pyecharts示例图#

1
from pyecharts.render import make_snapshot
2
from snapshot_selenium import snapshot
3

4
bar = (
5
    Bar()
6
    .add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
7
    .add_yaxis('商家',[5, 20, 36, 10, 75, 90])
8
)
9
make_snapshot(snapshot,bar.render(),'bar.png')

1
from pyecharts.globals import CurrentConfig, NotebookType
2
CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB

1
from pyecharts.charts import Bar
2
bar = Bar()
3
bar.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
4
bar.add_yaxis('商家',[5, 20, 36, 10, 75, 90])
5
bar.load_javascript()

1
bar.render_notebook()

1
from pyecharts.charts import Pie
2
import pyecharts.options as opts
3
from pyecharts.faker import Faker

1
list(zip(Faker.choose(),Faker.values()))

1
[('河马', 139),
2
 ('蟒蛇', 41),
3
 ('老虎', 100),
4
 ('大象', 121),
5
 ('兔子', 80),
6
 ('熊猫', 47),
7
 ('狮子', 147)]

1
c = Pie()
2
c.add('',[list(x) for x in zip(Faker.choose(),Faker.values())])
3
c.render_notebook()

1
c = (
2
    Pie()
3
    .add('数量',[list(x) for x in zip(Faker.choose(),Faker.values())])
4
    .set_colors(['#313695','#4575b4','#74add1','#abd9e9','#e0f3f8','#ffffbf','#fee090',])
5
    .set_global_opts(
6
        title_opts=opts.TitleOpts(title='设置颜色',pos_top=0,pos_left=0),
7
        legend_opts=opts.LegendOpts(type_='scroll',pos_right=0,orient='vertical')
8
    )
9
    .set_series_opts(
10
        label_opts=opts.LabelOpts(formatter="{b}:{c}"),
11
    )
12
)
13
c.render_notebook()

1
v = Faker.choose()
2
v

1
['河马', '蟒蛇', '老虎', '大象', '兔子', '熊猫', '狮子']

1
c = (
2
    Pie()
3
    .add(
4
        '',
5
        [list(i) for i in zip(v,Faker.values())],
6
        radius=['20%','70%'],
7
        center=['20%','50%'],
8
        rosetype='radius',
9
        label_opts=opts.LabelOpts(is_show=False)
10
    )
11
    .add(
12
        '',
13
        [list(i) for i in zip(v,Faker.values())],
14
        radius=['20%','70%'],
15
        center=['80%','50%'],
16
        rosetype='radius',
17
        label_opts=opts.LabelOpts(is_show=True)
18
    )
19
    .set_global_opts(title_opts=opts.TitleOpts(title='南丁格尔玫瑰图'))
20
)
21
c.render_notebook()

1
from pyecharts.charts import Bar

1
c=(
2
    Bar()
3
    .add_xaxis(Faker.choose())
4
    .add_yaxis('商家A',Faker.values())
5
    .add_yaxis('商家B',Faker.values())
6
    .set_global_opts(
7
        title_opts=opts.TitleOpts(title='销量',subtitle='副标题')
8
    )
9
)
10
c.render_notebook()

1
c=(
2
    Bar(
3
        init_opts=opts.InitOpts(
4
            animation_opts=opts.AnimationOpts(
5
                animation_delay=100, #延时动画1000ms
6
                animation_easing='elasticOut' #弹性动画
7
            )
8
        )
9
    )
10
    .add_xaxis(Faker.choose())
11
    .add_yaxis('商家A',Faker.values())
12
    .add_yaxis('商家B',Faker.values())
13
    .set_global_opts(
14
        title_opts=opts.TitleOpts(title='销量',subtitle='副标题'),
15
    )
16
)
17
c.render_notebook()

1
from pyecharts.commons.utils import JsCode

1
c=(
2
    Bar(
3
        init_opts=opts.InitOpts(
4
            bg_color={
5
                'image' :JsCode('img'),
6
            }
7
        )
8
    )
9
    .add_xaxis(Faker.choose())
10
    .add_yaxis('商家A',Faker.values())
11
    .add_yaxis('商家B',Faker.values())
12
    .set_global_opts(
13
        title_opts=opts.TitleOpts(title='销量',subtitle='副标题'),
14
    )
15
)
16

