Python数据可视化之Pygal图表类型

将使用Python可视化包Pygal来生成可缩放的矢量图形文件

pygal官方文档：http://www.pygal.org/en/stable/

START

安装pygal

pip install pygal -i https://pypi.tuna.tsinghua.edu.cn/simple

使用的编辑器是Pycharm工具软件，各位可以参考一下

下载完并且安装完Pycharn后新建项目新建python文件

简单的python图表

import pygal

pygal.Bar()(1, 3, 3, 7)(1, 6, 6, 4).render()

生成svg图表

pygal.Bar()(1, 3, 3, 7)(1, 6, 6, 4).render_to_file("simple.svg")

simple.svg

由于markdown不支持svg格式，只好用截图代替

制作多系列图标

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

mul-graph.svg

堆叠图表StackedBar

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

StackedBar.svg

将上面的图表水平HorizontalStackedBar

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

HorizontalStackedBar.svg

添加标签

import pygal
bar_chart = pygal.HorizontalStackedBar()
bar_chart.title = "Remarquable sequences"
bar_chart.x_labels = map(str, range(11))
bar_chart.add('Fibonacci', [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55])
bar_chart.add('Padovan', [1, 1, 1, 2, 2, 3, 4, 5, 7, 9, 12])
bar_chart.render_to_file("HorizontalStackedBar-add-labels.svg")

HorizontalStackedBar-add-labels.svg

图表类型

上面只介绍了Bar，下面就介绍Pygal各种图表类型

Line

Basic

基本的简单线形图

import pygal

line_chart = pygal.Line()
line_chart.title = 'Browser usage evolution (in %)'
line_chart.x_labels = map(str, range(2002, 2013))
line_chart.add('Firefox', [None, None,    0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
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])
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])
line_chart.render_to_file("line-basic.svg")

line-basic.svg

Horizontal Line

相同的图形但水平，范围为0-100。

import pygal

line_chart = pygal.HorizontalLine()
line_chart.title = 'Browser usage evolution (in %)'
line_chart.x_labels = map(str, range(2002, 2013))
line_chart.add('Firefox', [None, None,    0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
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])
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])
line_chart.range = [0, 100]
line_chart.render_to_file("line-horizontal-line.svg")

line-horizontal-line.svg

Stacked

相同的图形但具有堆叠值和填充渲染

import pygal

# fill参数是指是否填充
line_chart = pygal.StackedLine(fill=True)
line_chart.title = 'Browser usage evolution (in %)'
line_chart.x_labels = map(str, range(2002, 2013))
line_chart.add('Firefox', [None, None, 0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
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])
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])
line_chart.render_to_file("line-stacked.svg")

line-stacked.sv

Time

对于与时间相关的图，只需格式化标签或使用xy图表的一种变体

import pygal
from datetime import datetime

# x_label_rotation=20是指x轴标签右旋转20度，可负数，负数向左旋转
date_chart = pygal.Line(x_label_rotation=-20)
date_chart.x_labels = map(lambda d: d.strftime('%Y-%m-%d'), [
 datetime(2013, 1, 2),
 datetime(2013, 1, 12),
 datetime(2013, 2, 2),
 datetime(2013, 2, 22)])
date_chart.add("Visits", [300, 412, 823, 672])
date_chart.render_to_file("line-time.svg")

line-time.svg

Lambda是一个表达式，也可以是一个匿名函数

def sum(x, y):
    return x + y

在Lambda中可以这样写

p = lambda x, y: x + y

Bar

Basic

基本的简单条形图

import pygal

line_chart = pygal.Bar()
line_chart.title = 'Browser usage evolution (in %)'
line_chart.x_labels = map(str, range(2002, 2013))
line_chart.add('Firefox', [None, None, 0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
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])
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])
line_chart.render_to_file("bar-basic.svg")

