【数据可视化】使用pyecharts绘制南丁格尔玫瑰图和水平堆叠条形图

南丁格尔玫瑰图

from pyecharts.charts import Piefrom pyecharts import options as optsimport random# 随机颜色生成# def randomcolor(kind):#colors = []#for i in range(kind):# colArr = ['1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'D', 'E', 'F']# color = ""# for i in range(6):# color += colArr[random.randint(0, 14)]# colors.append("#" + color)#return colors# 数据#provinces = ['西藏', '青海', '贵州', '江苏']#num = [51, 44, 33, 31]#color_series = randomcolor(len(provinces))levels = ['数据层 3049', '应用层 846', '传输层 642', '感知层 209']num = [64.7, 17.9, 13.5, 4.4]color_series = ['FF8785', '6CDADA', 'FF99FF', '7EAEF1']#color_series = ['FF99FF', '7EAEF1', 'FF8785', '6CDADA']# 创建饼图fig = Pie(init_opts=opts.InitOpts(width='800px', height='800px'))# 添加数据fig.add("", [list(z) for z in zip(levels, num)],radius=['35%', '80%'], center=['45%', '55%'], # radius和center需要根据len（levels）调节rosetype='area')# 设置全局配置fig.set_global_opts(title_opts=opts.TitleOpts(title=''),legend_opts=opts.LegendOpts(is_show=False))# 设置系列配置和颜色fig.set_series_opts(label_opts=opts.LabelOpts(is_show=True, position='inside', font_size=23,formatter='{b}\n{c}%', font_style='normal', font_weight='bold',font_family='Microsoft YaHei')) # b:province;c:numfig.set_colors(color_series)# 在网页生成照片fig.render('chart1.html')

效果：

水平堆叠条形图

# 大类与层次# 柱状堆叠图import pyecharts.options as optsfrom pyecharts.charts import Barimport randomgoods = ['物联网服务业', '物联网制造业']chuan = [600, 46]shu = [3007, 46]ying = [846]gan = ["", 209]bar = (Bar().add_xaxis(goods).add_yaxis('传输层', chuan, stack='stack1', color='FF8785').add_yaxis('数据层', shu, stack='stack1', color='6CDADA').add_yaxis('感知层', ying, stack='stack1', color='FF99FF').add_yaxis('应用层', gan, stack='stack1', color='7EAEF1').reversal_axis().set_series_opts(label_opts=opts.LabelOpts(is_show=True, position="insideRight", font_size=12,font_style='normal', font_weight='bold',font_family='Microsoft YaHei')).set_global_opts(title_opts=opts.TitleOpts(title=''),xaxis_opts=opts.AxisOpts(name='企业数量'),yaxis_opts=opts.AxisOpts(name='物联网大类')))bar.render('chart2.html')

效果：