pyecharts教程-Linux大棚

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2024年1月11日发(作者：java常用工具类下载)

这篇教程简单介绍一下pyecharts（echarts提供给python的接口包）简单使用，感兴趣的可以了解一下。

一．安装

pyecharts兼容和，直接输入安装命令”pip install pyecharts”就行。

二．使用

1. 柱状图

from pyecharts import Bar

bar =Bar("我的第一个图表", "这里是副标题")

("服装", ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"], [5, 20,

36, 10, 75, 90])

()

程序截图：

2. 水平柱状图

from pyecharts import Bar

bar =Bar("x 轴和 y 轴交换")

attr=["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]

v1=[5, 20, 36, 10, 75, 90]

v2=[10, 25, 16, 18, 55, 62]

("商家A", attr, v1)

("商家B", attr, v2, is_convert=True)

()

程序截图：

3. 饼状图

from pyecharts import Pie

pie=Pie('饼状图')

('',['优秀','良好','及格'],[12,20,3],is_label_show=True)

()

程序截图：

4. 带有涟漪特效动画的散点图

from pyecharts import EffectScatter

es =EffectScatter("动态散点图各种图形示例")

("", [10], [10], symbol_size=20, effect_scale=, effect_period=3,

symbol="pin")

("", [20], [20], symbol_size=12, effect_scale=,

effect_period=4,symbol="rect")

("", [30], [30], symbol_size=30, effect_scale=,

effect_period=5,symbol="roundRect")

("", [40], [40], symbol_size=10, effect_scale=,

effect_brushtype='fill',symbol="diamond")

("", [50], [50], symbol_size=16, effect_scale=,

effect_period=3,symbol="arrow")

("", [60], [60], symbol_size=6, effect_scale=,

effect_period=3,symbol="triangle")

()

程序截图：

5. 漏斗图

from pyecharts import Funnel

attr =["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]

value =[20, 40, 60, 80, 100, 120]

funnel =Funnel("漏斗图示例")

("商品", attr, value, is_label_show=True, label_pos="inside",

label_text_color="#fff")

()

程序截图：

6. 仪表盘

from pyecharts import Gauge

gauge =Gauge("仪表盘示例")

("业务指标", "完成率",

()

程序截图：

7. 地理坐标系图

程序一：

from pyecharts import Geo

data =[ ("海门", 9),("鄂尔多斯", 12),("招远", 12),("舟山", 12),("齐齐哈尔", 14),("盐城", 15), ("赤峰", 16),("青岛", 18),

("乳山", 18),("金昌", 19),("泉州", 21),("莱西", 21), ("日照",

21),("胶南", 22),("南通", 23),("拉萨", 24),("云浮", 24),("梅州", 25)]

geo =Geo("全国主要城市空气质量", "data from ", title_color="#fff",

title_pos="center",width=800, height=600, background_color='#404a59')

attr, value =(data)

("", attr, value, visual_range=[0, 200], visual_text_color="#fff",

symbol_size=15, is_visualmap=True)

()

程序运行截图：

程序二：

from pyecharts import Geo

data =[("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14), ("盐城", 15)]

geo =Geo("全国主要城市空气质量", "data from ", title_color="#fff",

title_pos="center", width=800, height=500, background_color='#404a59')

attr, value =(data)

("", attr, value, type="effectScatter", is_random=True, effect_scale=5)

()

程序截图：

8. 关系图

程序一：

from pyecharts import Graph

nodes =[{"name": "结点1", "symbolSize": 10}, {"name": "结点2",

"symbolSize": 20}, {"name": "结点3", "symbolSize": 30}, {"name": "结点4", "symbolSize": 40},

{"name": "结点5", "symbolSize": 50}, {"name": "结点6",

"symbolSize": 40}, {"name": "结点7", "symbolSize": 30}, {"name": "结点8", "symbolSize": 20}]

links =[]

for i in nodes:

for j in nodes:

({"source": ('name'), "target": ('name')})

graph =Graph("关系图-环形布局示例")

("", nodes, links, is_label_show=True, repulsion=8000,

layout='circular', label_text_color=None)

()

程序截图：

9. 折线/面积图

程序一：

from pyecharts import Line

attr =["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]

v1 =[5, 20, 36, 10, 10, 100]

v2 =[55, 60, 16, 20, 15, 80]

line =Line("折线图-阶梯图示例")

