937 lines
26 KiB
Plaintext
937 lines
26 KiB
Plaintext
{
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"cells": [
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"请读取二手车数据源，完成以下需求，在notebook中运行代码，将完整运行结果导出为pdf上传。\n",
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"\n",
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"1、车辆价格分布情况\n",
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"\n",
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"2、车辆销量品牌分布\n",
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"\n",
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"3、排放标准分析\n",
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"\n",
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"4、车龄分析\n",
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"\n",
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"5、里程分析\n",
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"\n",
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"6、折旧价格分析\n",
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"\n",
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"7、不同品牌新车平均价格对比\n",
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"\n",
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"8、排放标准与行驶里程的关系\n",
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"\n",
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"9、车龄与二手车价格的相关性"
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],
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"id": "2ce470d74c7f8f38"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-23T06:44:52.013294Z",
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"start_time": "2025-04-23T06:44:51.744723Z"
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}
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},
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"cell_type": "code",
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"source": "import pandas as pd",
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"id": "ca151ea5138a6483",
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"outputs": [],
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"execution_count": 1
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-18T02:17:28.463954Z",
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"start_time": "2025-04-18T02:17:28.440605Z"
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}
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},
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"cell_type": "code",
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"source": [
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"car = pd.read_csv('./data/second_cars_info.csv',encoding='gbk')\n",
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"car.head(5)"
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],
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"id": "cafa1492fc572672",
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"outputs": [
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{
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"data": {
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"text/plain": [
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" Brand Name Boarding_time Km Discharge排放标准 \\\n",
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"0 奥迪 奥迪A6L 2006款 2.4 CVT 舒适型 2006年8月 9.00万公里 国3 \n",
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"1 奥迪 奥迪A6L 2007款 2.4 CVT 舒适型 2007年1月 8.00万公里 国4 \n",
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"2 奥迪 奥迪A6L 2004款 2.4L 技术领先型 2005年5月 15.00万公里 国2 \n",
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"3 奥迪 奥迪A8L 2013款 45 TFSI quattro舒适型 2013年10月 4.80万公里 欧4 \n",
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"4 奥迪 奥迪A6L 2014款 30 FSI 豪华型 2014年9月 0.81万公里 国4,国5 \n",
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"\n",
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" Sec_price New_price \n",
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"0 6.90 50.89万 \n",
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"1 8.88 50.89万 \n",
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"2 3.82 54.24万 \n",
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"3 44.80 101.06万 \n",
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"4 33.19 54.99万 "
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],
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Brand</th>\n",
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" <th>Name</th>\n",
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" <th>Boarding_time</th>\n",
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" <th>Km</th>\n",
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" <th>Discharge排放标准</th>\n",
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" <th>Sec_price</th>\n",
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" <th>New_price</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>奥迪</td>\n",
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" <td>奥迪A6L 2006款 2.4 CVT 舒适型</td>\n",
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" <td>2006年8月</td>\n",
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" <td>9.00万公里</td>\n",
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" <td>国3</td>\n",
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" <td>6.90</td>\n",
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" <td>50.89万</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>奥迪</td>\n",
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" <td>奥迪A6L 2007款 2.4 CVT 舒适型</td>\n",
