Hello everyone , I meet you again , I'm your friend, Quan Jun
Yu Yu Liu , Now a start-up company is in charge of technology , Do crawler and data processing related work , I have been engaged in the research and development of card system 、 Research and development of financial cloud computing service system , Big data research and development in the direction of Internet of things , Write a Book ,《Python3.5 Learn from scratch 》How to do Python Of data visualization ？
pyecharts Is one used to generate Echarts Class library for diagrams . Echarts Baidu open source is a data visualization JS library . Mainly used for data visualization .
One 、 install
pyecharts compatible Python2 and Python3. The current version is 0.1.4
pip install pyecharts
Two 、 introduction
Let's start with your first chart
frompyecharts importBarbar =Bar(“ My first chart “, “ Here is the subtitle “)bar.add(“ clothing “, [“ shirt “, “ Woolen sweater “, “ Snow spins unlined upper garment “, “ The trousers “, “ High heels “, “ socks “], [5, 20, 36, 10, 75, 90])bar.show_config()bar.render()
Tip： You can press the download button on the right to download the picture to the local
Basically all chart types are drawn like this ：
3、 ... and 、 Chart type
Because of the length , Here are only examples of each chart type （ Code + Generate charts ）, The purpose is to arouse the interest of readers . Please refer to the project for detailed parameter introduction README.md file
1 Bar（ Histogram / Bar chart ）
frompyecharts importBarbar =Bar(“ Examples of marker lines and marker points “)bar.add(“ merchants A“, attr, v1, mark_point=[“average“])bar.add(“ merchants B“, attr, v2, mark_line=[“min“, “max“])bar.render()
frompyecharts importBarbar =Bar(“x Axis and y Axis exchange “)bar.add(“ merchants A“, attr, v1)bar.add(“ merchants B“, attr, v2, is_convert=True)bar.render()
2 EffectScatter（ Scatter with ripple effect animation ）
frompyecharts importEffectScatterv1 =[10, 20, 30, 40, 50, 60]v2 =[25, 20, 15, 10, 60, 33]es =EffectScatter(“ Dynamic scatter diagram example “)es.add(“effectScatter“, v1, v2)es.render()
es =EffectScatter(“ Various graphic examples of dynamic scatter diagram “)es.add(“”, [10], [10], symbol_size=20, effect_scale=3.5, effect_period=3, symbol=“pin“)es.add(“”, [20], [20], symbol_size=12, effect_scale=4.5, effect_period=4,symbol=“rect“)es.add(“”, [30], [30], symbol_size=30, effect_scale=5.5, effect_period=5,symbol=“roundRect“)es.add(“”, [40], [40], symbol_size=10, effect_scale=6.5, effect_brushtype=‘fill‘,symbol=“diamond“)es.add(“”, [50], [50], symbol_size=16, effect_scale=5.5, effect_period=3,symbol=“arrow“)es.add(“”, [60], [60], symbol_size=6, effect_scale=2.5, effect_period=3,symbol=“triangle“)es.render()
3 Funnel（ Funnel diagram ）
frompyecharts importFunnelattr =[“ shirt “, “ Woolen sweater “, “ Snow spins unlined upper garment “, “ The trousers “, “ High heels “, “ socks “]value =[20, 40, 60, 80, 100, 120]funnel =Funnel(“ Example funnel chart “)funnel.add(“ goods “, attr, value, is_label_show=True, label_pos=“inside“, label_text_color=“#fff“)funnel.render()
4 Gauge（ The dashboard ）
