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)
2. 数据处理
把表格统计到一起
df_all = pd.concat([df1,df2,df3]) df_all.info()

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()

3. 处理完数据以后,我们就可以做可视化图表了

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()



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()



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()



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