阿古朵

from pyecharts import options as optsfrom pyecharts.charts import Bar, Grid, Linebar = ( Bar() .add_xaxis(["{}年".format(i) for i in range(2010, 2020)]) .add_yaxis( "中国GDP", [6.09, 7.55, 8.53, 9.57, 10.48, 11.06, 11.23, 12.31,

from pyecharts import options as optsfrom pyecharts.charts import Liquidfrom pyecharts.globals import SymbolTypec = ( Liquid() .add("2019中国在世界占比", [0.16, 0.83], is_outline_show=False, shape=SymbolType.DIAMOND) .set_global_opts(title_opts=op

import pyecharts.options as optsfrom pyecharts.charts import Piex_data = ["中国", "韩国", "印度", "德国", "日本", "其他国家"]y_data = [16.2, 1.8, 3.2, 4.4, 5.7, 44.3]( Pie(init_opts=opts.InitOpts(width="1000px", height="900px")) .add( series_name="

近年来中国及各国GDP变化一．可视化数据来源经各方面搜索，最终选择此数据来源https://www.kylc.com/stats/global/yearly_per_country/g_gdp/chn.html整理后数据如下中国GDP 6.09, 7.55, 8.53, 9.57, 10.48, 11.06, 11.23, 12.31, 13.89, 14.28 美国GDP 14.99, 15.544, 16.2, 16.78, 17.53, 18.22, 18.71, 19.52, 20.58

销售指标完成率

from pyecharts import options as optsfrom pyecharts.charts import Geofrom pyecharts.faker import Fakercity=[("北京",600),("天津",4),("太原",700)]c = ( Geo() .add_schema(maptype="china") .add("",city) .set_series_opts(lable_opts=opts.LabelOpts

第七次全国人口普查各地区人口排行榜

from pyecharts import options as optsfrom pyecharts.charts import Barx=['长治','朔州','运城','晋城','晋中']y1=[8,6,5,25,4]y2=[6,1,3,19,3]y3=[2,5,2,6,1]bar = ( Bar() .add_xaxis(x) .add_yaxis("总人数", y1) .add_yaxis("男生", y2) .add_yaxis("女生", .

import pyecharts.options as optsfrom pyecharts.charts import Linelow = [4000,5000,6000,5500,3000,4500]line = Line()line.add_xaxis(lab)line.add_yaxis("步数",low, markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_='min',name

#普通import pyecharts.options as optsfrom pyecharts.charts import Linelow=[-1,0,-2,0,-1,0,3]height=[12,14,16,16,18,17,18]lab=["周一","周二","周三","周四","周五","周六","周日"]line=Line()#生成line类型图标、line.add_xaxis(lab)#添加x轴line.add_yaxis("低温",low) #添加y轴数据line.ad

预习下节课pyecharts简介

#雷达图#在一个画布中显示几个雷达图import numpy as npimport matplotlib.pyplot as pltplt.rcParams['font.sans-serif']=["SimHei"]def make_spider(order,data,title,color): N=len(categories) angles=np.linspace(0,2*np.pi,N,endpoint=False)#将圆根据标签的个数等比分 angl..

#英雄 一个英雄import matplotlib.pyplot as pltimport numpy as npplt.rcParams["font.sans-serif"] = ["SimHei"]abilities=['kda','输出','生存','团战','发育']theta=np.linspace(0,2*np.pi,len(abilities),endpoint=False)#将图根据标签个数等比划分r=[70,90,60,80,69]plt.polar(theta,r,'r.

#上课案列import matplotlib.pyplot as pltimport numpy as nptheta=[0.25*np.pi,0.75*np.pi,1*np.pi,1.5*np.pi,0.25*np.pi] #第一个点在最后面要再放一个，这样才会形成一个封闭的区域r=[20,40,60,80,20]plt.polar(theta,r,'ro-')#第一个n是180°。所以180°的四分之一是45°，20是极径，ro是颜色和形状,ro后面加‘-’就有线了plt.fill(t.

饼图与条形图比较#直方图import matplotlib.pyplot as pltplt.rcParams["font.sans-serif"] = ["Simhei"]plt.figure()xiaofei = ["吃饭","零食","水果","衣服","化妆品","生活日用品","交通"]num = [170,50,50,200,100,50,50]plt.bar(xiaofei,num)plt.title("一周账单")plt.ylabel("钱")plt.xlabel(

#班级城市分布import matplotlib.pyplot as pltplt.rcParams[“font.sans-serif”]=[“SimHei”] #汉字plt.figure()citys=[“运城”,“临汾”,“忻州”,“吕梁”,“晋中”]num=[1,3,13,19,7]ex=[0,0,0,0.1,0] #距离plt.title(“大数据A1904班同学城市分布”)plt.pie(num,labels=citys,autopct="%.2f%%",explode=ex)p

1.春节电影票房排行榜2.2021年元旦假期全国各省份旅游收入排行榜3.2021年元旦假期全国各省份接待游客数量排行榜#第一题import matplotlib.pyplot as pltplt.rcParams['font.sans-serif']=['SimHei']plt.figure()name = ['你好，李焕英','唐人街探案3','刺杀小说家','熊出没']values = [48.2,43.1,8.9,5.2]plt.bar(name,values)plt.title(

import matplotlib.pyplot as pltplt.rcParams['font.sans-serif']=['SimHei'] #显示中文标签#创建画布plt.figure()#准备数据，绘图data=[50,112,95,151,174,111,150,179,139,161,143,101,176,160,137,138,149,190,180,71,136,97,141,110,132,156,118,121,194,135,144,92,84,55,120,128,1.

#1.导包import matplotlib.pyplot as pltplt.rcParams[‘font.sans-serif’]=[‘SimHei’]#正确展示中文plt.rcParams[‘axes.unicode_minus’]=False#正确显示负号#2.创建画布plt.figure()#3.绘图low = [-1,0,-2,0,-1,0,3]high = [12,14,16,16,18,17,18]plt.plot(low,marker=“s”)#marker设置数据标记