frompyecharts importGaugegauge =Gauge(“ Example dashboard “)gauge.add(“ Business indicators “, “ Completion rate “, 66.66)gauge.show_config()gauge.render()
5 Geo（ Geographic coordinate system ）
frompyecharts importGeodata =[ (“ Haimen “, 9),(“ ordos “, 12),(“ Zhaoyuan “, 12),(“ zhoushan “, 12),(“ Qiqihar “, 14),(“ yancheng “, 15), (“ Chifeng “, 16),(“ Qingdao “, 18),(“ Rushan “, 18),(“ Jinchang “, 19),(“ quanzhou “, 21),(“ Laixi “, 21), (“ sunshine “, 21),(“ Jiaonan “, 22),(“ nantong “, 23),(“ Lhasa “, 24),(“ The clouds are floating “, 24),(“ Meizhou “, 25)…]geo =Geo(“ Air quality in major cities of the country “, “data from pm2.5“, title_color=“#fff“, title_pos=“center“,width=1200, height=600, background_color=‘#404a59‘)attr, value =geo.cast(data)geo.add(“”, attr, value, visual_range=[0, 200], visual_text_color=“#fff“, symbol_size=15, is_visualmap=True)geo.show_config()geo.render()
frompyecharts importGeodata =[(“ Haimen “, 9), (“ ordos “, 12), (“ Zhaoyuan “, 12), (“ zhoushan “, 12), (“ Qiqihar “, 14), (“ yancheng “, 15)]geo =Geo(“ Air quality in major cities of the country “, “data from pm2.5“, title_color=“#fff“, title_pos=“center“, width=1200, height=600, background_color=‘#404a59‘)attr, value =geo.cast(data)geo.add(“”, attr, value, type=“effectScatter“, is_random=True, effect_scale=5)geo.show_config()geo.render()
6 Graph（ The diagram ）
frompyecharts importGraphnodes =[{ “name“: “ node 1“, “symbolSize“: 10}, { “name“: “ node 2“, “symbolSize“: 20}, { “name“: “ node 3“, “symbolSize“: 30}, { “name“: “ node 4“, “symbolSize“: 40}, { “name“: “ node 5“, “symbolSize“: 50}, { “name“: “ node 6“, “symbolSize“: 40}, { “name“: “ node 7“, “symbolSize“: 30}, { “name“: “ node 8“, “symbolSize“: 20}]links =[]fori innodes: forj innodes: links.append({ “source“: i.get(‘name‘), “target“: j.get(‘name‘)})graph =Graph(“ The diagram - An example of a circular layout “)graph.add(“”, nodes, links, is_label_show=True, repulsion=8000, layout=‘circular‘, label_text_color=None)graph.show_config()graph.render()
frompyecharts importGraphimportjsonwithopen(“..jsonweibo.json“, “r“, encoding=“utf-8“) asf: j =json.load(f) nodes, links, categories, cont, mid, userl =jgraph =Graph(“ Microblog forwarding diagram “, width=1200, height=600)graph.add(“”, nodes, links, categories, label_pos=“right“, repulsion=50, is_legend_show=False, line_curve=0.2, label_text_color=None)graph.show_config()graph.render()
7 Line（ Broken line / Area map ）
frompyecharts importLineattr =[“ shirt “, “ Woolen sweater “, “ Snow spins unlined upper garment “, “ The trousers “, “ High heels “, “ socks “]v1 =[5, 20, 36, 10, 10, 100]v2 =[55, 60, 16, 20, 15, 80]line =Line(“ Example of line chart “)line.add(“ merchants A“, attr, v1, mark_point=[“average“])line.add(“ merchants B“, attr, v2, is_smooth=True, mark_line=[“max“, “average“])line.show_config()line.render()
line =Line(“ Broken line diagram - Example of ladder diagram “)line.add(“ merchants A“, attr, v1, is_step=True, is_label_show=True)line.show_config()line.render()
