利用Python进行数据可视化的实例代码利用Python进行数据可视化的实

前言
首先搭建环境
实例代码

例子1：
例子2：
例子3:
例子4:
例子5:
例子6:

总结

前言前面写过一篇用Python制作PPT的博客，感兴趣的可以参考
用Python制作PPT
这篇是关于用Python进行数据可视化的，准备作为一个长贴，随时更新有价值的Python可视化用例,都是网上搜集来的，与君共享,本文所有测试均基于Python3.

首先搭建环境

$pip install pyecharts -U$pip install echarts-themes-pypkg$pip install snapshot_selenium$pip install echarts-countries-pypkg$pip install echarts-cities-pypkg$pip install echarts-china-provinces-pypkg$pip install echarts-china-cities-pypkg$pip install echarts-china-counties-pypkg$pip install echarts-china-misc-pypkg$pip install echarts-united-kingdom-pypkg$pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pyecharts$git clone https://github.com/pyecharts/pyecharts.git$cd pyecharts/$pip install -r requirements.txt$python setup.py install

一顿操作下来，该装的不该装的都装上了，多装一些包没坏处，说不定哪天就用上了呢

实例代码
例子1：

from pyecharts.charts import Barfrom pyecharts import options as opts bar = (Bar().add_xaxis(["chenshan", "maoyi", "longdai", "kuzi", "fengyi", "gaogenxie", "wazi"]).add_yaxis("storeA", [114, 55, 27, 101, 125, 27, 105]).add_yaxis("storeB", [57, 134, 137, 129, 145, 60, 49]).set_global_opts(title_opts=opts.TitleOpts(title="sales")))#bar.render_notebook()bar.render()

render():默认将会在根目录下生成一个 render.html 的文件，支持 path 参数，设置文件保存位置，如 render("./xx/xxx.html").
结果是以网页的形式输出的，执行后，在当前目录下生成render.html，用浏览器打开,最好事先安装chrome浏览器.

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例子2：

from pyecharts import options as optsfrom pyecharts.charts import Piefrom pyecharts.faker import Faker pie = (Pie().add("", [list(z) for z in zip(Faker.choose(), Faker.values())]).set_colors(["blue", "green", "yellow", "red", "pink", "orange", "purple"]).set_global_opts(title_opts=opts.TitleOpts(title="Pie-设置颜色")).set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))) pie.render()

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例子3:

import pyecharts.options as optsfrom pyecharts.charts import Linefrom pyecharts.faker import Faker c = (Line().add_xaxis(Faker.choose()).add_yaxis("storeA", Faker.values(), is_smooth=True).add_yaxis("storeB", Faker.values(), is_smooth=True).set_global_opts(title_opts=opts.TitleOpts(title="Line-smooth")))c.render()

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例子4:

from pyecharts import options as optsfrom pyecharts.charts import Kline data = https://www.it610.com/article/[[2320.26, 2320.26, 2287.3, 2362.94],[2300, 2291.3, 2288.26, 2308.38],[2295.35, 2346.5, 2295.35, 2345.92],[2347.22, 2358.98, 2337.35, 2363.8],[2360.75, 2382.48, 2347.89, 2383.76],[2383.43, 2385.42, 2371.23, 2391.82],[2377.41, 2419.02, 2369.57, 2421.15],[2425.92, 2428.15, 2417.58, 2440.38],[2411, 2433.13, 2403.3, 2437.42],[2432.68, 2334.48, 2427.7, 2441.73],[2430.69, 2418.53, 2394.22, 2433.89],[2416.62, 2432.4, 2414.4, 2443.03],[2441.91, 2421.56, 2418.43, 2444.8],[2420.26, 2382.91, 2373.53, 2427.07],[2383.49, 2397.18, 2370.61, 2397.94],[2378.82, 2325.95, 2309.17, 2378.82],[2322.94, 2314.16, 2308.76, 2330.88],[2320.62, 2325.82, 2315.01, 2338.78],[2313.74, 2293.34, 2289.89, 2340.71],[2297.77, 2313.22, 2292.03, 2324.63],[2322.32, 2365.59, 2308.92, 2366.16],[2364.54, 2359.51, 2330.86, 2369.65],[2332.08, 2273.4, 2259.25, 2333.54],[2274.81, 2326.31, 2270.1, 2328.14],[2333.61, 2347.18, 2321.6, 2351.44],[2340.44, 2324.29, 2304.27, 2352.02],[2326.42, 2318.61, 2314.59, 2333.67],[2314.68, 2310.59, 2296.58, 2320.96],[2309.16, 2286.6, 2264.83, 2333.29],[2282.17, 2263.97, 2253.25, 2286.33],[2255.77, 2270.28, 2253.31, 2276.22],] k = (Kline().add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)]).add_yaxis("k-line", data).set_global_opts(yaxis_opts=opts.AxisOpts(is_scale=True),xaxis_opts=opts.AxisOpts(is_scale=True),title_opts=opts.TitleOpts(title="Kline-examples"),) )k.render()