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" <td>2007年1月</td>\n",
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" <td>8.00万公里</td>\n",
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" <td>国4</td>\n",
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" <td>8.88</td>\n",
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" <td>50.89万</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>奥迪</td>\n",
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" <td>奥迪A6L 2004款 2.4L 技术领先型</td>\n",
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" <td>2005年5月</td>\n",
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" <td>15.00万公里</td>\n",
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" <td>国2</td>\n",
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" <td>3.82</td>\n",
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" <td>54.24万</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>奥迪</td>\n",
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" <td>奥迪A8L 2013款 45 TFSI quattro舒适型</td>\n",
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" <td>2013年10月</td>\n",
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" <td>4.80万公里</td>\n",
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" <td>欧4</td>\n",
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" <td>44.80</td>\n",
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" <td>101.06万</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>奥迪</td>\n",
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" <td>奥迪A6L 2014款 30 FSI 豪华型</td>\n",
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" <td>2014年9月</td>\n",
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" <td>0.81万公里</td>\n",
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" <td>国4,国5</td>\n",
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" <td>33.19</td>\n",
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" <td>54.99万</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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]
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},
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"execution_count": 82,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 82
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-18T02:17:28.513253Z",
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"start_time": "2025-04-18T02:17:28.491887Z"
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}
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},
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"cell_type": "code",
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"source": [
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"from decimal import Decimal\n",
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"car[\"Km\"] = car[\"Km\"].str.extract(\"(\\d+\\.?\\d+)\",expand = True)\n",
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"car[\"New_price\"] = car[\"New_price\"].str.extract(\"(\\d+\\.?\\d+)\",expand = True)\n",
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"car[\"New_price\"] = car[\"New_price\"].apply(lambda x : Decimal(x) * 10000)\n",
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"# car[\"Sec_price\"] = car[\"Sec_price\"].apply(lambda x : Decimal(str(x)) * 10000)\n",
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"# car[\"Km\"] = car[\"Km\"].apply(lambda x : Decimal(str(x)) * 10000)\n",
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"car.head(5)"
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],
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"id": "1094ed7ec64fd6d3",
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"outputs": [
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{
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"data": {
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||
"text/plain": [
|
||
" Brand Name Boarding_time Km Discharge排放标准 \\\n",
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||
"0 奥迪 奥迪A6L 2006款 2.4 CVT 舒适型 2006年8月 9.00 国3 \n",
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"1 奥迪 奥迪A6L 2007款 2.4 CVT 舒适型 2007年1月 8.00 国4 \n",
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"2 奥迪 奥迪A6L 2004款 2.4L 技术领先型 2005年5月 15.00 国2 \n",
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"3 奥迪 奥迪A8L 2013款 45 TFSI quattro舒适型 2013年10月 4.80 欧4 \n",
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"4 奥迪 奥迪A6L 2014款 30 FSI 豪华型 2014年9月 0.81 国4,国5 \n",
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"\n",
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" Sec_price New_price \n",
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"0 6.90 508900.00 \n",
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"1 8.88 508900.00 \n",
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"2 3.82 542400.00 \n",
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"3 44.80 1010600.00 \n",
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"4 33.19 549900.00 "
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" <th>Name</th>\n",
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" <th>Boarding_time</th>\n",
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" <th>Km</th>\n",
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" <th>Discharge排放标准</th>\n",
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||
" <th>Sec_price</th>\n",
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" <th>New_price</th>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>奥迪</td>\n",
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||
" <td>奥迪A6L 2006款 2.4 CVT 舒适型</td>\n",