("商家A", attr, v1, is_step=True, is_label_show=True)

()

程序截图：

程序二：

from pyecharts import Line

attr =["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]

v1 =[5, 20, 36, 10, 10, 100]

v2 =[55, 60, 16, 20, 15, 80]

line =Line("折线图-面积图示例")

("商家A", attr, v1, is_fill=True, line_opacity=, area_opacity=,

symbol=None)

("商家B", attr, v2, is_fill=True, area_color='#000', area_opacity=,

is_smooth=True)

()

程序截图：

10. 水球图

程序一：

from pyecharts import Liquid

liquid =Liquid("水球图示例")

("Liquid", [, , , ], is_liquid_outline_show=False)

()

程序截图：

程序二：

from pyecharts import Liquid

liquid =Liquid("水球图示例")

("Liquid", [, , , ], is_liquid_animation=False, shape='diamond')

()

程序截图：

11. 地图

程序一：

from pyecharts import Map

value =[155, 10, 66, 78, 33, 80, 190, 53, ]

attr =["福建", "山东", "北京", "上海", "甘肃", "新疆", "河南", "广西", "西藏"]

map=Map("Map 结合 VisualMap 示例", width=800, height=600)

("", attr, value, maptype='china', is_visualmap=True,

visual_text_color='#000')

()

程序截图：

程序二：

from pyecharts import Map

value =[20, 190, 253, 77, 65]

attr =['汕头市', '汕尾市', '揭阳市', '阳江市', '肇庆市']

map=Map("广东地图示例", width=800, height=500)

("", attr, value, maptype='广东', is_visualmap=True,

visual_text_color='#000')

()

程序截图：

12. 平行坐标系

from pyecharts import Parallel

c_schema =[ {"dim": 0, "name": "data"}, {"dim": 1, "name": "AQI"}, {"dim":

2, "name": ""}, {"dim": 3, "name": "PM10"},

{"dim": 4, "name": "CO"}, {"dim": 5, "name": "NO2"}, {"dim":

6, "name": "CO2"},

{"dim": 7, "name": "等级", "type": "category", "data": ['优', '良', '轻度污染', '中度污染', '重度污染', '严重污染']}]

data =[ [1, 91, 45, 125, , 34, 23, "良"], [2, 65, 27, 78, , 45, 29, "良"], [3, 83, 60, 84, , 73, 27, "良"], [4, 109, 81, 121, , 68, 51, "轻度污染"],

[5, 106, 77, 114, , 55, 51, "轻度污染"], [6, 109, 81, 121, , 68,

51, "轻度污染"], [7, 106, 77, 114, , 55, 51, "轻度污染"], [8, 89, 65, 78, ,

51, 26, "良"],

[9, 53, 33, 47, , 50, 17, "良"], [10, 80, 55, 80, , 75, 24, "良"], [11, 117, 81, 124, , 45, 24, "轻度污染"], [12, 99, 71, 142, , 62,

42, "良"],

[13, 95, 69, 130, , 74, 50, "良"], [14, 116, 87, 131, , 84, 40,

"轻度污染"]]

parallel =Parallel("平行坐标系-用户自定义指示器")

(c_schema=c_schema)

("parallel", data)

()

程序截图：

13. 极坐标系图

程序一：

from pyecharts import Polar

radius =['周一', '周二', '周三', '周四', '周五', '周六', '周日']

polar =Polar("极坐标系-堆叠柱状图示例", width=1200, height=600)

("A", [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type='barRadius',

is_stack=True)

("B", [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type='barRadius',

is_stack=True)

("C", [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type='barRadius',

is_stack=True)

()

程序截图：

程序二：

from pyecharts import Polar

radius =['周一', '周二', '周三', '周四', '周五', '周六', '周日']

polar =Polar("极坐标系-堆叠柱状图示例", width=1200, height=600)

("", [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type='barAngle',

is_stack=True)

("", [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type='barAngle',

is_stack=True)

("", [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type='barAngle',

is_stack=True)

()

