能绕赤道（4万公里）5圈的车是什么样的？Python爬取懂车帝网站数据，并做数据可视化展示二手车概况

超、凢脫俗 2022-09-12 12:54 4阅读 0赞

# 知识点： #

*  requests 发送网络请求
 *  parsel 解析数据
 *  csv 保存数据

# 第三方库 #

*  requests >>> pip install requests
 *  parsel >>> pip install parsel

# 开发环境： #

*  版 本：anaconda5.2.0（python3.6.5）
 *  编辑器：pycharm

![image][]

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# 爬虫代码 #

### 导入模块 ###

import requests
    import parsel
    import csv

### 发送请求 ###

url = f'https://www.dongchedi.com/usedcar/x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x?sh_city_name=%E5%85%A8%E5%9B%BD&page=1'
    html_data = requests.get(url).text

### 解析数据 筛选数据 ###

selector = parsel.Selector(html_data)
    lis = selector.css('#__next > div:nth-child(2) > div.new-main.new > div > div > div.wrap > ul > li')
    for li in lis:
        title = li.css('dl dt p::text').get()
        info_list = li.css('dl dd')
        info = ''.join(info_list.css('dd:nth-child(2)::text').getall()).split('|')
        car_age = info[0]
        mileage = info[1].replace('万公里', '')
        city = info[2]

### 做一个判断 ###

if len(info_list) == 4:
        dcd_auth = info_list.css('dd span::text').get()
        price = info_list.css('dd:nth-child(4)::text').get()
        original_price = info_list.css('dd:nth-child(5)::text').get()
    else:
        dcd_auth = '无认证'
        price = info_list.css('dd:nth-child(3)::text').get()
        original_price = info_list.css('dd:nth-child(4)::text').get()
    price = price.replace('万', '')
    original_price = original_price.replace('新车含税价: ', '').replace('万', '')
    print(title, car_age, mileage, city, dcd_auth, price, original_price)

### 保存数据 ###

csv_dcd = open('dcd.csv', mode='a', encoding='utf-8', newline='')
    csv_write = csv.writer(csv_dcd)
    csv_write.writerow(['品牌', '车龄', '里程(万公里)', '城市', '认证', '售价(万元)', '原价(万元)'])

![image][image 1]

# 数据可视化 #

### 导入模块 ###

import pandas as pd
    from pyecharts.charts import *
    from pyecharts.commons.utils import JsCode
    from pyecharts import options as opts

### 读取数据 ###

df = pd.read_csv('dcd.csv', encoding = 'utf-8')
    df.head()

### 各省市二手车数量柱状图 ###

bar=(
        Bar(init_opts=opts.InitOpts(height='500px',width='1000px',theme='dark'))
        .add_xaxis(counts.index.tolist())
        .add_yaxis(
            '城市二手车数量',
            counts.values.tolist(),
            label_opts=opts.LabelOpts(is_show=True,position='top'),
            itemstyle_opts=opts.ItemStyleOpts(
                color=JsCode("""new echarts.graphic.LinearGradient( 0, 0, 0, 1,[{offset: 0,color: 'rgb(255,99,71)'}, {offset: 1,color: 'rgb(32,178,170)'}]) """
                )
            )
        )
        .set_global_opts(
            title_opts=opts.TitleOpts(
                title='各个城市二手车数量柱状图'),
                xaxis_opts=opts.AxisOpts(name='书籍名称',
                type_='category',                                           
                axislabel_opts=opts.LabelOpts(rotate=90),
            ),
            yaxis_opts=opts.AxisOpts(
                name='数量',
                min_=0,
                max_=1400.0,
                splitline_opts=opts.SplitLineOpts(is_show=True,linestyle_opts=opts.LineStyleOpts(type_='dash'))
            ),
            tooltip_opts=opts.TooltipOpts(trigger='axis',axis_pointer_type='cross')
        )
    
        .set_series_opts(
            markline_opts=opts.MarkLineOpts(
                data=[
                    opts.MarkLineItem(type_='average',name='均值'),
                    opts.MarkLineItem(type_='max',name='最大值'),
                    opts.MarkLineItem(type_='min',name='最小值'),
                ]
            )
        )
    )
    bar.render_notebook()

