commit 655911b74834b9271b077fb3d163404d5c8f139f Author: dev_xulongjin Date: Mon Apr 14 16:06:13 2025 +0800 chore(project): 初始化项目结构和配置 - 添加 .idea 目录和相关配置文件，设置项目忽略文件、编码、模块管理等 - 创建商务大数据分析目录和子目录，准备数据和任务笔记本 - 添加示例数据文件：中国城市人口数据.csv - 创建任务笔记本文件，进行数据处理和分析示例 diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000..13566b8 --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,8 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Editor-based HTTP Client requests +/httpRequests/ +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml diff --git a/.idea/encodings.xml b/.idea/encodings.xml new file mode 100644 index 0000000..bd1b04f --- /dev/null +++ b/.idea/encodings.xml @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/.idea/gcc-project-py-25-2.iml b/.idea/gcc-project-py-25-2.iml new file mode 100644 index 0000000..4c8cdd0 --- /dev/null +++ b/.idea/gcc-project-py-25-2.iml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 0000000..105ce2d --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000..020aa4a --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,6 @@ + + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 0000000..01f34e1 --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml new file mode 100644 index 0000000..d843f34 --- /dev/null +++ b/.idea/vcs.xml @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/商务大数据分析/20250402/data/中国城市人口数据.csv b/商务大数据分析/20250402/data/中国城市人口数据.csv new file mode 100644 index 0000000..b84e70b --- /dev/null +++ b/商务大数据分析/20250402/data/中国城市人口数据.csv @@ -0,0 +1,23 @@ +ʡ,2020˿ڣˣ,2019˿ڣˣ +ӱʡ,7461,7447 +ɽʡ,3492,3497 +ʡ,4259,4277 +ʡ,2407,2448 +ʡ,8475,8469 +㽭ʡ,6457,6375 +ʡ,6103,6092 +ʡ,4154,4137 +ʡ,4519,4516 +ɽʡ,10153,10106 +ʡ,9937,9901 +ʡ,5775,5927 +ʡ,6644,6640 +㶫ʡ,12601,12489 +ʡ,1008,995 +Ĵʡ,8367,8351 +ʡ,3856,3848 +ʡ,4721,4714 +ʡ,3953,3944 +ʡ,2502,2509 +ຣʡ,592,590 +ʡ,3185,3255 diff --git a/商务大数据分析/20250402/data/某地区房屋销售数据 (1).csv b/商务大数据分析/20250402/data/某地区房屋销售数据 (1).csv new file mode 100644 index 0000000..7d5d854 --- /dev/null +++ b/商务大数据分析/20250402/data/某地区房屋销售数据 (1).csv @@ -0,0 +1,27369 @@ +ݳʱ,ʱ,ݼ۸,,׷ +2010/1/4 0:00,2615,435000,house,3 +2010/1/5 0:00,2904,712000,house,4 +2010/1/6 0:00,2617,435000,house,4 +2010/1/6 0:00,2606,1350000,house,5 +2010/1/7 0:00,2905,612500,house,4 +2010/1/8 0:00,2614,420500,house,3 +2010/1/8 0:00,2902,432600,house,3 +2010/1/11 0:00,2903,525000,house,4 +2010/1/11 0:00,2611,535000,house,4 +2010/1/11 0:00,2913,640000,house,4 +2010/1/13 0:00,2617,519000,house,5 +2010/1/13 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" + ] + }, + "execution_count": 126, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 126 + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/商务大数据分析/20250402/task2.ipynb b/商务大数据分析/20250402/task2.ipynb new file mode 100644 index 0000000..7cfc989 --- /dev/null +++ b/商务大数据分析/20250402/task2.ipynb @@ -0,0 +1,478 @@ +{ + "cells": [ + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-04-02T07:57:56.382179Z", + "start_time": "2025-04-02T07:57:55.984261Z" + } + }, + "cell_type": "code", + "source": "import pandas as pd", + "id": "3244cf38b10be81b", + "outputs": [], + "execution_count": 1 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-04-02T08:00:15.267189Z", + "start_time": "2025-04-02T08:00:15.229542Z" + } + }, + "cell_type": "code", + "source": [ + "data = pd.read_csv('data/某地区房屋销售数据 (1).csv', encoding='gbk')\n", + "data['new_postcode'] = data['地区邮编'].apply(lambda x: str(x)[:2])\n", + "data.head(3)" + ], + "id": "d973cf9fe6ac90a6", + "outputs": [ + { + "data": { + "text/plain": [ + " 房屋出售时间 地区邮编 房屋价格 房屋类型 配套房间数 new_postcode\n", + "0 2010/1/4 0:00 2615 435000 house 3 26\n", + "1 2010/1/5 0:00 2904 712000 house 4 29\n", + "2 2010/1/6 0:00 2617 435000 house 4 26" + ], + "text/html": [ + "
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12010/1/5 0:002904712000house429
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房屋类型houseunit
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" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 7 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-04-02T08:04:41.035870Z", + "start_time": "2025-04-02T08:04:41.012959Z" + } + }, + "cell_type": "code", + "source": [ + "# 3、不同类型房产和不同房间数的房价之间的比较，使用pivot_table函数\n", + "data.pivot_table(values='房屋价格', index='房屋类型', columns='配套房间数', aggfunc='mean')" + ], + "id": "4ed9b36daea1c503", + "outputs": [ + { + "data": { + "text/plain": [ + "配套房间数 0 1 2 3 \\\n", + "房屋类型 \n", + "house 677394.736842 353634.269663 489555.889339 560117.683516 \n", + "unit 330850.000000 336570.325391 432502.153116 594535.982287 \n", + "\n", + "配套房间数 4 5 \n", + "房屋类型 \n", + "house 730667.024375 9.290297e+05 \n", + "unit 641736.842105 1.146333e+06 " + ], + "text/html": [ + "
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配套房间数012345
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