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全网最详细超长python学习笔记、14章节知识点很全面十分详细，快速入门，只用看这一篇你就学会了！

【1】windows系统如何安装后缀是whl的python库

【2】超级详细Python-matplotlib画图，手把手教你画图！（线条颜色、大小、线形、标签）

【3】超级详细matplotlib使用教程，手把手教你画图!(多个图、刻度、标签、图例等)

【4】python读写文件操作---详细讲解！

【5】数据可视化pygal，画出美观的图表

数据可视化pygal，画出美观的图表

这里有很多图表画图样式雷达图、金字塔图、特殊饼状图、柱状图、世界地图、箱图、等等

1.安装库

  1. pip install pygal -i https://pypi.douban.com/simple
  1. pip install cairosvg -i https://pypi.douban.com/simple
  1. pip install lxml -i https://pypi.douban.com/simple
  1. pip install tinycss -i https://pypi.douban.com/simple
  1. pip install cssselect -i https://pypi.douban.com/simple

依次安装依赖库，主要是为了渲染的效果。

如果出现如下报错：

  1. OSError: no library called "cairo" was found
  2. cannot load library 'libcairo.so': error 0x7e
  3. cannot load library 'libcairo.2.dylib': error 0x7e
  4. cannot load library 'libcairo-2.dll': error 0xc1

去官网https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer下载

  1. https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer

下载完成后，安装一直next即可，然后重启VScode.

2.画图简单一试

  1. import pygal  
  3. bar_chart = pygal.Bar()
  4. bar_chart.add('Fibonacci', [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55])
  5. bar_chart.render_to_file('bar_chart.svg')
  6. # Save the svg to a file

结果：

  • 把pygal这个模块导入，import进来
  • 建立一个柱状图，关键词是Bar。这个图定义为bar_chart，
  • 用add添加数据，为'Fibonacci'添加数据，
  • 把得到的图像保存为svg格式，存到当前的目录下面），保存的文件名就是ar_chart.svg，

  1. import pygal
  2. bar_chart = pygal.Bar()
  3. bar_chart.add('Fibonacci', [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55])
  4. bar_chart.add('Padovan', [1, 1, 1, 2, 2, 3, 4, 5, 7, 9, 12])
  5. #bar_chart.render()
  6. bar_chart.render_to_file('bar_chart.svg')

结果

把原来的Bar换成HorizontalStackedBar，水平堆积条形图

  1. import pygal
  2. bar_chart = pygal.HorizontalStackedBar()
  3. bar_chart.add('Fibonacci', [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55])
  4. bar_chart.add('Padovan', [1, 1, 1, 2, 2, 3, 4, 5, 7, 9, 12])
  5. bar_chart.render_to_file('bar_chart.svg')

下面添加标题和坐标轴：

3.图表类型

pygal官网：http://www.pygal.org/en/stable/documentation/types/index.html#chart-types 里面有各种类型图表以及代码参考

提示库都是要导入的：

  1. import pygal
  2. from datetime import datetime   # 你需要日期参数
  3. from math import cos   # 你需要用到cos函数

line

Basic

  1. line_chart = pygal.Line()
  2. line_chart.title = 'Browser usage evolution (in %)'
  3. line_chart.x_labels = map(str, range(2002, 2013))
  4. line_chart.add('Firefox', [None, None,    0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
  5. line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
  6. line_chart.add('IE',      [85.8, 84.6, 84.7, 74.5,   66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1])
  7. line_chart.add('Others',  [14.2, 15.4, 15.3,  8.9,    9, 10.4,  8.9,  5.8,  6.7,  6.8,  7.5])
  8. line_chart.render()

Horizontal Line

  1. line_chart = pygal.HorizontalLine()
  2. line_chart.title = 'Browser usage evolution (in %)'
  3. line_chart.x_labels = map(str, range(2002, 2013))
  4. line_chart.add('Firefox', [None, None,    0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
  5. line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
  6. line_chart.add('IE',      [85.8, 84.6, 84.7, 74.5,   66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1])
  7. line_chart.add('Others',  [14.2, 15.4, 15.3,  8.9,    9, 10.4,  8.9,  5.8,  6.7,  6.8,  7.5])
  8. line_chart.range = [0, 100]
  9. line_chart.render()

