      <th>name</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>ticket</th>\n",
              "      <th>fare</th>\n",
              "      <th>cabin</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Allen, Miss. Elisabeth Walton</td>\n",
              "      <td>female</td>\n",
              "      <td>29.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>24160</td>\n",
              "      <td>211.3375</td>\n",
              "      <td>B5</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Miss. Helen Loraine</td>\n",
              "      <td>female</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
              "      <td>female</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1</td>\n",
              "      <td>Andrews, Miss. Kornelia Theodosia</td>\n",
              "      <td>female</td>\n",
              "      <td>63.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>13502</td>\n",
              "      <td>77.9583</td>\n",
              "      <td>D7</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1</td>\n",
              "      <td>Appleton, Mrs. Edward Dale (Charlotte Lamson)</td>\n",
              "      <td>female</td>\n",
              "      <td>53.0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>11769</td>\n",
              "      <td>51.4792</td>\n",
              "      <td>C101</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   pclass                                             name     sex   age  \\\n",
              "0       1                    Allen, Miss. Elisabeth Walton  female  29.0   \n",
              "2       1                     Allison, Miss. Helen Loraine  female   2.0   \n",
              "4       1  Allison, Mrs. Hudson J C (Bessie Waldo Daniels)  female  25.0   \n",
              "6       1                Andrews, Miss. Kornelia Theodosia  female  63.0   \n",
              "8       1    Appleton, Mrs. Edward Dale (Charlotte Lamson)  female  53.0   \n",
              "\n",
              "   sibsp  parch  ticket      fare    cabin embarked  survived  \n",
              "0      0      0   24160  211.3375       B5        S         1  \n",
              "2      1      2  113781  151.5500  C22 C26        S         0  \n",
              "4      1      2  113781  151.5500  C22 C26        S         0  \n",
              "6      1      0   13502   77.9583       D7        S         1  \n",
              "8      2      0   11769   51.4792     C101        S         1  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "metadata": {
        "id": "FOuLeYIojMMH",
        "colab_type": "code",
        "outputId": "aa4fbb43-cf32-4e6c-e92f-c97ad79da9d1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 排序\n",
        "df.sort_values(\"age\", ascending=False).head()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>pclass</th>\n",
              "      <th>name</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>ticket</th>\n",
              "      <th>fare</th>\n",
              "      <th>cabin</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1</td>\n",
              "      <td>Barkworth, Mr. Algernon Henry Wilson</td>\n",
              "      <td>male</td>\n",
              "      <td>80.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>27042</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>A23</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>61</th>\n",
              "      <td>1</td>\n",
              "      <td>Cavendish, Mrs. Tyrell William (Julia Florence...</td>\n",
              "      <td>female</td>\n",
              "      <td>76.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>19877</td>\n",
              "      <td>78.8500</td>\n",
              "      <td>C46</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1235</th>\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",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>135</th>\n",
              "      <td>1</td>\n",
              "      <td>Goldschmidt, Mr. George B</td>\n",
              "      <td>male</td>\n",
              "      <td>71.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>PC 17754</td>\n",
              "      <td>34.6542</td>\n",
              "      <td>A5</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1</td>\n",
              "      <td>Artagaveytia, Mr. Ramon</td>\n",
              "      <td>male</td>\n",
              "      <td>71.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>PC 17609</td>\n",
              "      <td>49.5042</td>\n",
              "      <td>NaN</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      pclass                                               name     sex   age  \\\n",
              "14         1               Barkworth, Mr. Algernon Henry Wilson    male  80.0   \n",
              "61         1  Cavendish, Mrs. Tyrell William (Julia Florence...  female  76.0   \n",
              "1235       3                                Svensson, Mr. Johan    male  74.0   \n",
              "135        1                          Goldschmidt, Mr. George B    male  71.0   \n",
              "9          1                            Artagaveytia, Mr. Ramon    male  71.0   \n",
              "\n",
              "      sibsp  parch    ticket     fare cabin embarked  survived  \n",
              "14        0      0     27042  30.0000   A23        S         1  \n",
              "61        1      0     19877  78.8500   C46        S         1  \n",
              "1235      0      0    347060   7.7750   NaN        S         0  \n",
              "135       0      0  PC 17754  34.6542    A5        C         0  \n",
              "9         0      0  PC 17609  49.5042   NaN        C         0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "metadata": {
        "id": "v0TCbtSMjMO5",
        "colab_type": "code",