程序截图：

14. 雷达图

程序一：

from pyecharts import Radar

schema =[ ("销售", 6500), ("管理", 16000), ("信息技术", 30000), ("客服", 38000), ("研发", 52000), ("市场", 25000)]

v1 =[[4300, 10000, 28000, 35000, 50000, 19000]]

v2 =[[5000, 14000, 28000, 31000, 42000, 21000]]

radar =Radar()

(schema)

("预算分配", v1, is_splitline=True, is_axisline_show=True)

("实际开销", v2, label_color=["#4e79a7"], is_area_show=False)

()

程序截图：

程序二：

from pyecharts import Radar

value_bj =[ [55, 9, 56, , 18, 6, 1], [25, 11, 21, , 34, 9, 2], [56, 7,

63, , 14, 5, 3], [33, 7, 29, , 16, 6, 4]]

value_sh =[ [91, 45, 125, , 34, 23, 1], [65, 27, 78, , 45, 29, 2], [83,

60, 84, , 73, 27, 3], [109, 81, 121, , 68, 51, 4]]

c_schema=[{"name": "AQI", "max": 300, "min": 5}, {"name": "", "max": 250,

"min": 20}, {"name": "PM10", "max": 300, "min": 5},

{"name": "CO", "max": 5}, {"name": "NO2", "max": 200}, {"name":

"SO2", "max": 100}]

radar =Radar()

(c_schema=c_schema, shape='circle')

("北京", value_bj, item_color="#f9713c", symbol=None)

("上海", value_sh, item_color="#b3e4a1", symbol=None)

()

程序截图：

15. 散点图

from pyecharts import Scatter

v1 =[10, 20, 30, 40, 50, 60]

v2 =[10, 20, 30, 40, 50, 60]

scatter =Scatter("散点图示例")

("A", v1, v2)

("B", v1[::-1], v2)

()

程序截图：

16. 词云图

from pyecharts import WordCloud

name =['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)

("", name, value, word_size_range=[20, 100])

()

程序截图：

17. 更多图

程序一：

import math

from pyecharts import Polar

data =[]

for i in range(101):

theta =i /100*360

r =5*(1+(theta /180*)

([r, theta])

hour =[i for i in range(1, 25)]

polar =Polar("极坐标系示例", width=800, height=500)

("Love", data, angle_data=hour, boundary_gap=False,start_angle=0)

()

运行截图：

程序二：

import math

from pyecharts import Polar

data =[]

for i in range(361):

t =i /180*

r =(2*t) *(2*t)

([r, i])

polar =Polar("极坐标系示例", width=1200, height=600)

("Color-Flower", data, start_angle=0, symbol=None, axis_range=[0, None],

area_color="#f71f24", area_opacity=

()

程序截图：

程序三：

import random

from pyecharts import Pie

attr =['A', 'B', 'C', 'D', 'E', 'F']

pie =Pie("饼图示例", width=1000, height=600)

("", attr, [(0, 100) for _ in range(6)], radius=[50, 55], center=[25,

50],is_random=True,is_label_show=True)

("", attr, [(20, 100) for _ in range(6)], radius=[0, 45], center=[25,

50],rosetype='area',is_label_show=True)

("", attr, [(0, 100) for _ in range(6)], radius=[50, 55], center=[65,

50],is_random=True,is_label_show=True)

("", attr, [(20, 100) for _ in range(6)], radius=[0, 45], center=[65,

50],rosetype='radius',is_label_show=True)

()

程序截图：

程序四：

from pyecharts import Bar

attr =["{}月".format(i) for i in range(1, 13)]

v1 =[, , , , , , , , , , , ]

v2 =[, , , , , , , , , , , ]

bar =Bar("柱状图示例")

("蒸发量", attr, v1, mark_line=["average"], mark_point=["max", "min"])

("降水量", attr, v2, mark_line=["average"], mark_point=["max", "min"])

()

程序截图：

程序五：

from pyecharts import Pie

pie =Pie('各类电影中"好片"所占的比例', "数据来着豆瓣",

title_pos='center')

("", ["剧情", ""], [25, 75], center=[10, 30], radius=[18, 24],

label_pos='center', is_label_show=True, label_text_color=None, )

("", ["奇幻", ""], [24, 76], center=[30, 30], radius=[18, 24],

label_pos='center', is_label_show=True, label_text_color=None,

legend_pos='left')

("", ["爱情", ""], [14, 86], center=[50, 30], radius=[18, 24],