line =Line(“ Broken line diagram - Area map example “)line.add(“ merchants A“, attr, v1, is_fill=True, line_opacity=0.2, area_opacity=0.4, symbol=None)line.add(“ merchants B“, attr, v2, is_fill=True, area_color=‘#000‘, area_opacity=0.3, is_smooth=True)line.show_config()line.render()
8 Liquid（ Water polo ）
frompyecharts importLiquidliquid =Liquid(“ Example of water polo diagram “)liquid.add(“Liquid“, [0.6])liquid.show_config()liquid.render()
frompyecharts importLiquidliquid =Liquid(“ Example of water polo diagram “)liquid.add(“Liquid“, [0.6, 0.5, 0.4, 0.3], is_liquid_outline_show=False)liquid.show_config()liquid.render()
frompyecharts importLiquidliquid =Liquid(“ Example of water polo diagram “)liquid.add(“Liquid“, [0.6, 0.5, 0.4, 0.3], is_liquid_animation=False, shape=‘diamond‘)liquid.show_config()liquid.render()
9 Map（ Map ）
frompyecharts importMapvalue =[155, 10, 66, 78, 33, 80, 190, 53, 49.6]attr =[“ fujian “, “ Shandong “, “ Beijing “, “ Shanghai “, “ gansu “, “ xinjiang “, “ Henan “, “ guangxi “, “ Tibet “]map=Map(“Map combination VisualMap Example “, width=1200, height=600)map.add(“”, attr, value, maptype=‘china‘, is_visualmap=True, visual_text_color=‘#000‘)map.show_config()map.render()
frompyecharts importMapvalue =[20, 190, 253, 77, 65]attr =[‘ Shantou city ‘, ‘ Shanwei cities ‘, ‘ Jieyang city ‘, ‘ yangjiang ‘, ‘ Zhaoqing city ‘]map=Map(“ Guangdong map example “, width=1200, height=600)map.add(“”, attr, value, maptype=‘ guangdong ‘, is_visualmap=True, visual_text_color=‘#000‘)map.show_config()map.render()
10 Parallel（ Parallel coordinate system ）
frompyecharts importParallelc_schema =[ { “dim“: 0, “name“: “data“}, { “dim“: 1, “name“: “AQI“}, { “dim“: 2, “name“: “PM2.5“}, { “dim“: 3, “name“: “PM10“}, { “dim“: 4, “name“: “CO“}, { “dim“: 5, “name“: “NO2“}, { “dim“: 6, “name“: “CO2“}, { “dim“: 7, “name“: “ Grade “, “type“: “category“, “data“: [‘ optimal ‘, ‘ good ‘, ‘ Light pollution ‘, ‘ Moderate pollution ‘, ‘ Severe pollution ‘, ‘ Serious pollution ‘]}]data =[ [1, 91, 45, 125, 0.82, 34, 23, “ good “], [2, 65, 27, 78, 0.86, 45, 29, “ good “], [3, 83, 60, 84, 1.09, 73, 27, “ good “], [4, 109, 81, 121, 1.28, 68, 51, “ Light pollution “], [5, 106, 77, 114, 1.07, 55, 51, “ Light pollution “], [6, 109, 81, 121, 1.28, 68, 51, “ Light pollution “], [7, 106, 77, 114, 1.07, 55, 51, “ Light pollution “], [8, 89, 65, 78, 0.86, 51, 26, “ good “], [9, 53, 33, 47, 0.64, 50, 17, “ good “], [10, 80, 55, 80, 1.01, 75, 24, “ good “], [11, 117, 81, 124, 1.03, 45, 24, “ Light pollution “], [12, 99, 71, 142, 1.1, 62, 42, “ good “], [13, 95, 69, 130, 1.28, 74, 50, “ good “], [14, 116, 87, 131, 1.47, 84, 40, “ Light pollution “]]parallel =Parallel(“ Parallel coordinate system - User defined indicator “)parallel.config(c_schema=c_schema)parallel.add(“parallel“, data)parallel.show_config()parallel.render()
11 Pie（ The pie chart ）
frompyecharts importPieattr =[“ shirt “, “ Woolen sweater “, “ Snow spins unlined upper garment “, “ The trousers “, “ High heels “, “ socks “]v1 =[11, 12, 13, 10, 10, 10]pie =Pie(“ Pie chart example “)pie.add(“”, attr, v1, is_label_show=True)pie.show_config()pie.render()
