import pandas as pd
from collections import Counter
###画图
from pyecharts import options as opts
from pyecharts.charts import Map
from pyecharts.globals import ThemeType
from pyecharts.charts import Bar, Pie, Timeline
from pyecharts.faker import Faker


datafile = u'七次人口普查数据.xlsx'
data = pd.read_excel(datafile)


###第七次不同省份总人口
def an1():
    name = data['省份'].tolist()[1:]
    value = data['2020年第七次人口普查'].tolist()[1:]
    provinces = [i.replace("\u3000","") for i in name]
    #value = [int(int(i)/10000) for i in value]
    print(provinces)
    print(value)
    c = (
        Map()
            .add("", [list(z) for z in zip(provinces, value)], "china")
            .set_global_opts(
            title_opts=opts.TitleOpts(title="第七次不同省份总人口"),
            visualmap_opts=opts.VisualMapOpts(max_=130000000, split_number=8, is_piecewise=True),
        )
    ).render(path="第七次不同省份总人口.html")

import pandas as pd
from pyecharts.charts import Pie
from pyecharts import options as opts
import os
os.chdir(r"C:\Users\Administrator\Desktop\广东省人口分析")
df = pd.read_excel(r"人口地域分布.xlsx")
df.sort_values(by='人口数', ascending=False, inplace=True)
v = df['地 区'][:15].values.tolist()
d = df['人口数'][:15].values.tolist()
pie1 = Pie(init_opts=opts.InitOpts(width='1350px', height='750px'))

pie1.set_colors(color_series)
# 添加数据，设置饼图的半径，是否展示成南丁格尔图
pie1.add("", [list(z) for z in zip(v, d)],
        radius=["30%", "135%"],
        center=["50%", "65%"],
        rosetype="area"
        )

pie1.set_global_opts(title_opts=opts.TitleOpts(title='玫瑰图示例'),
                     legend_opts=opts.LegendOpts(is_show=False),
                     toolbox_opts=opts.ToolboxOpts())
# 设置系列配置项
pie1.set_series_opts(label_opts=opts.LabelOpts(is_show=True, position="inside", font_size=12,
                                               formatter="{b}:{c}人", font_style="italic",
                                               font_weight="bold", font_family="Microsoft YaHei"
                                               ),
                     )
# 生成html文档
pie1.render('南丁格尔玫瑰图.html')