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" <td>2006年8月</td>\n",
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" <td>9.00</td>\n",
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||
" <td>国3</td>\n",
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" <td>6.90</td>\n",
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" <td>508900.00</td>\n",
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" </tr>\n",
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" <tr>\n",
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||
" <th>1</th>\n",
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||
" <td>奥迪</td>\n",
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||
" <td>奥迪A6L 2007款 2.4 CVT 舒适型</td>\n",
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||
" <td>2007年1月</td>\n",
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" <td>8.00</td>\n",
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" <td>国4</td>\n",
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" <td>8.88</td>\n",
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" <td>508900.00</td>\n",
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" <tr>\n",
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||
" <th>2</th>\n",
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" <td>奥迪</td>\n",
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||
" <td>奥迪A6L 2004款 2.4L 技术领先型</td>\n",
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||
" <td>2005年5月</td>\n",
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||
" <td>15.00</td>\n",
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||
" <td>国2</td>\n",
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||
" <td>3.82</td>\n",
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||
" <td>542400.00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
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||
" <th>3</th>\n",
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" <td>奥迪</td>\n",
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" <td>奥迪A8L 2013款 45 TFSI quattro舒适型</td>\n",
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" <td>2013年10月</td>\n",
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" <td>4.80</td>\n",
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" <td>欧4</td>\n",
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" <td>44.80</td>\n",
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" <td>1010600.00</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>奥迪</td>\n",
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" <td>奥迪A6L 2014款 30 FSI 豪华型</td>\n",
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" <td>2014年9月</td>\n",
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" <td>0.81</td>\n",
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||
" <td>国4,国5</td>\n",
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" <td>33.19</td>\n",
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" <td>549900.00</td>\n",
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"cell_type": "code",
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"source": [
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"car['Boarding_time'] = pd.to_datetime(car['Boarding_time'].str.replace('年', '-').str.replace('月', ''), errors='coerce', format='%Y-%m')\n",
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"car.head(3)"
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],
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||
"id": "2df80c752148dcd1",
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"outputs": [
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||
{
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||
"data": {
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"text/plain": [
|
||
" Brand Name Boarding_time Km Discharge排放标准 \\\n",
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||
"0 奥迪 奥迪A6L 2006款 2.4 CVT 舒适型 2006-08-01 9.00 国3 \n",
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"1 奥迪 奥迪A6L 2007款 2.4 CVT 舒适型 2007-01-01 8.00 国4 \n",
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"2 奥迪 奥迪A6L 2004款 2.4L 技术领先型 2005-05-01 15.00 国2 \n",
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"\n",
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||
" Sec_price New_price \n",
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"0 6.90 508900.00 \n",
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"1 8.88 508900.00 \n",
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"2 3.82 542400.00 "
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|
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" <th>Brand</th>\n",
|
||
" <th>Name</th>\n",
|
||
" <th>Boarding_time</th>\n",
|
||
" <th>Km</th>\n",
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||
" <th>Discharge排放标准</th>\n",
|
||
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|
||
" <th>New_price</th>\n",
|
||
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|
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|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>奥迪</td>\n",
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||
" <td>奥迪A6L 2006款 2.4 CVT 舒适型</td>\n",
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||
" <td>2006-08-01</td>\n",
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||
" <td>9.00</td>\n",
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||
" <td>国3</td>\n",
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||
" <td>6.90</td>\n",
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||