frompyecharts importPieattr =[“ shirt “, “ Woolen sweater “, “ Snow spins unlined upper garment “, “ The trousers “, “ High heels “, “ socks “]v1 =[11, 12, 13, 10, 10, 10]v2 =[19, 21, 32, 20, 20, 33]pie =Pie(“ The pie chart - An example of a rose chart “, title_pos=‘center‘, width=900)pie.add(“ goods A“, attr, v1, center=[25, 50], is_random=True, radius=[30, 75], rosetype=‘radius‘)pie.add(“ goods B“, attr, v2, center=[75, 50], is_random=True, radius=[30, 75], rosetype=‘area‘, is_legend_show=False, is_label_show=True)pie.show_config() pie.render()
12 Polar（ Polar system ）
frompyecharts importPolarradius =[‘ Monday ‘, ‘ Tuesday ‘, ‘ Wednesday ‘, ‘ Thursday ‘, ‘ Friday ‘, ‘ Saturday ‘, ‘ Sunday ‘]polar =Polar(“ Polar system - Stacked histogram example “, width=1200, height=600)polar.add(“A“, [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type=‘barRadius‘, is_stack=True)polar.add(“B“, [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type=‘barRadius‘, is_stack=True)polar.add(“C“, [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type=‘barRadius‘, is_stack=True)polar.show_config()polar.render()
frompyecharts importPolarradius =[‘ Monday ‘, ‘ Tuesday ‘, ‘ Wednesday ‘, ‘ Thursday ‘, ‘ Friday ‘, ‘ Saturday ‘, ‘ Sunday ‘]polar =Polar(“ Polar system - Stacked histogram example “, width=1200, height=600)polar.add(“”, [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type=‘barAngle‘, is_stack=True)polar.add(“”, [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type=‘barAngle‘, is_stack=True)polar.add(“”, [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type=‘barAngle‘, is_stack=True)polar.show_config()polar.render()
13 Radar（ Radar map ）
frompyecharts importRadarschema =[ (“ sales “, 6500), (“ management “, 16000), (“ information technology “, 30000), (“ Customer service “, 38000), (“ Research and development “, 52000), (“ market “, 25000)]v1 =[[4300, 10000, 28000, 35000, 50000, 19000]]v2 =[[5000, 14000, 28000, 31000, 42000, 21000]]radar =Radar()radar.config(schema)radar.add(“ Budget allocation “, v1, is_splitline=True, is_axisline_show=True)radar.add(“ The actual cost “, v2, label_color=[“#4e79a7“], is_area_show=False)radar.show_config()radar.render()
value_bj =[ [55, 9, 56, 0.46, 18, 6, 1], [25, 11, 21, 0.65, 34, 9, 2], [56, 7, 63, 0.3, 14, 5, 3], [33, 7, 29, 0.33, 16, 6, 4]…]value_sh =[ [91, 45, 125, 0.82, 34, 23, 1], [65, 27, 78, 0.86, 45, 29, 2], [83, 60, 84, 1.09, 73, 27, 3], [109, 81, 121, 1.28, 68, 51, 4]…]c_schema=[{ “name“: “AQI“, “max“: 300, “min“: 5}, { “name“: “PM2.5“, “max“: 250, “min“: 20}, { “name“: “PM10“, “max“: 300, “min“: 5}, { “name“: “CO“, “max“: 5}, { “name“: “NO2“, “max“: 200}, { “name“: “SO2“, “max“: 100}]radar =Radar()radar.config(c_schema=c_schema, shape=‘circle‘)radar.add(“ Beijing “, value_bj, item_color=“#f9713c“, symbol=None)radar.add(“ Shanghai “, value_sh, item_color=“#b3e4a1“, symbol=None)radar.show_config()radar.render()
14 Scatter（ Scatter plot ）
frompyecharts importScatterv1 =[10, 20, 30, 40, 50, 60]v2 =[10, 20, 30, 40, 50, 60]scatter =Scatter(“ An example of a scatter diagram “)scatter.add(“A“, v1, v2)scatter.add(“B“, v1[::–1], v2)scatter.show_config()scatter.render()
Scatter print Pyecharts typeface .