        "outputId": "5c602a41-3250-48e1-f5c2-973340a20708",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 135
        }
      },
      "cell_type": "code",
      "source": [
        "# Grouping（数据聚合与分组运算）\n",
        "sex_group = df.groupby(\"survived\")\n",
        "sex_group.mean()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>pclass</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>survived</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2.500618</td>\n",
              "      <td>30.545369</td>\n",
              "      <td>0.521632</td>\n",
              "      <td>0.328801</td>\n",
              "      <td>23.353831</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.962000</td>\n",
              "      <td>28.918228</td>\n",
              "      <td>0.462000</td>\n",
              "      <td>0.476000</td>\n",
              "      <td>49.361184</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            pclass        age     sibsp     parch       fare\n",
              "survived                                                    \n",
              "0         2.500618  30.545369  0.521632  0.328801  23.353831\n",
              "1         1.962000  28.918228  0.462000  0.476000  49.361184"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "metadata": {
        "id": "34LmckWDhdSA",
        "colab_type": "code",
        "outputId": "0befc9a0-b30b-472b-ef19-e092b8da6f28",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 220
        }
      },
      "cell_type": "code",
      "source": [
        "# iloc根据位置的索引来访问\n",
        "df.iloc[0, :] # iloc在索引中的特定位置获取行（或列）（因此它只需要整数）"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pclass                                  1\n",
              "name        Allen, Miss. Elisabeth Walton\n",
              "sex                                female\n",
              "age                                    29\n",
              "sibsp                                   0\n",
              "parch                                   0\n",
              "ticket                              24160\n",
              "fare                              211.338\n",
              "cabin                                  B5\n",
              "embarked                                S\n",
              "survived                                1\n",
              "Name: 0, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "metadata": {
        "id": "QrdXeuRdFkXB",
        "colab_type": "code",
        "outputId": "1f6b255f-7ed1-463c-adb6-55a026881d56",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# 获取指定位置的数据\n",
        "df.iloc[0, 1]\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Allen, Miss. Elisabeth Walton'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "metadata": {
        "id": "Rz35_-x2FkaL",
        "colab_type": "code",
        "outputId": "4d50ef2b-f1d7-4b50-84ea-44a11d1b360a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 220
        }
      },
      "cell_type": "code",
      "source": [
        "# loc根据标签的索引来访问\n",
        "df.loc[0] # loc从索引中获取具有特定标签的行（或列）"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pclass                                  1\n",
              "name        Allen, Miss. Elisabeth Walton\n",
              "sex                                female\n",
              "age                                    29\n",
              "sibsp                                   0\n",
              "parch                                   0\n",
              "ticket                              24160\n",
              "fare                              211.338\n",
              "cabin                                  B5\n",
              "embarked                                S\n",
              "survived                                1\n",
              "Name: 0, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "metadata": {
        "id": "uSezrq4vEFYh",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 预处理"
      ]
    },
    {
      "metadata": {
        "id": "EZ1pCKHIjMUY",
        "colab_type": "code",
        "outputId": "90120eb7-0764-4feb-f084-399d4f7f3081",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 具有至少一个NaN值的行\n",
        "df[pd.isnull(df).any(axis=1)].head()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>pclass</th>\n",
              "      <th>name</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>ticket</th>\n",
              "      <th>fare</th>\n",
              "      <th>cabin</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1</td>\n",
              "      <td>Artagaveytia, Mr. Ramon</td>\n",
              "      <td>male</td>\n",
              "      <td>71.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>PC 17609</td>\n",
              "      <td>49.5042</td>\n",
              "      <td>NaN</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1</td>\n",
              "      <td>Barber, Miss. Ellen \"Nellie\"</td>\n",
              "      <td>female</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>19877</td>\n",
              "      <td>78.8500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1</td>\n",
              "      <td>Baumann, Mr. John D</td>\n",
              "      <td>male</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>PC 17318</td>\n",
              "      <td>25.9250</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>1</td>\n",
              "      <td>Bidois, Miss. Rosalie</td>\n",
              "      <td>female</td>\n",
              "      <td>42.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>PC 17757</td>\n",
              "      <td>227.5250</td>\n",
              "      <td>NaN</td>\n",
              "      <td>C</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>1</td>\n",