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例子5:

from pyecharts import options as optsfrom pyecharts.charts import Gauge g = (Gauge().add("", [("complete", 66.6)]).set_global_opts(title_opts=opts.TitleOpts(title="Gauge-basic examples"))) g.render()

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例子6:

from pyecharts import options as optsfrom pyecharts.charts import Bar (Bar().add_xaxis(["名字很长的X轴标签1","名字很长的X轴标签2","名字很长的X轴标签3","名字很长的X轴标签4","名字很长的X轴标签5","名字很长的X轴标签6",]).add_yaxis("商家A", [10, 20, 30, 40, 50, 40]).add_yaxis("商家B", [20, 10, 40, 30, 40, 50]).set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),title_opts=opts.TitleOpts(title="Bar-旋转X轴标签", subtitle="解决标签名字过长的问题"),).render())

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from pyecharts import options as optsfrom pyecharts.faker import Fakerfrom pyecharts.charts import Page, Piel1 = ['aa','bb','cc','dd','ee']num =[10,20,15,25,30]c = (Pie().add("",[list(z) for z in zip(l1, num)],radius=["40%", "75%"],# 圆环的粗细和大小).set_global_opts(title_opts=opts.TitleOpts(title="Pie-Radius"),legend_opts=opts.LegendOpts(orient="vertical", pos_top="5%", pos_left="2%"# 左面比例尺),).set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")))c.render()

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from pyecharts.faker import Fakerfrom pyecharts import options as optsfrom pyecharts.charts import Page, Piel1 = ['aa','bb','cc','dd','ee']num =[10,20,15,25,30]c = (Pie().add("",[list(z) for z in zip(l1, num)],radius=["40%", "55%"],label_opts=opts.LabelOpts(position="outside",formatter="{a|{a}}{abg|} {hr|} {b|{b}: }{c}{per|{d}%}",background_color="#eee",border_color="#aaa",border_width=1,border_radius=4,rich={"a": {"color": "#999", "lineHeight": 22, "align": "center"},"abg": {"backgroundColor": "#e3e3e3","width": "100%","align": "right","height": 22,"borderRadius": [4, 4, 0, 0],},"hr": {"borderColor": "#aaa","width": "100%","borderWidth": 0.5,"height": 0,},"b": {"fontSize": 16, "lineHeight": 33},"per": {"color": "#eee","backgroundColor": "#334455","padding": [2, 4],"borderRadius": 2,},},),).set_global_opts(title_opts=opts.TitleOpts(title="Pie-富文本示例")))c.render()