frompyecharts importScatterscatter =Scatter(“ An example of a scatter diagram “)v1, v2 =scatter.draw(“../images/pyecharts-0.png“)scatter.add(“pyecharts“, v1, v2, is_random=True)scatter.show_config()scatter.render()
15 WordCloud（ Clouds of words ）
frompyecharts importWordCloudname =[‘Sam S Club‘, ‘Macys‘, ‘Amy Schumer‘, ‘Jurassic World‘, ‘Charter Communications‘, ‘Chick Fil A‘, ‘Planet Fitness‘, ‘Pitch Perfect‘, ‘Express‘, ‘Home‘, ‘Johnny Depp‘, ‘Lena Dunham‘, ‘Lewis Hamilton‘, ‘KXAN‘, ‘Mary Ellen Mark‘, ‘Farrah Abraham‘, ‘Rita Ora‘, ‘Serena Williams‘, ‘NCAA baseball tournament‘, ‘Point Break‘]value =[10000, 6181, 4386, 4055, 2467, 2244, 1898, 1484, 1112, 965, 847, 582, 555, 550, 462, 366, 360, 282, 273, 265]wordcloud =WordCloud(width=1300, height=620)wordcloud.add(“”, name, value, word_size_range=[20, 100])wordcloud.show_config()wordcloud.render()
wordcloud =WordCloud(width=1300, height=620)wordcloud.add(“”, name, value, word_size_range=[30, 100], shape=‘diamond‘)wordcloud.show_config()wordcloud.render()
5、 ... and 、 User customization
Users can also customize the combination Line/Bar Chart
Need to use get_series() and custom() Method
get_series()“”” Get the series data “””
custom(series)”’ Add custom chart type ”’
First use get_series() get data , Reuse custom() Combine charts
frompyecharts importBar, Lineattr =[‘A‘, ‘B‘, ‘C‘, ‘D‘, ‘E‘, ‘F‘]v1 =[10, 20, 30, 40, 50, 60]v2 =[15, 25, 35, 45, 55, 65]v3 =[38, 28, 58, 48, 78, 68]bar =Bar(“Line – Bar Example “)bar.add(“bar“, attr, v1)line =Line()line.add(“line“, v2, v3)bar.custom(line.get_series())bar.show_config()bar.render()
6、 ... and 、 More examples
Draw a love in polar coordinates
importmathfrompyecharts importPolardata =[]fori inrange(101): theta =i /100*360r =5*(1+math.sin(theta /180*math.pi)) data.append([r, theta])hour =[i fori inrange(1, 25)]polar =Polar(“ Example of polar coordinate system “, width=1200, height=600)polar.add(“Love“, data, angle_data=hour, boundary_gap=False,start_angle=0)polar.show_config()polar.render()
Draw a little flower in polar coordinates
importmathfrompyecharts importPolardata =[]fori inrange(361): t =i /180*math.pi r =math.sin(2*t) *math.cos(2*t) data.append([r, i])polar =Polar(“ Example of polar coordinate system “, width=1200, height=600)polar.add(“Flower“, data, start_angle=0, symbol=None, axis_range=[0, None])polar.show_config()polar.render()
You can also color the flowers
importmathfrompyecharts importPolardata =[]fori inrange(361): t =i /180*math.pi r =math.sin(2*t) *math.cos(2*t) data.append([r, i])polar =Polar(“ Example of polar coordinate system “, width=1200, height=600)polar.add(“Color-Flower“, data, start_angle=0, symbol=None, axis_range=[0, None], area_color=“#f71f24“, area_opacity=0.6)polar.show_config()polar.render()
Draw a love with scattered pictures
frompyecharts importScatterscatter =Scatter(“ An example of a scatter diagram “, width=800, height=480)v1 ,v2 =scatter.draw(“../images/love.png“)scatter.add(“Love“, v1, v2)scatter.render()
Draw a hot picture with scattered dots Bra
frompyecharts importScatterscatter =Scatter(“ An example of a scatter diagram “, width=1000, height=480)v1 ,v2 =scatter.draw(“../images/cup.png“)scatter.add(“Cup“, v1, v2)scatter.render()
Broken line chart of the lowest and highest temperature in a place
frompyecharts importLineattr =[‘ Monday ‘, ‘ Tuesday ‘, ‘ Wednesday ‘, ‘ Thursday ‘, ‘ Friday ‘, ‘ Saturday ‘, ‘ Sunday ‘, ]line =Line(“ Example of line chart “)line.add(“ The highest temperature “, attr, [11, 11, 15, 13, 12, 13, 10], mark_point=[“max“, “min“], mark_line=[“average“])line.add(“ Minimum temperature “, attr, [1, –2, 2, 5, 3, 2, 0], mark_point=[“max“, “min“], mark_line=[“average“], yaxis_formatter=“°C“)line.show_config()line.render()
