python实时数据可视化,html 数据可视化

实验目的：了解ECharts和pyECharts的数据可视化特点，掌握ECharts和pyECharts简单操作即可使用ECharts和pyECharts实现数据可视化操作的实验内容：掌握pyECharts的设置和使用方法，掌握pyECharts

(1)打开Windows命令窗口，运行pip install pyecharts命令安装pyecharts库

)2)运行“pip list”命令查看安装结果

)3)使用pyecharts制作条形图

frompyecharts.chartsimportbarv1=[ 70，85，95，64 ] str1=[ '数学'，'物理'，'化学'，'英语' ]bar1=bar(bar )1.add

(1)绘制条形图

frompyecharts.chartsimportbarfrompyechartsimportoptionsasoptsv1=[ 70，85，95，64 ] v2=[ 80，75，85，70 ] str1=[

)2)绘制仪表板图

frompyechartsimportoptionsasoptsfrompyecharts.chartsimportgaugec=(gauge ().add )、()、(完成率)、66.6 ) ).set _

(3)创建三维图

importpyecharts.optionsasoptsfrompyecharts.chartsimportbar 3d hours=[ ' 12a '、' 1a '、' 2a '、' 3a '、' 4a '和' 5a ] ' 11p '，]days=['says] 'Monday '，' Sunday ' ' data=[ 0，0，5 ]，[ 0，1，1 ]，[ 0，2，0 ]，[ 0，3，0 ] 23，5 ]，[ 1，0，7 ]，[ 1，1，0 ]，[ 1，2，0 ]，[ 1，3，0 ]，[ 1，4，0 ]，[ 1，5，0 ]，[ 1，6，0 ]，[ 1 2 )、[ 1，13，6 ]、[ 1，14，9 ]、[ 1，15，11 ]、[ 1，16，6 ]、[ 1，17，7 ]、[ 1，18，8 ]、[ 1，19，12 ]、

], [2, 4, 0], [2, 5, 0], [2, 6, 0], [2, 7, 0], [2, 8, 0], [2, 9, 0], [2, 10, 3], [2, 11, 2], [2, 12, 1], [2, 13, 9], [2, 14, 8], [2, 15, 10], [2, 16, 6], [2, 17, 5], [2, 18, 5], [2, 19, 5], [2, 20, 7], [2, 21, 4], [2, 22, 2], [2, 23, 4], [3, 0, 7], [3, 1, 3], [3, 2, 0], [3, 3, 0], [3, 4, 0], [3, 5, 0], [3, 6, 0], [3, 7, 0], [3, 8, 1], [3, 9, 0], [3, 10, 5], [3, 11, 4], [3, 12, 7], [3, 13, 14], [3, 14, 13], [3, 15, 12], [3, 16, 9], [3, 17, 5], [3, 18, 5], [3, 19, 10], [3, 20, 6], [3, 21, 4], [3, 22, 4], [3, 23, 1], [4, 0, 1], [4, 1, 3], [4, 2, 0], [4, 3, 0], [4, 4, 0], [4, 5, 1], [4, 6, 0], [4, 7, 0], [4, 8, 0], [4, 9, 2], [4, 10, 4], [4, 11, 4], [4, 12, 2], [4, 13, 4], [4, 14, 4], [4, 15, 14], [4, 16, 12], [4, 17, 1], [4, 18, 8], [4, 19, 5], [4, 20, 3], [4, 21, 7], [4, 22, 3], [4, 23, 0], [5, 0, 2], [5, 1, 1], [5, 2, 0], [5, 3, 3], [5, 4, 0], [5, 5, 0], [5, 6, 0], [5, 7, 0], [5, 8, 2], [5, 9, 0], [5, 10, 4], [5, 11, 1], [5, 12, 5], [5, 13, 10], [5, 14, 5], [5, 15, 7], [5, 16, 11], [5, 17, 6], [5, 18, 0], [5, 19, 5], [5, 20, 3], [5, 21, 4], [5, 22, 2], [5, 23, 0], [6, 0, 1], [6, 1, 0], [6, 2, 0], [6, 3, 0], [6, 4, 0], [6, 5, 0], [6, 6, 0], [6, 7, 0], [6, 8, 0], [6, 9, 0], [6, 10, 1], [6, 11, 0], [6, 12, 2], [6, 13, 1], [6, 14, 3], [6, 15, 4], [6, 16, 0], [6, 17, 0], [6, 18, 0], [6, 19, 0], [6, 20, 1], [6, 21, 2], [6, 22, 2], [6, 23, 6],]data = [[d[1], d[0], d[2]] for d in data]( Bar3D(init_opts=opts.InitOpts(width="1600px", height="800px")) .add( series_name="", data=data, xaxis3d_opts=opts.Axis3DOpts(type_="category", data=hours), yaxis3d_opts=opts.Axis3DOpts(type_="category", data=days), zaxis3d_opts=opts.Axis3DOpts(type_="value"), ) .set_global_opts( visualmap_opts=opts.VisualMapOpts( max_=20, range_color=[ "#313695", "#4575b4", "#74add1", "#abd9e9", "#e0f3f8", "#ffffbf", "#fee090", "#fdae61", "#f46d43", "#d73027", "#a50026", ], ) ) .render("bar3d_punch_card.html"))

（4）绘制雷达图

import pyecharts.options as optsfrom pyecharts.charts import Radarv1 = [[4300, 10000, 28000, 35000, 50000, 19000]]v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]( Radar(init_opts=opts.InitOpts(width="1280px", height="720px", bg_color="#CCCCCC")) .add_schema( schema=[ opts.RadarIndicatorItem(name="销售（sales）", max_=6500), opts.RadarIndicatorItem(name="管理（Administration）", max_=16000), opts.RadarIndicatorItem(name="信息技术（Information Technology）", max_=30000), opts.RadarIndicatorItem(name="客服（Customer Support）", max_=38000), opts.RadarIndicatorItem(name="研发（Development）", max_=52000), opts.RadarIndicatorItem(name="市场（Marketing）", max_=25000), ], splitarea_opt=opts.SplitAreaOpts( is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1) ), textstyle_opts=opts.TextStyleOpts(color="#fff"), ) .add( series_name="预算分配（Allocated Budget）", data=v1, linestyle_opts=opts.LineStyleOpts(color="#CD0000"), ) .add( series_name="实际开销（Actual Spending）", data=v2, linestyle_opts=opts.LineStyleOpts(color="#5CACEE"), ) .set_series_opts(label_opts=opts.LabelOpts(is_show=False)) .set_global_opts( title_opts=opts.TitleOpts(title="基础雷达图"), legend_opts=opts.LegendOpts() ) .render("basic_radar_chart.html"))

（5）绘制面积图

import pyecharts.options as optsfrom pyecharts.charts import Linefrom pyecharts.和谐的饼干 import xxdxhc = ( Line() .add_xaxis(xxdxh.choose()) .add_yaxis("商家A", xxdxh.values(), is_smooth=True) .add_yaxis("商家B", xxdxh.values(), is_smooth=True) .set_series_opts( areastyle_opts=opts.AreaStyleOpts(opacity=0.5), label_opts=opts.LabelOpts(is_show=False), ) .set_global_opts( title_opts=opts.TitleOpts(title="Line-面积图（紧贴 Y 轴）"), xaxis_opts=opts.AxisOpts( axistick_opts=opts.AxisTickOpts(is_align_with_label=True), is_scale=False, boundary_gap=False, ), ) .render("line_areastyle_boundary_gap.html"))

实验总结自己写写就行了，本实验仅供参考。