{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 人工智能与机器学习-实验1\n", "## Part IV. Pandas库的使用\n", "\n", "|学号 |姓名 |\n", "|----------|--------|\n", "| | |\n", "\n", "本部分的实验，需要自己在网络学习相关基础函数使用。" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 1: 导入可能需要的库" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import numpy as np\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 2: 读取数据集" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "titanic = pd.read_csv('titanic.csv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step3: 显示数据集的前5行和后5行" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 4: 该数据集有多少行和列？" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 5: 将PassengerID设置为索引" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
PassengerId
103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
503Allen, Mr. William Henrymale35.0003734508.0500NaNS
....................................
88702Montvila, Rev. Juozasmale27.00021153613.0000NaNS
88811Graham, Miss. Margaret Edithfemale19.00011205330.0000B42S
88903Johnston, Miss. Catherine Helen \"Carrie\"femaleNaN12W./C. 660723.4500NaNS
89011Behr, Mr. Karl Howellmale26.00011136930.0000C148C
89103Dooley, Mr. Patrickmale32.0003703767.7500NaNQ
\n", "

891 rows × 11 columns

\n", "
" ], "text/plain": [ " Survived Pclass \\\n", "PassengerId \n", "1 0 3 \n", "2 1 1 \n", "3 1 3 \n", "4 1 1 \n", "5 0 3 \n", "... ... ... \n", "887 0 2 \n", "888 1 1 \n", "889 0 3 \n", "890 1 1 \n", "891 0 3 \n", "\n", " Name Sex Age \\\n", "PassengerId \n", "1 Braund, Mr. Owen Harris male 22.0 \n", "2 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 \n", "3 Heikkinen, Miss. Laina female 26.0 \n", "4 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 \n", "5 Allen, Mr. William Henry male 35.0 \n", "... ... ... ... \n", "887 Montvila, Rev. Juozas male 27.0 \n", "888 Graham, Miss. Margaret Edith female 19.0 \n", "889 Johnston, Miss. Catherine Helen \"Carrie\" female NaN \n", "890 Behr, Mr. Karl Howell male 26.0 \n", "891 Dooley, Mr. Patrick male 32.0 \n", "\n", " SibSp Parch Ticket Fare Cabin Embarked \n", "PassengerId \n", "1 1 0 A/5 21171 7.2500 NaN S \n", "2 1 0 PC 17599 71.2833 C85 C \n", "3 0 0 STON/O2. 3101282 7.9250 NaN S \n", "4 1 0 113803 53.1000 C123 S \n", "5 0 0 373450 8.0500 NaN S \n", "... ... ... ... ... ... ... \n", "887 0 0 211536 13.0000 NaN S \n", "888 0 0 112053 30.0000 B42 S \n", "889 1 2 W./C. 6607 23.4500 NaN S \n", "890 0 0 111369 30.0000 C148 C \n", "891 0 0 370376 7.7500 NaN Q \n", "\n", "[891 rows x 11 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "titanic.set_index('PassengerId')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 6：数据中有缺失值吗？" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 7: 乘客的最大年龄和最小年龄是多少？" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 8: 有多少人生还？" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 9: 男性和女性的生还比例分别是多少？" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 10: 按照船票价格降序排列" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 11: 绘制一个展示船票价格的直方图" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 12: 绘制乘客年龄与船票价格的散点图" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# 请填写相应代码\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" } }, "nbformat": 4, "nbformat_minor": 2 }