              "      <td>Birnbaum, Mr. Jakob</td>\n",
              "      <td>male</td>\n",
              "      <td>25.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>13905</td>\n",
              "      <td>26.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    pclass                          name     sex   age  sibsp  parch  \\\n",
              "9        1       Artagaveytia, Mr. Ramon    male  71.0      0      0   \n",
              "13       1  Barber, Miss. Ellen \"Nellie\"  female  26.0      0      0   \n",
              "15       1           Baumann, Mr. John D    male   NaN      0      0   \n",
              "23       1         Bidois, Miss. Rosalie  female  42.0      0      0   \n",
              "25       1           Birnbaum, Mr. Jakob    male  25.0      0      0   \n",
              "\n",
              "      ticket      fare cabin embarked  survived  \n",
              "9   PC 17609   49.5042   NaN        C         0  \n",
              "13     19877   78.8500   NaN        S         1  \n",
              "15  PC 17318   25.9250   NaN        S         0  \n",
              "23  PC 17757  227.5250   NaN        C         1  \n",
              "25     13905   26.0000   NaN        C         0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "metadata": {
        "id": "zUaiFplEkmoB",
        "colab_type": "code",
        "outputId": "65b701a3-6d72-4914-f920-67561a59a73e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 删除具有Nan值的行\n",
        "df = df.dropna() # 删除具有NaN值的行\n",
        "df = df.reset_index() # 重置行索引\n",
        "df.head()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>pclass</th>\n",
              "      <th>name</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>ticket</th>\n",
              "      <th>fare</th>\n",
              "      <th>cabin</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Allen, Miss. Elisabeth Walton</td>\n",
              "      <td>female</td>\n",
              "      <td>29.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>24160</td>\n",
              "      <td>211.3375</td>\n",
              "      <td>B5</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Master. Hudson Trevor</td>\n",
              "      <td>male</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Miss. Helen Loraine</td>\n",
              "      <td>female</td>\n",
              "      <td>2.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Mr. Hudson Joshua Creighton</td>\n",
              "      <td>male</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
              "      <td>female</td>\n",
              "      <td>25.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>113781</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>C22 C26</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index  pclass                                             name     sex  \\\n",
              "0      0       1                    Allen, Miss. Elisabeth Walton  female   \n",
              "1      1       1                   Allison, Master. Hudson Trevor    male   \n",
              "2      2       1                     Allison, Miss. Helen Loraine  female   \n",
              "3      3       1             Allison, Mr. Hudson Joshua Creighton    male   \n",
              "4      4       1  Allison, Mrs. Hudson J C (Bessie Waldo Daniels)  female   \n",
              "\n",
              "       age  sibsp  parch  ticket      fare    cabin embarked  survived  \n",
              "0  29.0000      0      0   24160  211.3375       B5        S         1  \n",
              "1   0.9167      1      2  113781  151.5500  C22 C26        S         1  \n",
              "2   2.0000      1      2  113781  151.5500  C22 C26        S         0  \n",
              "3  30.0000      1      2  113781  151.5500  C22 C26        S         0  \n",
              "4  25.0000      1      2  113781  151.5500  C22 C26        S         0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "metadata": {
        "id": "ubujZv_8qG-d",
        "colab_type": "code",
        "outputId": "3a397700-f1ff-496b-e585-ef0ad7c2b37f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 删除多行\n",
        "df = df.drop([\"name\", \"cabin\", \"ticket\"], axis=1) # we won't use text features for our initial basic models\n",
        "df.head()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>pclass</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>29.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>211.3375</td>\n",
              "      <td>S</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>male</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>S</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>2.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>male</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>25.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>S</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index  pclass     sex      age  sibsp  parch      fare embarked  survived\n",
              "0      0       1  female  29.0000      0      0  211.3375        S         1\n",
              "1      1       1    male   0.9167      1      2  151.5500        S         1\n",
              "2      2       1  female   2.0000      1      2  151.5500        S         0\n",
              "3      3       1    male  30.0000      1      2  151.5500        S         0\n",
              "4      4       1  female  25.0000      1      2  151.5500        S         0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "metadata": {
        "id": "8m117GcVnon9",
        "colab_type": "code",
        "outputId": "ee33bb3e-c64b-4e2c-8e82-03e669b7bcba",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 映射特征值\n",
        "df['sex'] = df['sex'].map( {'female': 0, 'male': 1} ).astype(int)\n",