Stacked

  1. line_chart = pygal.StackedLine(fill=True)
  2. line_chart.title = 'Browser usage evolution (in %)'
  3. line_chart.x_labels = map(str, range(2002, 2013))
  4. line_chart.add('Firefox', [None, None, 0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
  5. line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
  6. line_chart.add('IE',      [85.8, 84.6, 84.7, 74.5,   66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1])
  7. line_chart.add('Others',  [14.2, 15.4, 15.3,  8.9,    9, 10.4,  8.9,  5.8,  6.7,  6.8,  7.5])
  8. line_chart.render()

  1. from datetime import datetime, timedelta
  2. date_chart = pygal.Line(x_label_rotation=20)
  3. date_chart.x_labels = map(lambda d: d.strftime('%Y-%m-%d'), [
  4.  datetime(2013, 1, 2),
  5.  datetime(2013, 1, 12),
  6.  datetime(2013, 2, 2),
  7.  datetime(2013, 2, 22)])
  8. date_chart.add("Visits", [300, 412, 823, 672])
  9. date_chart.render()

Bar

Basic

  1. line_chart = pygal.Bar()
  2. line_chart.title = 'Browser usage evolution (in %)'
  3. line_chart.x_labels = map(str, range(2002, 2013))
  4. line_chart.add('Firefox', [None, None, 0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
  5. line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
  6. line_chart.add('IE',      [85.8, 84.6, 84.7, 74.5,   66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1])
  7. line_chart.add('Others',  [14.2, 15.4, 15.3,  8.9,    9, 10.4,  8.9,  5.8,  6.7,  6.8,  7.5])
  8. line_chart.render()

Stacked

  1. line_chart = pygal.StackedBar()
  2. line_chart.title = 'Browser usage evolution (in %)'
  3. line_chart.x_labels = map(str, range(2002, 2013))
  4. line_chart.add('Firefox', [None, None, 0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
  5. line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
  6. line_chart.add('IE',      [85.8, 84.6, 84.7, 74.5,   66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1])
  7. line_chart.add('Others',  [14.2, 15.4, 15.3,  8.9,    9, 10.4,  8.9,  5.8,  6.7,  6.8,  7.5])
  8. line_chart.render()

Horizontal

  1. line_chart = pygal.HorizontalBar()
  2. line_chart.title = 'Browser usage in February 2012 (in %)'
  3. line_chart.add('IE', 19.5)
  4. line_chart.add('Firefox', 36.6)
  5. line_chart.add('Chrome', 36.3)
  6. line_chart.add('Safari', 4.5)
  7. line_chart.add('Opera', 2.3)
  8. line_chart.render()

Histogram

柱状图是一种特殊的柱状图，它为一个柱状图取3个值:纵坐标高度、横坐标开始和横坐标结束。

  1. hist = pygal.Histogram()
  2. hist.add('Wide bars', [(5, 0, 10), (4, 5, 13), (2, 0, 15)])
  3. hist.add('Narrow bars',  [(10, 1, 2), (12, 4, 4.5), (8, 11, 13)])
  4. hist.render()

XY

Basic

  1. from math import cos
  2. xy_chart = pygal.XY()
  3. xy_chart.title = 'XY Cosinus'
  4. xy_chart.add('x = cos(y)', [(cos(x / 10.), x / 10.) for x in range(-50, 50, 5)])
  5. xy_chart.add('y = cos(x)', [(x / 10., cos(x / 10.)) for x in range(-50, 50, 5)])
  6. xy_chart.add('x = 1',  [(1, -5), (1, 5)])
  7. xy_chart.add('x = -1', [(-1, -5), (-1, 5)])
  8. xy_chart.add('y = 1',  [(-5, 1), (5, 1)])
  9. xy_chart.add('y = -1', [(-5, -1), (5, -1)])
  10. xy_chart.render()