" <td>508900.00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>奥迪</td>\n",
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||
" <td>奥迪A6L 2007款 2.4 CVT 舒适型</td>\n",
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||
" <td>2007-01-01</td>\n",
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||
" <td>8.00</td>\n",
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||
" <td>国4</td>\n",
|
||
" <td>8.88</td>\n",
|
||
" <td>508900.00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>奥迪</td>\n",
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||
" <td>奥迪A6L 2004款 2.4L 技术领先型</td>\n",
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||
" <td>2005-05-01</td>\n",
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||
" <td>15.00</td>\n",
|
||
" <td>国2</td>\n",
|
||
" <td>3.82</td>\n",
|
||
" <td>542400.00</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
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"</div>"
|
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]
|
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},
|
||
"execution_count": 84,
|
||
"metadata": {},
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||
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}
|
||
},
|
||
"cell_type": "code",
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||
"source": [
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||
"today = pd.Timestamp('today')\n",
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"car['Year'] = today.year - car['Boarding_time'].dt.year\n",
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"car['Month'] = today.month - car['Boarding_time'].dt.month\n",
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"car['Year'] = car['Year'] + car['Month'] / 12"
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],
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||
"id": "adb1e9029cf50440",
|
||
"outputs": [],
|
||
"execution_count": 85
|
||
},
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||
{
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"metadata": {
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"ExecuteTime": {
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|
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"start_time": "2025-04-18T02:17:28.689606Z"
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}
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||
},
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||
"cell_type": "code",
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||
"source": [
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||
"# 1、车辆价格分布情况\n",
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||
"car['Sec_price'].describe()"
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||
],
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||
"id": "192ca8d230bba52c",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"count 11281.000000\n",
|
||
"mean 26.897567\n",
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||
"std 55.451814\n",
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||
"min 0.650000\n",
|
||
"25% 5.200000\n",
|
||
"50% 10.490000\n",
|
||
"75% 24.800000\n",
|
||
"max 808.000000\n",
|
||
"Name: Sec_price, dtype: float64"
|
||
]
|
||
},
|
||
"execution_count": 86,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 86
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:17:28.759802Z",
|
||
"start_time": "2025-04-18T02:17:28.755785Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 2、车辆销量品牌分布\n",
|
||
"car['Brand'].value_counts()"
|
||
],
|
||
"id": "84cd0ac0f5397e98",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"别克 1350\n",
|
||
"大众 991\n",
|
||
"奔驰 895\n",
|
||
"宝马 773\n",
|
||
"奥迪 758\n",
|
||
" ... \n",
|
||
"东风风光 1\n",
|
||
"昌河 1\n",
|
||
"北汽制造 1\n",
|
||
"北京 1\n",
|
||
"中欧房车 1\n",
|
||
"Name: Brand, Length: 104, dtype: int64"
|
||
]
|
||
},
|
||
"execution_count": 87,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 87
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:17:28.829496Z",
|
||
"start_time": "2025-04-18T02:17:28.826138Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 3、排放标准分析\n",
|
||
"car['Discharge排放标准'].value_counts()"
|
||
],
|
||
"id": "abfa9e35e2c0e57b",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"国4 4300\n",
|
||
"欧4 1898\n",
|
||
"欧5 1201\n",
|
||
"国4,国5 848\n",
|
||
"国3 798\n",
|
||
"国5 683\n",
|
||
"欧3 292\n",
|
||
"-- 276\n",
|
||
"国2 241\n",
|
||
"国4,京5 223\n",
|
||
"国3,OBD 119\n",
|
||
"OBD 90\n",
|
||
"国4,OBD 63\n",
|
||
"欧4,OBD 62\n",
|
||
"OBD,国5 38\n",
|
||
"欧6 36\n",
|
||
"国4,OBD,国5 31\n",
|
||
"国5,京5 22\n",
|
||
"欧5,OBD 9\n",
|
||
"欧4,欧5 9\n",
|
||
"欧5,国4 7\n",
|
||
"欧4,国3 7\n",
|
||
"国4,OBD,京5 6\n",
|
||
"欧4,国4 6\n",
|
||
"欧4,国4,OBD 5\n",
|
||
"欧3,欧4 2\n",
|
||
"欧5,国5 2\n",
|
||
"国4,国5,京5 1\n",
|
||
"欧1 1\n",
|
||
"欧2 1\n",
|
||
"京5 1\n",
|
||
"国3,国4 1\n",
|
||
"欧4,-- 1\n",
|
||
"欧5,国4,国5 1\n",
|
||
"Name: Discharge排放标准, dtype: int64"
|
||
]
|
||
},
|
||
"execution_count": 88,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 88
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:17:28.890889Z",
|
||
"start_time": "2025-04-18T02:17:28.886821Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 4、车龄分析\n",
|
||
"car['Year'].describe()"
|
||
],
|
||
"id": "93126f910d7182c6",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"count 11188.000000\n",
|
||
"mean 13.123592\n",
|
||
"std 2.991405\n",
|
||
"min 7.500000\n",
|
||
"25% 10.750000\n",
|
||
"50% 13.166667\n",
|
||
"75% 15.083333\n",
|
||
"max 27.333333\n",
|
||
"Name: Year, dtype: float64"
|
||
]
|
||
},
|
||
