python 数据可视化大屏制作

数据链接：https://pan.baidu.com/s/1waFRKxAvt42kRN9kAfFs4w 
提取码：1234

from pyecharts import options as opts
from pyecharts.globals import ThemeType #导入主题库
from pyecharts.globals import SymbolType #主题库
from pyecharts.charts import Pie,Bar,Map,WordCloud,Page  #玫瑰图，柱状图，地图，词云，组合图
import pandas as pd

df_taobao = pd.read_excel("D:/可视化项目/数据可视化演示/taobao_goods.xlsx") #读取数据
df_taobao

#删除重复值
df_taobao.drop_duplicates(inplace=True)  

#提取省份
ld_list = []
for ld in df_taobao["location"]:
    ld_list.append(ld.split(" ")[0])  #使用分割提取
    
#原数据表中替换省份    
df_taobao["location"] = ld_list
df_taobao

#销售数据格式转换
sales_list = []
for sale in df_taobao["sales"]:
    sale = sale[:-3].replace("+","")  #去掉“人付款”三字
    if "万" in sale:
        sale = int(float(sale[:-1])*10000) #将万转换为元
    print(sale)
    sales_list.append(sale)
df_taobao["sales"] = sales_list

locations = [location for location in df_taobao["location"].value_counts().items()]  #提取省份和数量使用items组成元组
locations

#地图
map = (
Map()
    .add("店铺数量",[list(location) for location in locations],"china")  #显示店铺数量，使用china地图
    .set_global_opts(
        title_opts = opts.TitleOpts(title = "地址分布图"), #设置标题
         visualmap_opts = opts.VisualMapOpts(max_ = 3000),  #设置阈值
        
    )
)
map.render() #保存为html
map.render_notebook()  #在notebook中显示图像

#用户评论词云
from wordcloud import WordCloud
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import jieba 
df_commments = pd.read_excel("D:/可视化项目/数据可视化演示/goods_comments.xlsx")
df_commments

text = "".join(jieba.lcut(str([i for i in df_commments["comment"]])))  #将所有评论组合成一个text

mask =np.array( Image.open("D:/可视化项目/数据可视化演示/bra.jpg"))  #词云背景图片
wc = WordCloud(mask=mask,font_path='C:/Windows/Fonts/simsun.ttc',mode="RGBA").generate(text) #设置格式
plt.imshow(wc,interpolation="bilinear") #显示词云
wc.to_file("词.png")  #保存

from pyecharts.faker import Faker  #假数据库
bar = (
    Bar()
    .add_xaxis(Faker.days_attrs)
    .add_yaxis("商家A",Faker.days_values)
    .add_yaxis("商家B",Faker.days_values)
    .add_yaxis("商家C",Faker.days_values)
    .set_global_opts(
        title_opts=opts.TitleOpts(title = "柱状图"),
        datazoom_opts = [opts.DataZoomOpts()] #设置动态图
    )
)
bar.render_notebook()

from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Faker

v = Faker.choose()
pie =(
    Pie()
    .add(
    "",
    [list(z) for z in zip(v,list(range(10,1000,10)))],
    radius = ["30%","75%"],    #图像中心园的大小
#     center=["75%","50%"],   显示在图像的区域
        
    rosetype = "radius",
    label_opts=opts.LabelOpts(is_show=False),
    )
    .set_global_opts(title_opts=opts.TitleOpts(title="玫瑰实列"))
)
pie.render_notebook()

from pyecharts import options as opts
from pyecharts.charts import Liquid
liquid = (
    Liquid()
    .add("lq",[0.45,0.45])
    #第一个值显示数值，第二个是水位高度
    .set_global_opts(title_opts = opts.TitleOpts(title = "湿度"))
)
liquid.render_notebook()

page = Page(layout=Page.DraggablePageLayout)
page.add(
bar,
liquid,
pie,
map,
)  #将写的单个图片全导入
page.render_notebook()
page.render() #保存组合图
Page.save_resize_html("render.html",cfg_file="chart_config (1).json") #保存组合图为json格式

注：图位置调整以及保存，切记点击save_config保存网页，然后路径会出现chart_config (1).json文件