bar-basic.svg

Stacked

相同的图形但具有堆叠值

import pygal

line_chart = pygal.StackedBar()
line_chart.title = 'Browser usage evolution (in %)'
line_chart.x_labels = map(str, range(2002, 2013))
line_chart.add('Firefox', [None, None, 0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])
line_chart.add('Chrome',  [None, None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])
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])
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])
line_chart.render_to_file("bar-stacked.svg")

bar-stacked.svg

Horizontal

水平条形图

import pygal

line_chart = pygal.HorizontalBar()
line_chart.title = 'Browser usage in February 2012 (in %)'
line_chart.add('IE', 19.5)
line_chart.add('Firefox', 36.6)
line_chart.add('Chrome', 36.3)
line_chart.add('Safari', 4.5)
line_chart.add('Opera', 2.3)
line_chart.render_to_file("bar-horizontal.svg")

bar-horizontal.svg

Histogram

Basic

直方图是特殊条形，它为条形图取3个值：纵坐标高度，横坐标开始和横坐标结束。

import pygal

hist = pygal.Histogram()
hist.add('Wide bars', [(5, 0, 10), (4, 5, 13), (2, 0, 15)])
hist.add('Narrow bars',  [(10, 1, 2), (12, 4, 4.5), (8, 11, 13)])
hist.render_to_file("histogram-basic.svg")

histogram-basic.svg

XY

Basic

基本XY线，绘制余弦函数

import pygal
from math import cos

xy_chart = pygal.XY()
xy_chart.title = 'XY Cosinus'
xy_chart.add('x = cos(y)', [(cos(x / 10.), x / 10.) for x in range(-50, 50, 5)])
xy_chart.add('y = cos(x)', [(x / 10., cos(x / 10.)) for x in range(-50, 50, 5)])
xy_chart.add('x = 1',  [(1, -5), (1, 5)])
xy_chart.add('x = -1', [(-1, -5), (-1, 5)])
xy_chart.add('y = 1',  [(-5, 1), (5, 1)])
xy_chart.add('y = -1', [(-5, -1), (5, -1)])
xy_chart.render_to_file("xy-basic.svg")

xy-basic.svg

Scatter Plot

禁用点和点之间的连线而获得散点图

import pygal

# stroke参数是指是否禁用连线
xy_chart = pygal.XY(stroke=False)
xy_chart.title = 'Correlation'
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)])
xy_chart.add('B', [(.1, .15), (.12, .23), (.4, .3), (.6, .4), (.21, .21), (.5, .3), (.6, .8), (.7, .8)])
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)])
xy_chart.render_to_file("xy-scatter-plot.svg")

xy-scatter-plot.svg

Dates

DateTime

import pygal
from datetime import datetime

# truncate_label=-1是指显示到最后一个元素
# x_value_formatter指X轴的值的格式化
datetimeline = pygal.DateTimeLine(
    x_label_rotation=35, truncate_label=-1,
    x_value_formatter=lambda dt: dt.strftime('%d, %b %Y at %I:%M:%S %p')
)
datetimeline.add("Serie", [
    (datetime(2013, 1, 2, 12, 0), 300),
    (datetime(2013, 1, 12, 14, 30, 45), 412),
    (datetime(2013, 2, 2, 6), 823),
    (datetime(2013, 2, 22, 9, 45), 672)
])
datetimeline.render_to_file("dates-datetime.svg")

dates-datetime.svg

Date

import pygal
from datetime import date

dateline = pygal.DateLine(x_label_rotation=25)
dateline.x_labels = [
    date(2013, 1, 1),
    date(2013, 7, 1),
    date(2014, 1, 1),
    date(2014, 7, 1),
    date(2015, 1, 1),
    date(2015, 7, 1)
]
dateline.add("Serie", [
    (date(2013, 1, 2), 213),
    (date(2013, 8, 2), 281),
    (date(2014, 12, 7), 198),
    (date(2015, 3, 21), 120)
])
dateline.render_to_file("dates-date.svg")