"execution_count": 89,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 89
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:17:28.960584Z",
|
||
"start_time": "2025-04-18T02:17:28.955583Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 5、里程分析\n",
|
||
"car['Km'].describe()"
|
||
],
|
||
"id": "9a5d106b4e15e8a2",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"count 11184\n",
|
||
"unique 968\n",
|
||
"top 6.00\n",
|
||
"freq 485\n",
|
||
"Name: Km, dtype: object"
|
||
]
|
||
},
|
||
"execution_count": 90,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 90
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:17:29.031125Z",
|
||
"start_time": "2025-04-18T02:17:29.024995Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 6、折旧价格分析\n",
|
||
"# car = car.dropna(subset=['Km'])\n",
|
||
"car[['Km', 'Sec_price']].corr()"
|
||
],
|
||
"id": "52035886c7842d2f",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
" Sec_price\n",
|
||
"Sec_price 1.0"
|
||
],
|
||
"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>Sec_price</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>Sec_price</th>\n",
|
||
" <td>1.0</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
]
|
||
},
|
||
"execution_count": 91,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 91
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:23:06.001261Z",
|
||
"start_time": "2025-04-18T02:23:05.987085Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 7、不同品牌新车平均价格对比\n",
|
||
"car[['Brand', 'New_price']].groupby('Brand').mean()"
|
||
],
|
||
"id": "568eaf05460ebb68",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
" New_price\n",
|
||
"Brand \n",
|
||
"DS 2.644188e+05\n",
|
||
"GMC 1.423178e+06\n",
|
||
"Jeep 4.342455e+05\n",
|
||
"MINI 3.076827e+05\n",
|
||
"WEY 1.930000e+05\n",
|
||
"... ...\n",
|
||
"雪佛兰 1.564546e+05\n",
|
||
"雪铁龙 1.655019e+05\n",
|
||
"雷克萨斯 7.538173e+05\n",
|
||
"雷诺 2.770526e+05\n",
|
||
"马自达 2.170586e+05\n",
|
||
"\n",
|
||
"[104 rows x 1 columns]"
|
||
],
|
||
"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>New_price</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>Brand</th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>DS</th>\n",
|
||
" <td>2.644188e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>GMC</th>\n",
|
||
" <td>1.423178e+06</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>Jeep</th>\n",
|
||
" <td>4.342455e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>MINI</th>\n",
|
||
" <td>3.076827e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>WEY</th>\n",
|
||
" <td>1.930000e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>雪佛兰</th>\n",
|
||
" <td>1.564546e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>雪铁龙</th>\n",
|
||
" <td>1.655019e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>雷克萨斯</th>\n",
|
||
" <td>7.538173e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>雷诺</th>\n",
|
||
" <td>2.770526e+05</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>马自达</th>\n",
|
||
" <td>2.170586e+05</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>104 rows × 1 columns</p>\n",
|
||
"</div>"
|
||
]
|
||
},
|
||
"execution_count": 96,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 96
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:25:53.211176Z",
|
||
"start_time": "2025-04-18T02:25:53.179478Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 8、排放标准与行驶里程的关系\n",
|
||
"car['Km'] = pd.to_numeric(car['Km'], errors='coerce')\n",
|
||
"car.groupby('Discharge排放标准')['Km'].mean()"
|
||
],
|
||
"id": "4af30a35353b2754",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Discharge排放标准\n",
|
||
"-- 6.302677\n",
|
||
"OBD 8.320222\n",
|
||
"OBD,国5 3.307105\n",
|
||
"京5 2.000000\n",
|
||
"国2 11.470539\n",
|
||
"国3 8.524411\n",
|
||
"国3,OBD 7.691681\n",
|
||
"国3,国4 5.000000\n",
|
||
"国4 7.075801\n",
|
||
"国4,OBD 5.169841\n",
|
||
"国4,OBD,京5 5.533333\n",
|
||
"国4,OBD,国5 4.262258\n",
|
||
"国4,京5 4.808879\n",
|
||
"国4,国5 4.026185\n",
|
||
"国4,国5,京5 3.400000\n",
|
||
"国5 2.302224\n",
|
||
"国5,京5 3.365455\n",
|
||
"欧1 8.000000\n",
|
||
"欧2 12.000000\n",
|
||
"欧3 9.064828\n",
|
||
"欧3,欧4 8.000000\n",
|
||
"欧4 6.729597\n",
|
||
"欧4,-- 7.500000\n",
|
||
"欧4,OBD 5.134426\n",
|
||
"欧4,国3 8.914286\n",
|
||
"欧4,国4 6.133333\n",
|
||
"欧4,国4,OBD 7.460000\n",
|
||
"欧4,欧5 4.120000\n",
|
||
"欧5 3.364559\n",
|
||
"欧5,OBD 4.911111\n",
|
||
"欧5,国4 4.382857\n",
|
||
"欧5,国4,国5 7.000000\n",
|
||
"欧5,国5 0.650000\n",
|
||
"欧6 1.073714\n",
|
||
"Name: Km, dtype: float64"
|
||
]
|
||
},
|
||
"execution_count": 99,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 99
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-04-18T02:26:08.841815Z",
|
||
"start_time": "2025-04-18T02:26:08.835149Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"# 9、车龄与二手车价格的相关性\n",
|
||
"car[['Year', 'Sec_price']].corr()"
|
||
],
|
||
"id": "ab1c177ba107b9bc",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
" Year Sec_price\n",
|
||
"Year 1.00000 -0.30768\n",
|
||
"Sec_price -0.30768 1.00000"
|
||
],
|
||
"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>Year</th>\n",
|
||
" <th>Sec_price</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>Year</th>\n",
|
||
" <td>1.00000</td>\n",
|
||
" <td>-0.30768</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>Sec_price</th>\n",
|
||
" <td>-0.30768</td>\n",
|
||
" <td>1.00000</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
]
|
||
},
|
||
"execution_count": 100,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 100
|
||
}
|
||
],
|
||
"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
|
||
}
|