        "df[\"embarked\"] = df['embarked'].dropna().map( {'S':0, 'C':1, 'Q':2} ).astype(int)\n",
        "df.head()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>pclass</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
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              "      <td>1</td>\n",
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              "      <th>2</th>\n",
              "      <td>2</td>\n",
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              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>30.0000</td>\n",
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              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>25.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index  pclass  sex      age  sibsp  parch      fare  embarked  survived\n",
              "0      0       1    0  29.0000      0      0  211.3375         0         1\n",
              "1      1       1    1   0.9167      1      2  151.5500         0         1\n",
              "2      2       1    0   2.0000      1      2  151.5500         0         0\n",
              "3      3       1    1  30.0000      1      2  151.5500         0         0\n",
              "4      4       1    0  25.0000      1      2  151.5500         0         0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "metadata": {
        "id": "ZaVqjpsCEtft",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 特征工程"
      ]
    },
    {
      "metadata": {
        "id": "_FPtk5tpqrDI",
        "colab_type": "code",
        "outputId": "72c426bb-005d-4b47-a9d4-8cbe28e936c5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# lambda表达式创建新特征\n",
        "def get_family_size(sibsp, parch):\n",
        "    family_size = sibsp + parch\n",
        "    return family_size\n",
        "\n",
        "df[\"family_size\"] = df[[\"sibsp\", \"parch\"]].apply(lambda x: get_family_size(x[\"sibsp\"], x[\"parch\"]), axis=1)\n",
        "df.head()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>pclass</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "      <th>family_size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
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              "      <td>211.3375</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>25.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index  pclass  sex      age  sibsp  parch      fare  embarked  survived  \\\n",
              "0      0       1    0  29.0000      0      0  211.3375         0         1   \n",
              "1      1       1    1   0.9167      1      2  151.5500         0         1   \n",
              "2      2       1    0   2.0000      1      2  151.5500         0         0   \n",
              "3      3       1    1  30.0000      1      2  151.5500         0         0   \n",
              "4      4       1    0  25.0000      1      2  151.5500         0         0   \n",
              "\n",
              "   family_size  \n",
              "0            0  \n",
              "1            3  \n",
              "2            3  \n",
              "3            3  \n",
              "4            3  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "metadata": {
        "id": "JK3FqfjnpSNi",
        "colab_type": "code",
        "outputId": "80aedded-c9f6-40cb-b073-cf8afab75531",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        }
      },
      "cell_type": "code",
      "source": [
        "# 重新组织标题\n",
        "df = df[['pclass', 'sex', 'age', 'sibsp', 'parch', 'family_size', 'fare', 'embarked', 'survived']]\n",
        "df.head()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>pclass</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>family_size</th>\n",
              "      <th>fare</th>\n",
              "      <th>embarked</th>\n",
              "      <th>survived</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>25.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>151.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   pclass  sex      age  sibsp  parch  family_size      fare  embarked  \\\n",
              "0       1    0  29.0000      0      0            0  211.3375         0   \n",
              "1       1    1   0.9167      1      2            3  151.5500         0   \n",
              "2       1    0   2.0000      1      2            3  151.5500         0   \n",
              "3       1    1  30.0000      1      2            3  151.5500         0   \n",
              "4       1    0  25.0000      1      2            3  151.5500         0   \n",
              "\n",
              "   survived  \n",
              "0         1  \n",
              "1         1  \n",
              "2         0  \n",
              "3         0  \n",
              "4         0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "metadata": {
        "id": "N_rwgfrFGTne",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 保存数据"
      ]
    },
    {
      "metadata": {
        "id": "rNNxA7Vrp2fC",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# 保存数据帧（dataframe）到 CSV\n",
        "df.to_csv(\"processed_titanic.csv\", index=False)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "gfc7Epp7sgqz",
        "colab_type": "code",
        "outputId": "e1e21143-2e87-43cb-aa16-b0af114a1b4a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "cell_type": "code",
      "source": [
        "# 看你一下你保持的文件\n",
        "!ls -l"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "total 96\n",
            "-rw-r--r-- 1 root root  6975 Dec 16 12:46 processed_titanic.csv\n",
            "drwxr-xr-x 1 root root  4096 Dec 10 17:34 sample_data\n",
            "-rw-r--r-- 1 root root 85153 Dec 16 12:46 titanic.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "i1rVSjsdDaTw",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}