《Python數據可視化之Matplotlib與Pyecharts》之玫瑰圖

11.9.2  不同職業羣體的購買力分析

爲了分析該企業不同職業羣體的購買力情況，繪製了不同羣體的銷售額的玫瑰圖，Python代碼如下：

# -*- coding: utf-8 -*-

 

#聲明Notebook類型，必須在引入pyecharts.charts等模塊前聲明

from pyecharts.globals import CurrentConfig, NotebookType

CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB

 

from pyecharts import options as opts

from pyecharts.charts import Page, Pie

from impala.dbapi import connect

 

#連接Hadoop數據庫

v1 = []

v2 = []

conn = connect(host='192.168.1.7', port=10000, database='sales',auth_mechanism='NOSASL',user='root')

cursor = conn.cursor()

 

#讀取Hadoop表數據

sql_num = "SELECT occupation,ROUND(SUM(sales/10000),2) FROM customers,orders WHERE customers.cust_id=orders.cust_id and dt=2019 GROUP BY occupation"

cursor.execute(sql_num)

sh = cursor.fetchall()

for s in sh:

    v1.append(s[0])

    v2.append(s[1])

 

#畫玫瑰圖

def rosetype() -> Pie:

    c = (

        Pie()

        .add(

            "",

            [list(z) for z in zip(v1, v2)],

            radius=["30%", "75%"],

            center=["50%", "55%"],

            rosetype="radius",

            label_opts=opts.LabelOpts(is_show=False),

        )

        .set_colors(["blue", "green", "purple", "red", "silver"])      #設置顏色 

        .set_global_opts(title_opts=opts.TitleOpts(title="2019年不同職業羣體的購買力分析", subtitle="2019年銷售經營狀況分析"),

                        legend_opts=opts.LegendOpts(orient="horizontal", pos_top="5%", pos_left="30%"),

                        toolbox_opts=opts.ToolboxOpts())

        .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))

    )

    return c

 

#第一次渲染時候調用load_javasrcript文件

rosetype().load_javascript()

#展示數據可視化圖表

rosetype().render_notebook()

在Jupyter lab中運行上述代碼，生成如圖11-9所示的玫瑰圖。

                                                                                           圖11-9  玫瑰圖