Python数据分析+可视化项目教学：分析猛男童年的玩具，并可视化展示商品数据

矫情吗；* 2022-09-04 02:56 187阅读 0赞

# 前言 #

你相信光吗（那年要不是我拿着手电筒照着电视机，迪迦奥特曼早就被打到了）

来自京东平台上的数据，万代奥特曼与万代高达以及乐高三大类型玩具的数据对比分析，消费者更爱哪一类？

那么，今天我们来分析一下，猛男的童年回忆：**高达、乐高、奥特曼**

## [Python从零基础入门到实战系统教程、源码、视频，想要数据集的同学也可以点这里][Python] ##

##### 采集数据部分我就不再讲了，想了解的可以看[《京东电商平台商品数据爬取》][Link 1]，这次的数据也是在京东平台上的数据 #####

# 开始代码部分 #

一次性导入所需要的全部第三方库

import pandas as pd 
    import pyecharts.options as opts
    from pyecharts.charts import *
    from pyecharts.globals import ThemeType#设定主题
    from pyecharts.commons.utils import JsCode

### 1. 读取数据，而这些数据，一般都是我们爬取到的商品数据，或者公司内的数据库里面的数据 ###

df1 = pd.read_csv(r'京东-乐高.csv', engine='python', encoding='utf-8-sig')
    df2 = pd.read_csv(r'6K高达.csv', engine='python', encoding='utf-8-sig')
    df3 = pd.read_csv(r'6K奥特曼.csv', engine='python', encoding='utf-8-sig')

查看下数据

df1.head(1)

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L20wXzQ4NDA1Nzgx_size_16_color_FFFFFF_t_70][]

### 2. 数据处理 ###

把表格统计到一起

df_all = pd.concat([df1,df2,df3])
    df_all.info()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L20wXzQ4NDA1Nzgx_size_16_color_FFFFFF_t_70 1][]

除去重复值

df_all.drop_duplicates(inplace=True)

删除不必要的列

df_all = df_all.drop(['商品SKU','商品链接','封面图链接','评论链接','店铺链接','页码','当前时间','页面网址'],axis=1)
    df_all.head(1)

筛选剔除广告

df_all = df_all[df_all['是否广告'] == '否']

重置索引

df_all = df_all.reset_index(drop=True)
    df_all.info()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L20wXzQ4NDA1Nzgx_size_16_color_FFFFFF_t_70 2][]

### 3. 处理完数据以后，我们就可以做可视化图表了 ###

##### 绘制商家上线的商品数目Top20柱状图 #####

bar1 = (
        Bar(init_opts=opts.InitOpts(theme='dark', width='1000px',height ='500px'))
        .add_xaxis(shopname.index.tolist())
        .add_yaxis("",shopname.values.tolist())
        .set_series_opts(
            label_opts=opts.LabelOpts(
                    is_show=True, 
                    position='insideRight',
                    font_style='italic'
                ),
            itemstyle_opts=opts.ItemStyleOpts(
                color=JsCode(
                    """new echarts.graphic.LinearGradient(1, 0, 0, 0, [{offset: 0,color: 'rgb(255,99,71)'}, {offset: 1,color: 'rgb(32,178,170)'}])"""
                )
            )
        )
        .set_global_opts(
            title_opts=opts.TitleOpts(title="商家上线的商品数目Top20"),
            xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45)),
            legend_opts=opts.LegendOpts(is_show=True))
        .reversal_axis()
    )
    bar1.render_notebook()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L20wXzQ4NDA1Nzgx_size_16_color_FFFFFF_t_70 3][]

##### 总体价格区间 #####

pie1 = (
        Pie(init_opts=opts.InitOpts(theme='dark',width='1000px',height='600px'))
        
        .add('', datas_pair, radius=['35%', '60%'])
        .set_global_opts(
            title_opts=opts.TitleOpts(title='不同价格区间的销售额整体表现'), 
            legend_opts=opts.LegendOpts(orient='vertical', pos_top='15%', pos_left='2%')
        )
        .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{d}%"))
        .set_global_opts(
            title_opts=opts.TitleOpts(
                title="乐高、奥特曼、高达\n\n价格区间", 
                pos_left='center', 
                pos_top='center',
                title_textstyle_opts=opts.TextStyleOpts(
                    color='#F0F8FF', 
                    font_size=20, 
                    font_weight='bold'
                ),
            )
        )
        .set_colors(['#EF9050', '#3B7BA9', '#6FB27C', '#FFAF34', '#D8BFD8', '#00BFFF', '#7FFFAA'])
    )
    pie1.render_notebook()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L20wXzQ4NDA1Nzgx_size_16_color_FFFFFF_t_70 4][]

##### 单价最高的商品Top20 #####

bar=(
        Bar(init_opts=opts.InitOpts(height='500px',width='1000px',theme='dark'))
        .add_xaxis(price_top.index.tolist())
        .add_yaxis(
            '单价最高的商品',
            price_top.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='单价最高的商品详细柱状图'),
                xaxis_opts=opts.AxisOpts(name='玩具名称',
                type_='category',                                           
                axislabel_opts=opts.LabelOpts(rotate=90),
            ),
            yaxis_opts=opts.AxisOpts(
                name='单价/元',
                min_=0,
                max_=39980.0,
                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()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L20wXzQ4NDA1Nzgx_size_16_color_FFFFFF_t_70 5][]

[Python]: https://jq.qq.com/?_wv=1027&k=lkuXNAJH
[Link 1]: https://www.bilibili.com/video/BV1NU4y1H7wX/
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[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L20wXzQ4NDA1Nzgx_size_16_color_FFFFFF_t_70 1]: /images/20220829/62847e641d694139901dccdbad819907.png
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