Scatter Plot

  1. xy_chart = pygal.XY(stroke=False)
  2. xy_chart.title = 'Correlation'
  3. xy_chart.add('A', [(0, 0), (.1, .2), (.3, .1), (.5, 1), (.8, .6), (1, 1.08), (1.3, 1.1), (2, 3.23), (2.43, 2)])
  4. xy_chart.add('B', [(.1, .15), (.12, .23), (.4, .3), (.6, .4), (.21, .21), (.5, .3), (.6, .8), (.7, .8)])
  5. xy_chart.add('C', [(.05, .01), (.13, .02), (1.5, 1.7), (1.52, 1.6), (1.8, 1.63), (1.5, 1.82), (1.7, 1.23), (2.1, 2.23), (2.3, 1.98)])
  6. xy_chart.render()

Pie

  1. pie_chart = pygal.Pie()
  2. pie_chart.title = 'Browser usage in February 2012 (in %)'
  3. pie_chart.add('IE', 19.5)
  4. pie_chart.add('Firefox', 36.6)
  5. pie_chart.add('Chrome', 36.3)
  6. pie_chart.add('Safari', 4.5)
  7. pie_chart.add('Opera', 2.3)
  8. pie_chart.render()

Multi-series pie

  1. pie_chart = pygal.Pie()
  2. pie_chart.title = 'Browser usage by version in February 2012 (in %)'
  3. pie_chart.add('IE', [5.7, 10.2, 2.6, 1])
  4. pie_chart.add('Firefox', [.6, 16.8, 7.4, 2.2, 1.2, 1, 1, 1.1, 4.3, 1])
  5. pie_chart.add('Chrome', [.3, .9, 17.1, 15.3, .6, .5, 1.6])
  6. pie_chart.add('Safari', [4.4, .1])
  7. pie_chart.add('Opera', [.1, 1.6, .1, .5])
  8. pie_chart.render()

  1. pie_chart = pygal.Pie(inner_radius=.4)
  2. pie_chart.title = 'Browser usage in February 2012 (in %)'
  3. pie_chart.add('IE', 19.5)
  4. pie_chart.add('Firefox', 36.6)
  5. pie_chart.add('Chrome', 36.3)
  6. pie_chart.add('Safari', 4.5)
  7. pie_chart.add('Opera', 2.3)
  8. pie_chart.render()

  1. pie_chart = pygal.Pie(inner_radius=.75)

  1. pie_chart = pygal.Pie(half_pie=True)

Radar

  1. radar_chart = pygal.Radar()
  2. radar_chart.title = 'V8 benchmark results'
  3. radar_chart.x_labels = ['Richards', 'DeltaBlue', 'Crypto', 'RayTrace', 'EarleyBoyer', 'RegExp', 'Splay', 'NavierStokes']
  4. radar_chart.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])
  5. radar_chart.add('Firefox', [7473, 8099, 11700, 2651, 6361, 1044, 3797, 9450])
  6. radar_chart.add('Opera', [3472, 2933, 4203, 5229, 5810, 1828, 9013, 4669])
  7. radar_chart.add('IE', [43, 41, 59, 79, 144, 136, 34, 102])
  8. radar_chart.render()

Box

默认情况下，使用极端模式，即须是数据集的极端，方框从第一个四分位数到第三个四分位数，中间的线是中间值。

  1. box_plot = pygal.Box()
  2. box_plot.title = 'V8 benchmark results'
  3. box_plot.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])
  4. box_plot.add('Firefox', [7473, 8099, 11700, 2651, 6361, 1044, 3797, 9450])
  5. box_plot.add('Opera', [3472, 2933, 4203, 5229, 5810, 1828, 9013, 4669])
  6. box_plot.add('IE', [43, 41, 59, 79, 144, 136, 34, 102])
  7. box_plot.render()