dates-date.svg

Time

import pygal
from datetime import time

dateline = pygal.TimeLine(x_label_rotation=25)
dateline.add("Serie", [
  (time(), 0),
  (time(6), 5),
  (time(8, 30), 12),
  (time(11, 59, 59), 4),
  (time(18), 10),
  (time(23, 30), -1),
])
dateline.render_to_file("dates-time.svg")

dates-time.svg

TimeDelta

import pygal
from datetime import timedelta

dateline = pygal.TimeDeltaLine(x_label_rotation=25)
dateline.add("Serie", [
  (timedelta(), 0),
  (timedelta(seconds=6), 5),
  (timedelta(minutes=11, seconds=59), 4),
  (timedelta(days=3, microseconds=30), 12),
  (timedelta(weeks=1), 10),
])
dateline.render_to_file("dates-timedelta.svg")

dates-timedelta.svg

Pie

Basic

简单的饼图

import pygal

pie_chart = pygal.Pie()
pie_chart.title = 'Browser usage in February 2012 (in %)'
pie_chart.add('IE', 19.5)
pie_chart.add('Firefox', 36.6)
pie_chart.add('Chrome', 36.3)
pie_chart.add('Safari', 4.5)
pie_chart.add('Opera', 2.3)
pie_chart.render_to_file("pie-basic.svg")

image

Multi-series pie

相同的饼图，但分为子类别

import pygal

pie_chart = pygal.Pie()
pie_chart.title = 'Browser usage by version in February 2012 (in %)'
pie_chart.add('IE', [5.7, 10.2, 2.6, 1])
pie_chart.add('Firefox', [.6, 16.8, 7.4, 2.2, 1.2, 1, 1, 1.1, 4.3, 1])
pie_chart.add('Chrome', [.3, .9, 17.1, 15.3, .6, .5, 1.6])
pie_chart.add('Safari', [4.4, .1])
pie_chart.add('Opera', [.1, 1.6, .1, .5])
pie_chart.render_to_file("pie-multi-series.svg")

pie-multi-series.svg

Donut

可以指定内半径来获得甜甜圈

import pygal

# inner_radius内圆半径0和1之间
pie_chart = pygal.Pie(inner_radius=.5)
pie_chart.title = 'Browser usage in February 2012 (in %)'
pie_chart.add('IE', 19.5)
pie_chart.add('Firefox', 36.6)
pie_chart.add('Chrome', 36.3)
pie_chart.add('Safari', 4.5)
pie_chart.add('Opera', 2.3)
pie_chart.render_to_file("pie-donut.svg")

pie-donut.svg

Half pie

import pygal

# half_pie参数是指是否为半圆
pie_chart = pygal.Pie(half_pie=True)
pie_chart.title = 'Browser usage in February 2012 (in %)'
pie_chart.add('IE', 19.5)
pie_chart.add('Firefox', 36.6)
pie_chart.add('Chrome', 36.3)
pie_chart.add('Safari', 4.5)
pie_chart.add('Opera', 2.3)
pie_chart.render_to_file("pie-half.svg")

pie-half.svg

Radar

Basic

简单的Kiviat图

import pygal

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

或者也可以

import pygal

radar_chart = pygal.Radar(title='V8 benchmark results', width=600, height=500)
radar_chart.title = 'V8 benchmark results'
radar_chart.width = 600
radar_chart.height = 500
radar_chart.x_labels = ['Richards', 'DeltaBlue', 'Crypto', 'RayTrace', 'EarleyBoyer', 'RegExp', 'Splay', 'NavierStokes']
radar_chart.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])
radar_chart.add('Firefox', [7473, 8099, 11700, 2651, 6361, 1044, 3797, 9450])
radar_chart.add('Opera', [3472, 2933, 4203, 5229, 5810, 1828, 9013, 4669])
radar_chart.add('IE', [43, 41, 59, 79, 144, 136, 34, 102])
radar_chart.render_to_file("radar-basic.svg")