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from pyecharts import options as optsfrom pyecharts.charts import Line, Bar, Gridbar = (Bar().add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"]).add_yaxis("商家A", [114, 55, 27, 101, 125, 27, 105]).add_yaxis("商家B", [57, 134, 137, 129, 145, 60, 49]).set_global_opts(title_opts=opts.TitleOpts(title="运维之路"),))week_name_list = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]high_temperature = [11, 11, 15, 13, 12, 13, 10]low_temperature = [1, -2, 2, 5, 3, 2, 0]line2 = (Line(init_opts=opts.InitOpts(width="1600px", height="800px")).add_xaxis(xaxis_data=https://www.it610.com/article/week_name_list).add_yaxis(series_name="最高气温",y_axis=high_temperature,markpoint_opts=opts.MarkPointOpts(data=https://www.it610.com/article/[opts.MarkPointItem(type_="max", name="最大值"),opts.MarkPointItem(type_="min", name="最小值"),]),markline_opts=opts.MarkLineOpts(data=https://www.it610.com/article/[opts.MarkLineItem(type_="average", name="平均值")]),).add_yaxis(series_name="最低气温",y_axis=low_temperature,markpoint_opts=opts.MarkPointOpts(data=https://www.it610.com/article/[opts.MarkPointItem(value=-2, name="周最低", x=1, y=-1.5)]),markline_opts=opts.MarkLineOpts(data=https://www.it610.com/article/[opts.MarkLineItem(type_="average", name="平均值"),opts.MarkLineItem(symbol="none", x="90%", y="max"),opts.MarkLineItem(symbol="circle", type_="max", name="最高点"),]),).set_global_opts(#title_opts=opts.TitleOpts(title="气温变化", subtitle="纯属虚构"),tooltip_opts=opts.TooltipOpts(trigger="axis"),toolbox_opts=opts.ToolboxOpts(is_show=True),xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=False),#legend_opts=opts.LegendOpts(pos_left="right"),)#.render("temperature_change_line_chart.html"))# 最后的 Grid#grid_chart = Grid(init_opts=opts.InitOpts(width="1400px", height="800px"))grid_chart = Grid()grid_chart.add(bar,grid_opts=opts.GridOpts(pos_left="3%", pos_right="1%", height="20%"),)# wrgrid_chart.add(line2,grid_opts=opts.GridOpts(pos_left="3%", pos_right="1%", pos_top="40%", height="35%"),)#grid_chart.render("professional_kline_chart.html")grid_chart.render()

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from pyecharts import options as optsfrom pyecharts.charts import Radarv1=[[83, 92, 87, 49, 89, 86]]# 数据必须为二维数组，否则会集中一个指示器显示v2=[[88, 95, 66, 43, 86, 96]]v3=[[80, 92, 87, 58, 78, 81]]radar1=(Radar().add_schema(# 添加schema架构schema=[opts.RadarIndicatorItem(name='传球',max_=100),# 设置指示器名称和最大值opts.RadarIndicatorItem(name='射门',max_=100),opts.RadarIndicatorItem(name='身体',max_=100),opts.RadarIndicatorItem(name='防守',max_=100),opts.RadarIndicatorItem(name='速度',max_=100),opts.RadarIndicatorItem(name='盘带',max_=100),]).add('罗纳尔多',v1,color="#f9713c") # 添加一条数据，参数1为数据名，参数2为数据，参数3为颜色.add('梅西',v2,color="#4169E1") .add('苏亚雷斯',v3,color="#00BFFF") .set_global_opts(title_opts=opts.TitleOpts(title='雷达图'),))radar1.render()

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import mathimport randomfrom pyecharts.faker import Fakerfrom pyecharts import options as optsfrom pyecharts.charts import Page, Polarc = (Polar().add_schema(angleaxis_opts=opts.AngleAxisOpts(data=https://www.it610.com/article/Faker.week, type_="category")).add("A", [1, 2, 3, 4, 3, 5, 1], type_="bar", stack="stack0").add("B", [2, 4, 6, 1, 2, 3, 1], type_="bar", stack="stack0").add("C", [1, 2, 3, 4, 1, 2, 5], type_="bar", stack="stack0").set_global_opts(title_opts=opts.TitleOpts(title="Polar-AngleAxis")))c.render()