  1. box_plot = pygal.Box(box_mode="1.5IQR")
  1. box_plot = pygal.Box(box_mode="tukey")
  1. box_plot = pygal.Box(box_mode="stdev")
  1. box_plot = pygal.Box(box_mode="pstdev")

各个类型的自己可以试一下。

SolidGauge

  1. gauge = pygal.SolidGauge(inner_radius=0.70)
  2. percent_formatter = lambda x: '{:.10g}%'.format(x)
  3. dollar_formatter = lambda x: '{:.10g}$'.format(x)
  4. gauge.value_formatter = percent_formatter
  6. gauge.add('Series 1', [{'value': 225000, 'max_value': 1275000}],
  7.           formatter=dollar_formatter)
  8. gauge.add('Series 2', [{'value': 110, 'max_value': 100}])
  9. gauge.add('Series 3', [{'value': 3}])
  10. gauge.add(
  11.     'Series 4', [
  12.         {'value': 51, 'max_value': 100},
  13.         {'value': 12, 'max_value': 100}])
  14. gauge.add('Series 5', [{'value': 79, 'max_value': 100}])
  15. gauge.add('Series 6', 99)
  16. gauge.add('Series 7', [{'value': 100, 'max_value': 100}])
  17. gauge.render()

  1. gauge = pygal.SolidGauge(
  2.     half_pie=True, inner_radius=0.70,
  3.     style=pygal.style.styles['default'](value_font_size=10))
  5. percent_formatter = lambda x: '{:.10g}%'.format(x)
  6. dollar_formatter = lambda x: '{:.10g}$'.format(x)
  7. gauge.value_formatter = percent_formatter
  9. gauge.add('Series 1', [{'value': 225000, 'max_value': 1275000}],
  10.           formatter=dollar_formatter)
  11. gauge.add('Series 2', [{'value': 110, 'max_value': 100}])
  12. gauge.add('Series 3', [{'value': 3}])
  13. gauge.add(
  14.     'Series 4', [
  15.         {'value': 51, 'max_value': 100},
  16.         {'value': 12, 'max_value': 100}])
  17. gauge.add('Series 5', [{'value': 79, 'max_value': 100}])
  18. gauge.add('Series 6', 99)
  19. gauge.add('Series 7', [{'value': 100, 'max_value': 100}])
  20. gauge.render()

Gauge

  1. gauge_chart = pygal.Gauge(human_readable=True)
  2. gauge_chart.title = 'DeltaBlue V8 benchmark results'
  3. gauge_chart.range = [0, 10000]
  4. gauge_chart.add('Chrome', 8212)
  5. gauge_chart.add('Firefox', 8099)
  6. gauge_chart.add('Opera', 2933)
  7. gauge_chart.add('IE', 41)
  8. gauge_chart.render()