radar-basic.svg

Box

Extremes (default)

import pygal

box_plot = pygal.Box()
box_plot.title = 'V8 benchmark results'
box_plot.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])
box_plot.add('Firefox', [7473, 8099, 11700, 2651, 6361, 1044, 3797, 9450])
box_plot.add('Opera', [3472, 2933, 4203, 5229, 5810, 1828, 9013, 4669])
box_plot.add('IE', [43, 41, 59, 79, 144, 136, 34, 102])
box_plot.render_to_file("box-extremes.svg")

box-extremes.svg

1.5 interquartile range

import pygal

box_plot = pygal.Box(box_mode="1.5IQR")
box_plot.title = 'V8 benchmark results'
box_plot.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])
box_plot.add('Firefox', [7473, 8099, 11700, 2651, 6361, 1044, 3797, 9450])
box_plot.add('Opera', [3472, 2933, 4203, 5229, 5810, 1828, 9013, 4669])
box_plot.add('IE', [43, 41, 59, 79, 144, 136, 34, 102])
box_plot.render_to_file("box-interquartile.svg")

box-interquartile.svg

Dot

Basic

import pygal

dot_chart = pygal.Dot(x_label_rotation=30)
dot_chart.title = 'V8 benchmark results'
dot_chart.x_labels = ['Richards', 'DeltaBlue', 'Crypto', 'RayTrace', 'EarleyBoyer', 'RegExp', 'Splay', 'NavierStokes']
dot_chart.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])
dot_chart.add('Firefox', [7473, 8099, 11700, 2651, 6361, 1044, 3797, 9450])
dot_chart.add('Opera', [3472, 2933, 4203, 5229, 5810, 1828, 9013, 4669])
dot_chart.add('IE', [43, 41, 59, 79, 144, 136, 34, 102])
dot_chart.render_to_file('dot-basic.svg')

dot-basic.svg

Negative

支持负数

import pygal

dot_chart = pygal.Dot(x_label_rotation=30)
dot_chart.add('Normal', [10, 50, 76, 80, 25])
dot_chart.add('With negatives', [0, -34, -29, 39, -75])
dot_chart.render_to_file('dot-negative.svg')

dot-negative.svg

Funnel

Basic

漏斗图

import pygal

funnel_chart = pygal.Funnel()
funnel_chart.title = 'V8 benchmark results'
funnel_chart.x_labels = ['Richards', 'DeltaBlue', 'Crypto', 'RayTrace', 'EarleyBoyer', 'RegExp', 'Splay', 'NavierStokes']
funnel_chart.add('Opera', [3472, 2933, 4203, 5229, 5810, 1828, 9013, 4669])
funnel_chart.add('Firefox', [7473, 8099, 11700, 2651, 6361, 1044, 3797, 9450])
funnel_chart.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])
funnel_chart.render_to_file('funnel-basic.svg')

funnel-basic.svg

SolidGauge

import pygal

gauge = pygal.SolidGauge(inner_radius=0.70)
# 百分格式
percent_formatter = lambda x: '{:.10g}%'.format(x)
# 美元格式
dollar_formatter = lambda x: '{:.10g}$'.format(x)
gauge.value_formatter = percent_formatter

gauge.add('Series 1', [{'value': 225000, 'max_value': 1275000}],
          formatter=dollar_formatter)
gauge.add('Series 2', [{'value': 110, 'max_value': 100}])
gauge.add('Series 3', [{'value': 3}])
gauge.add(
    'Series 4', [
        {'value': 51, 'max_value': 100},
        {'value': 12, 'max_value': 100}])
gauge.add('Series 5', [{'value': 79, 'max_value': 100}])
gauge.add('Series 6', 99)
gauge.add('Series 7', [{'value': 100, 'max_value': 100}])
gauge.render_to_file('solidgauge-normal.svg')