Pie chart nesting
frompyecharts importPiepie =Pie(“ Pie chart example “, title_pos=‘center‘, width=1000, height=600)pie.add(“”, [‘A‘, ‘B‘, ‘C‘, ‘D‘, ‘E‘, ‘F‘], [335, 321, 234, 135, 251, 148], radius=[40, 55],is_label_show=True)pie.add(“”, [‘H‘, ‘I‘, ‘J‘], [335, 679, 204], radius=[0, 30], legend_orient=‘vertical‘, legend_pos=‘left‘)pie.show_config()pie.render()
The pie chart is nested again
importrandomfrompyecharts importPieattr =[‘A‘, ‘B‘, ‘C‘, ‘D‘, ‘E‘, ‘F‘]pie =Pie(“ Pie chart example “, width=1000, height=600)pie.add(“”, attr, [random.randint(0, 100) for_ inrange(6)], radius=[50, 55], center=[25, 50],is_random=True)pie.add(“”, attr, [random.randint(20, 100) for_ inrange(6)], radius=[0, 45], center=[25, 50],rosetype=‘area‘)pie.add(“”, attr, [random.randint(0, 100) for_ inrange(6)], radius=[50, 55], center=[65, 50],is_random=True)pie.add(“”, attr, [random.randint(20, 100) for_ inrange(6)], radius=[0, 45], center=[65, 50],rosetype=‘radius‘)pie.show_config()pie.render()
Histogram of precipitation and evaporation in a place
frompyecharts importBarattr =[“{} month “.format(i) fori inrange(1, 13)]v1 =[2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]v2 =[2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]bar =Bar(“ Example histogram “)bar.add(“ Evaporation capacity “, attr, v1, mark_line=[“average“], mark_point=[“max“, “min“])bar.add(“ precipitation “, attr, v2, mark_line=[“average“], mark_point=[“max“, “min“])bar.show_config()bar.render()
In all kinds of movies ” Good movie ” Proportion
frompyecharts importPiepie =Pie(‘ In all kinds of movies ” Good movie ” Proportion ‘, “ The data comes from Douban “, title_pos=‘center‘)pie.add(“”, [“ The plot “, “”], [25, 75], center=[10, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None, )pie.add(“”, [“ fantasy “, “”], [24, 76], center=[30, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None, legend_pos=‘left‘)pie.add(“”, [“ love “, “”], [14, 86], center=[50, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None)pie.add(“”, [“ Thriller “, “”], [11, 89], center=[70, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None)pie.add(“”, [“ adventure “, “”], [27, 73], center=[90, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None)pie.add(“”, [“ action “, “”], [15, 85], center=[10, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None)pie.add(“”, [“ comedy “, “”], [54, 46], center=[30, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None)pie.add(“”, [“ Science fiction “, “”], [26, 74], center=[50, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None)pie.add(“”, [“ The suspense “, “”], [25, 75], center=[70, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None)pie.add(“”, [“ crime “, “”], [28, 72], center=[90, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None, is_legend_show=True, legend_top=“center“)pie.show_config()pie.render()
Draw a snail shell in polar coordinates
importmathfrompyecharts importPolardata =[]fori inrange(5): forj inrange(101): theta =j /100*360alpha =i *360+theta r =math.pow(math.e, 0.003*alpha) data.append([r, theta])polar =Polar(“ Example of polar coordinate system “)polar.add(“”, data, symbol_size=0, symbol=‘circle‘, start_angle=-25, is_radiusaxis_show=False, area_color=“#f3c5b3“, area_opacity=0.5, is_angleaxis_show=False)polar.show_config()polar.render()
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