*Pyramid

  1. ages = [(364381, 358443, 360172, 345848, 334895, 326914, 323053, 312576, 302015, 301277, 309874, 318295, 323396, 332736, 330759, 335267, 345096, 352685, 368067, 381521, 380145, 378724, 388045, 382303, 373469, 365184, 342869, 316928, 285137, 273553, 250861, 221358, 195884, 179321, 171010, 162594, 152221, 148843, 143013, 135887, 125824, 121493, 115913, 113738, 105612, 99596, 91609, 83917, 75688, 69538, 62999, 58864, 54593, 48818, 44739, 41096, 39169, 36321, 34284, 32330, 31437, 30661, 31332, 30334, 23600, 21999, 20187, 19075, 16574, 15091, 14977, 14171, 13687, 13155, 12558, 11600, 10827, 10436, 9851, 9794, 8787, 7993, 6901, 6422, 5506, 4839, 4144, 3433, 2936, 2615),
  2.    (346205, 340570, 342668, 328475, 319010, 312898, 308153, 296752, 289639, 290466, 296190, 303871, 309886, 317436, 315487, 316696, 325772, 331694, 345815, 354696, 354899, 351727, 354579, 341702, 336421, 321116, 292261, 261874, 242407, 229488, 208939, 184147, 162662, 147361, 140424, 134336, 126929, 125404, 122764, 116004, 105590, 100813, 95021, 90950, 85036, 79391, 72952, 66022, 59326, 52716, 46582, 42772, 38509, 34048, 30887, 28053, 26152, 23931, 22039, 20677, 19869, 19026, 18757, 18308, 14458, 13685, 12942, 12323, 11033, 10183, 10628, 10803, 10655, 10482, 10202, 10166, 9939, 10138, 10007, 10174, 9997, 9465, 9028, 8806, 8450, 7941, 7253, 6698, 6267, 5773),
  3.    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 23, 91, 412, 1319, 2984, 5816, 10053, 16045, 24240, 35066, 47828, 62384, 78916, 97822, 112738, 124414, 130658, 140789, 153951, 168560, 179996, 194471, 212006, 225209, 228886, 239690, 245974, 253459, 255455, 260715, 259980, 256481, 252222, 249467, 240268, 238465, 238167, 231361, 223832, 220459, 222512, 220099, 219301, 221322, 229783, 239336, 258360, 271151, 218063, 213461, 207617, 196227, 174615, 160855, 165410, 163070, 157379, 149698, 140570, 131785, 119936, 113751, 106989, 99294, 89097, 78413, 68174, 60592, 52189, 43375, 35469, 29648, 24575, 20863),
  4.    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 74, 392, 1351, 3906, 7847, 12857, 19913, 29108, 42475, 58287, 74163, 90724, 108375, 125886, 141559, 148061, 152871, 159725, 171298, 183536, 196136, 210831, 228757, 238731, 239616, 250036, 251759, 259593, 261832, 264864, 264702, 264070, 258117, 253678, 245440, 241342, 239843, 232493, 226118, 221644, 223440, 219833, 219659, 221271, 227123, 232865, 250646, 261796, 210136, 201824, 193109, 181831, 159280, 145235, 145929, 140266, 133082, 124350, 114441, 104655, 93223, 85899, 78800, 72081, 62645, 53214, 44086, 38481, 32219, 26867, 21443, 16899, 13680, 11508),
  5.    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 5, 17, 15, 31, 34, 38, 35, 45, 299, 295, 218, 247, 252, 254, 222, 307, 316, 385, 416, 463, 557, 670, 830, 889, 1025, 1149, 1356, 1488, 1835, 1929, 2130, 2362, 2494, 2884, 3160, 3487, 3916, 4196, 4619, 5032, 5709, 6347, 7288, 8139, 9344, 11002, 12809, 11504, 11918, 12927, 13642, 13298, 14015, 15751, 17445, 18591, 19682, 20969, 21629, 22549, 23619, 25288, 26293, 27038, 27039, 27070, 27750, 27244, 25905, 24357, 22561, 21794, 20595),
  6.    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 8, 0, 8, 21, 34, 49, 84, 97, 368, 401, 414, 557, 654, 631, 689, 698, 858, 1031, 1120, 1263, 1614, 1882, 2137, 2516, 2923, 3132, 3741, 4259, 4930, 5320, 5948, 6548, 7463, 8309, 9142, 10321, 11167, 12062, 13317, 15238, 16706, 18236, 20336, 23407, 27024, 32502, 37334, 34454, 38080, 41811, 44490, 45247, 46830, 53616, 58798, 63224, 66841, 71086, 73654, 77334, 82062, 87314, 92207, 94603, 94113, 92753, 93174, 91812, 87757, 84255, 79723, 77536, 74173),
  7.    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 5, 0, 11, 35, 137, 331, 803, 1580, 2361, 3632, 4866, 6849, 8754, 10422, 12316, 14152, 16911, 19788, 22822, 27329, 31547, 35711, 38932, 42956, 46466, 49983, 52885, 55178, 56549, 57632, 57770, 57427, 56348, 55593, 55554, 53266, 51084, 49342, 48555, 47067, 45789, 44988, 44624, 44238, 46267, 46203, 36964, 33866, 31701, 28770, 25174, 22702, 21934, 20638, 19051, 17073, 15381, 13736, 11690, 10368, 9350, 8375, 7063, 6006, 5044, 4030, 3420, 2612, 2006, 1709, 1264, 1018),
  8.    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 6, 11, 20, 68, 179, 480, 1077, 2094, 3581, 5151, 7047, 9590, 12434, 15039, 17257, 19098, 21324, 24453, 27813, 32316, 37281, 43597, 49647, 53559, 58888, 62375, 67219, 70956, 73547, 74904, 75994, 76224, 74979, 72064, 70330, 68944, 66527, 63073, 60899, 60968, 58756, 57647, 56301, 57246, 57068, 59027, 59187, 47549, 44425, 40976, 38077, 32904, 29431, 29491, 28020, 26086, 24069, 21742, 19498, 17400, 15738, 14451, 13107, 11568, 10171, 8530, 7273, 6488, 5372, 4499, 3691, 3259, 2657)]
  10. types = ['Males single', 'Females single',
  11.          'Males married', 'Females married',
  12.          'Males widowed', 'Females widowed',
  13.          'Males divorced', 'Females divorced']
  15. pyramid_chart = pygal.Pyramid(human_readable=True, legend_at_bottom=True)
  16. pyramid_chart.title = 'England population by age in 2010 (source: ons.gov.uk)'
  17. pyramid_chart.x_labels = map(lambda x: str(x) if not x % 5 else '', range(90))
  18. for type, age in zip(types, ages):
  19.     pyramid_chart.add(type, age)
  20. pyramid_chart.render()