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import mathimport randomfrom pyecharts.faker import Fakerfrom pyecharts import options as optsfrom pyecharts.charts import Page, Polardata = https://www.it610.com/article/[(i, random.randint(1, 100)) for i in range(10)]c = (Polar().add("", data, type_="effectScatter",effect_opts=opts.EffectOpts(scale=10, period=5),label_opts=opts.LabelOpts(is_show=False))#type默认为"line",#"effectScatter"，scatter,bar.set_global_opts(title_opts=opts.TitleOpts(title="Polar-Scatter0")))c.render()

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import mathimport randomfrom pyecharts.faker import Fakerfrom pyecharts import options as optsfrom pyecharts.charts import Page, Polarc = (Polar().add_schema(radiusaxis_opts=opts.RadiusAxisOpts(data=https://www.it610.com/article/Faker.week, type_="category")).add("A", [1, 2, 3, 4, 3, 5, 1], type_="bar", stack="stack0").add("B", [2, 4, 6, 1, 2, 3, 1], type_="bar", stack="stack0").add("C", [1, 2, 3, 4, 1, 2, 5], type_="bar", stack="stack0").set_global_opts(title_opts=opts.TitleOpts(title="Polar-RadiusAxis")))c.render()

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from pyecharts import options as optsfrom pyecharts.charts import Liquid, Pagefrom pyecharts.globals import SymbolType c = (Liquid().add("lq", [0.61, 0.7],shape='rect',is_outline_show=False)# 水球外形，有' circle', 'rect', 'roundRect', 'triangle', 'diamond', 'pin', 'arrow' 可选。# 默认 'circle'。也可以为自定义的 SVG 路径。#is_outline_show设置边框.set_global_opts(title_opts=opts.TitleOpts(title="Liquid-基本示例")))c.render()

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散点图：

from pyecharts.charts import Scatterimport pyecharts.options as opts female_height = [161.2,167.5,159.5,157,155.8,170,159.1,166,176.2,160.2,172.5,170.9,172.9,153.4,160,147.2,168.2,175,157,167.6,159.5,175,166.8,176.5,170.2,]female_weight = [51.6,59,49.2,63,53.6,59,47.6,69.8,66.8,75.2,55.2,54.2,62.5,42,50,49.8,49.2,73.2,47.8,68.8,50.6,82.5,57.2,87.8,72.8,54.5,] male_height = [174 ,175.3 ,193.5 ,186.5 ,187.2 ,181.5 ,184 ,184.5 ,175 ,184 ,180 ,177.8 ,192 ,176 ,174 ,184 ,192.7 ,171.5 ,173 ,176 ,176 ,180.5 ,172.7 ,176 ,173.5 ,178 ,]male_weight = [65.6 ,71.8 ,80.7 ,72.6 ,78.8 ,74.8 ,86.4 ,78.4 ,62 ,81.6 ,76.6 ,83.6 ,90 ,74.6 ,71 ,79.6 ,93.8 ,70 ,72.4 ,85.9 ,78.8 ,77.8 ,66.2 ,86.4 ,81.8 ,89.6 ,] scatter = Scatter()scatter.add_xaxis(female_height)scatter.add_xaxis(male_height)scatter.add_yaxis("female", female_weight, symbol_size=15) #散点大小scatter.add_yaxis("male", male_weight, symbol_size=15) #散点大小scatter.set_global_opts(title_opts=opts.TitleOpts(title="身高体重分布"),xaxis_opts=opts.AxisOpts(type_ = "value", # 设置x轴为数值轴splitline_opts=opts.SplitLineOpts(is_show = True)), # x轴分割线yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(is_show=True))# y轴分割线)scatter.set_series_opts(label_opts=opts.LabelOpts(is_show=False))scatter.render("./html/scatter_base.html")