Python做数据分析（一）分析社区超市运营数据，自动更新促销时间

import pandas as pd
data=pd.read_csv('超市运营数据.csv',encoding='gbk',parse_dates=["成交时间"])
data

data_group=data.groupby("类别ID")["销量"].sum().reset_index()
data_group

data_group=data_group.sort_values(by="销量",ascending=False).head(10)
data_group

data_group=data.groupby("商品ID")["销量"].sum().reset_index().sort_values(by="销量",ascending=False).head(10)
data_group

data['销售额']=data['销量']*data['单价']
data

data_group=data.groupby('门店编号')['销售额'].sum().reset_index()
data_group

from pyecharts import options as opts
from pyecharts.charts import Pie
x=list(data_group['门店编号'])
y=list(data_group['销售额'])
pie = (
    Pie()
   .add(
        "",
        [(i,j)for i,j in zip(x,y)],
        radius=["30%", "75%"],
        center=["50%", "50%"],
        rosetype="radius",
        label_opts=opts.LabelOpts(is_show=False),
    )
    .set_global_opts(title_opts=opts.TitleOpts(title="门店销售额占比"))
    .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {d}"))
)
pie.render_notebook()

data['小时']=data['成交时间'].map(lambda x:int(x.strftime("%H")))
data

traffic=data[['小时','订单ID']].drop_duplicates()
traffic

traffic_count=traffic.groupby("小时")["订单ID"].count()
traffic_count

小时
6      10
7      37
8     106
9     156
10    143
11     63
13     30
14     36
15     17
16     50
17     73
18     71
19     71
20     39
21     16
Name: 订单ID, dtype: int64

import pyecharts.options as opts
from pyecharts.charts import Line
x=[str(i) for i in list(range(6,22))]
y=list(traffic_count)
line=(
    Line()
    .add_xaxis(xaxis_data=x)
    .add_yaxis(series_name="销量",y_axis=y, is_smooth=True)
    .set_global_opts(
        title_opts=opts.TitleOpts(title="不同时段销量折线图"),
        yaxis_opts=opts.AxisOpts(
                axistick_opts=opts.AxisTickOpts(is_show=True),
                splitline_opts=opts.SplitLineOpts(is_show=True),
            ),)
)
line.render_notebook()