Treemap

  1. treemap = pygal.Treemap()
  2. treemap.title = 'Binary TreeMap'
  3. treemap.add('A', [2, 1, 12, 4, 2, 1, 1, 3, 12, 3, 4, None, 9])
  4. treemap.add('B', [4, 2, 5, 10, 3, 4, 2, 7, 4, -10, None, 8, 3, 1])
  5. treemap.add('C', [3, 8, 3, 3, 5, 3, 3, 5, 4, 12])
  6. treemap.add('D', [23, 18])
  7. treemap.add('E', [1, 2, 1, 2, 3, 3, 1, 2, 3,
  8.       4, 3, 1, 2, 1, 1, 1, 1, 1])
  9. treemap.add('F', [31])
  10. treemap.add('G', [5, 9.3, 8.1, 12, 4, 3, 2])
  11. treemap.add('H', [12, 3, 3])
  12. treemap.render()

World map

  1. pip install pygal_maps_world

  1. worldmap_chart = pygal.maps.world.World()
  2. worldmap_chart.title = 'Some countries'
  3. worldmap_chart.add('F countries', ['fr', 'fi'])
  4. worldmap_chart.add('M countries', ['ma', 'mc', 'md', 'me', 'mg',
  5.                                    'mk', 'ml', 'mm', 'mn', 'mo',
  6.                                    'mr', 'mt', 'mu', 'mv', 'mw',
  7.                                    'mx', 'my', 'mz'])
  8. worldmap_chart.add('U countries', ['ua', 'ug', 'us', 'uy', 'uz'])
  9. worldmap_chart.render()

  1. supra = pygal.maps.world.SupranationalWorld()
  2. supra.add('Asia', [('asia', 1)])
  3. supra.add('Europe', [('europe', 1)])
  4. supra.add('Africa', [('africa', 1)])
  5. supra.add('North america', [('north_america', 1)])
  6. supra.add('South america', [('south_america', 1)])
  7. supra.add('Oceania', [('oceania', 1)])
  8. supra.add('Antartica', [('antartica', 1)])
  9. supra.render()

等等详细可以参考官网http://www.pygal.org/en/stable/documentation/types/maps/pygal_maps_world.html

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