solidgauge-normal.svg

Half

import pygal

gauge = pygal.SolidGauge(
    half_pie=True, inner_radius=0.70,
    style=pygal.style.styles['default'](value_font_size=10))

percent_formatter = lambda x: '{:.10g}%'.format(x)
dollar_formatter = lambda x: '{:.10g}$'.format(x)
gauge.value_formatter = percent_formatter

gauge.add('Series 1', [{'value': 225000, 'max_value': 1275000}],
          formatter=dollar_formatter)
gauge.add('Series 2', [{'value': 110, 'max_value': 100}])
gauge.add('Series 3', [{'value': 3}])
gauge.add(
    'Series 4', [
        {'value': 51, 'max_value': 100},
        {'value': 12, 'max_value': 100}])
gauge.add('Series 5', [{'value': 79, 'max_value': 100}])
gauge.add('Series 6', 99)
gauge.add('Series 7', [{'value': 100, 'max_value': 100}])
gauge.render_to_file('solidgauge-half.svg')

solidgauge-half.svg

Gauge

Basic

仪表图

import pygal

gauge_chart = pygal.Gauge(human_readable=True)
gauge_chart.title = 'DeltaBlue V8 benchmark results'
gauge_chart.range = [0, 10000]
gauge_chart.add('Chrome', 8212)
gauge_chart.add('Firefox', 8099)
gauge_chart.add('Opera', 2933)
gauge_chart.add('IE', 41)
gauge_chart.render_to_file('gauge-basic.svg')

gauge-basic.svg

Pyramid

Basic

人口金字塔

import pygal

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),
   (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),
   (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),
   (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),
   (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),
   (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),
   (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),
   (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)]

types = ['Males single', 'Females single',
         'Males married', 'Females married',
         'Males widowed', 'Females widowed',
         'Males divorced', 'Females divorced']

pyramid_chart = pygal.Pyramid(human_readable=True, legend_at_bottom=True)
pyramid_chart.title = 'England population by age in 2010 (source: ons.gov.uk)'
pyramid_chart.x_labels = map(lambda x: str(x) if not x % 5 else '', range(90))
for type, age in zip(types, ages):
    pyramid_chart.add(type, age)
pyramid_chart.render_to_file('pyramid-basic.svg')

pyramid-basic.svg

Treemap

Basic

树形图

import pygal

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

treemap-basic.svg

Maps

World map

安装

pip install pygal_maps_world

Countries

import pygal

worldmap_chart = pygal.maps.world.World()
worldmap_chart.title = 'Some countries'
worldmap_chart.add('C countries', ['cn', 'ca', 'ch', 'cg'])
worldmap_chart.add('F countries', ['fr', 'fi'])
worldmap_chart.add('M countries', ['ma', 'mc', 'md', 'me', 'mg',
                                   'mk', 'ml', 'mm', 'mn', 'mo',
                                   'mr', 'mt', 'mu', 'mv', 'mw',
                                   'mx', 'my', 'mz'])
worldmap_chart.add('U countries', ['ua', 'ug', 'us', 'uy', 'uz'])
worldmap_chart.render_to_file('world-map-countries.svg')

world-map-countries.svg

Continents

访问各大洲

import pygal

supra = pygal.maps.world.SupranationalWorld()
supra.add('Asia', [('asia', 1)])
supra.add('Europe', [('europe', 1)])
supra.add('Africa', [('africa', 1)])
supra.add('North america', [('north_america', 1)])
supra.add('South america', [('south_america', 1)])
supra.add('Oceania', [('oceania', 1)])
supra.add('Antartica', [('antartica', 1)])
supra.render_to_file('world-map-continents.svg')

world-map-continents.svg

国家和七大洲代码列表：http://pygal.org/en/stable/documentation/types/maps/pygal_maps_world.html#coutry-code-list

END

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