![image][image 2]

### 各省市二手车平均价格柱状图 ###

bar=(
        Bar(init_opts=opts.InitOpts(height='500px',width='1000px',theme='dark'))
        .add_xaxis(means.index.tolist())
        .add_yaxis(
            '城市二手车平均价格',
            means.values.tolist(),
            label_opts=opts.LabelOpts(is_show=True,position='top'),
            itemstyle_opts=opts.ItemStyleOpts(
                color=JsCode("""new echarts.graphic.LinearGradient( 0, 0, 0, 1,[{offset: 0,color: 'rgb(255,99,71)'}, {offset: 1,color: 'rgb(32,178,170)'}]) """
                )
            )
        )
        .set_global_opts(
            title_opts=opts.TitleOpts(
                title='各个城市二手车平均价格柱状图'),
                xaxis_opts=opts.AxisOpts(name='城市名称',
                type_='category',                                           
                axislabel_opts=opts.LabelOpts(rotate=90),
            ),
            yaxis_opts=opts.AxisOpts(
                name='平均价格',
                min_=0,
                max_=40.0,
                splitline_opts=opts.SplitLineOpts(is_show=True,linestyle_opts=opts.LineStyleOpts(type_='dash'))
            ),
            tooltip_opts=opts.TooltipOpts(trigger='axis',axis_pointer_type='cross')
        )
    
        .set_series_opts(
            markline_opts=opts.MarkLineOpts(
                data=[
                    opts.MarkLineItem(type_='average',name='均值'),
                    opts.MarkLineItem(type_='max',name='最大值'),
                    opts.MarkLineItem(type_='min',name='最小值'),
                ]
            )
        )
    )
    bar.render_notebook()

![image][image 3]

### 二手车品牌占比情况 ###

pie1 = (
        Pie(init_opts=opts.InitOpts(theme='dark',width='1000px',height='600px'))
        .add('', datas_pair_1, radius=['35%', '60%'])
        .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{d}%"))
        .set_global_opts(
            title_opts=opts.TitleOpts(
                title="懂车帝二手车\n\n数量占比区间", 
                pos_left='center', 
                pos_top='center',
                title_textstyle_opts=opts.TextStyleOpts(
                    color='#F0F8FF',
                    font_size=20,
                    font_weight='bold'
                ),
            )
        )
    )
    pie1.render_notebook()

![image][image 4]

### 二手车里程区间 ###

pie1 = (
        Pie(init_opts=opts.InitOpts(theme='dark',width='1000px',height='600px'))
        .add('', datas_pair_1, radius=['35%', '60%'])
        .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{d}%"))
        .set_global_opts(
            title_opts=opts.TitleOpts(
                title="懂车帝二手车\n\n里程占比区间", 
                pos_left='center', 
                pos_top='center',
                title_textstyle_opts=opts.TextStyleOpts(
                    color='#F0F8FF',
                    font_size=20,
                    font_weight='bold'
                ),
            )
        )
    )
    pie1.render_notebook()

![image][image 5]

# [对于本篇文章有疑问，或者想要数据集的同学也可以点这里][Link 2] #

[image]: /images/20220828/66bb8bc26a624ff399efa9bee6a335b0.png
[Link 1]: https://www.bilibili.com/video/BV1544y1C7g4?share_source=copy_web
[image 1]: /images/20220828/e234fdbec3654a50aac60d15f359b7df.png
[image 2]: /images/20220828/683f15fa8e1a442da64308fc13d67c0c.png
[image 3]: /images/20220828/6f61802604754c608e52ffd7b5f26ca7.png
[image 4]: /images/20220828/b097106790b64f41975230d296cc28a1.png
[image 5]: /images/20220828/75c66df5e6144fab84289c9c66278aab.png
[Link 2]: https://link.csdn.net/?target=https%3A%2F%2Fjq.qq.com%2F%3F_wv%3D1027%26k%3DSuR89RD4