17
#添加js代码
18
c.add_js_funcs(
19
    """
20
    var img = new Image();
21
    img.src = "http://localhost:8888/files/pyecharts/%E3%81%82%E3%81%99%E3%81%8B.jpg?_xsrf=2%7C2b50c939%7Cd7ba3194aadfcc7497a9007df4693a2c%7C1722234893"
22
    """
23
)
24
c.render_notebook()

1
c=(
2
    Bar()
3
    .add_xaxis(Faker.choose())
4
    .add_yaxis('商家A',Faker.values(),stack='abc')
5
    .add_yaxis('商家B',Faker.values(),stack='abc')
6
    .set_series_opts(
7
        label_opts=opts.LabelOpts(is_show=False)
8
    )
9
    .set_global_opts(
10
        title_opts=opts.TitleOpts(title='堆叠柱状图',subtitle='副标题'),
11
        xaxis_opts=opts.AxisOpts(
12
            axislabel_opts=opts.LabelOpts(rotate=45)
13
        ),
14
        #缩放
15
        datazoom_opts=[
16
            opts.DataZoomOpts(),  #x轴拖拉缩放
17
            opts.DataZoomOpts(type_='inside') #滚轮缩放
18
        ]
19

20
    )
21
)
22

23
c.render_notebook()

1
c=(
2
    Bar()
3
    .add_xaxis(Faker.choose())
4
    .add_yaxis('商家A',Faker.values())
5
    .add_yaxis('商家B',Faker.values())
6
    .reversal_axis()  #反转轴
7
    .set_series_opts(
8
        label_opts=opts.LabelOpts(is_show=True,position='right')
9
    )
10
    .set_global_opts(
11
        title_opts=opts.TitleOpts(title='条形图',subtitle='副标题'),
12
    )
13
)
14

15
c.render_notebook()

1
c=(
2
    Bar()
3
    .add_xaxis(Faker.choose())
4
    .add_yaxis('商家A',Faker.values(),gap='0%')
5
    .add_yaxis('商家B',Faker.values(),gap='0%')
6
    .set_global_opts(
7
        title_opts=opts.TitleOpts(title='不同系列柱子之间距离'),
8
    )
9
)
10

11
c.render_notebook()

1
c=(
2
    Bar()
3
    .add_xaxis(Faker.choose())
4
    .add_yaxis('商家A',Faker.values(),category_gap='5%')
5
    .set_global_opts(
6
        title_opts=opts.TitleOpts(title='直方图'),
7
    )
8
)
9

10
c.render_notebook()

1
color_func="""
2
        function (params){
3
            if (params.value > 0 && params.value < 50){
4
                return 'red';
5
            }
6
            else if (params.value > 50 && params.value < 100){
7
                return 'green';
8
            }
9
            return 'blue';
10
        }
11
"""
12

13
c=(
14
    Bar()
15
    .add_xaxis(Faker.choose())
16
    .add_yaxis(
17
        '商家A',Faker.values(),
18
        itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_func)),
19

20
    )
21
    .add_yaxis(
22
        '商家B',Faker.values(),
23
        itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_func)),
24

25
    )
26
    .add_yaxis(
27
        '商家C',Faker.values(),
28
        itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_func)),
29

30
    )
31
    .set_global_opts(
32
        title_opts=opts.TitleOpts(title='直方图'),
33
    )
34
)
35

36
c.render_notebook()

1
from pyecharts.charts import PictorialBar
2
from pyecharts.globals import SymbolType

1
location = ['山西','四川','西藏','北京','上海','内蒙古','云南','黑龙江','广东','福建']
2
values = [13,42,67,81,86,94,166,220,249,262]
3
c = (
4
    PictorialBar()
5
    .add_xaxis(location)
6
    .add_yaxis(
7
        '',
8
        values,
9
        label_opts=opts.LabelOpts(is_show=True),
10
        symbol_repeat='fixed', #重复方式
11
        symbol=SymbolType.ROUND_RECT, #象形符号类型
12
        symbol_size=16, #符号裁剪
13
        is_symbol_clip=True
14
    )
15
    .reversal_axis()
16
    .set_global_opts(
17
        title_opts=opts.TitleOpts(title='象形柱状图'),
18
        xaxis_opts=opts.AxisOpts(is_show=False), #不显示x轴
19
        yaxis_opts=opts.AxisOpts(
20
            axistick_opts=opts.AxisTickOpts(is_show=False), #不显示y轴刻度
21
            axisline_opts=opts.AxisLineOpts(is_show=False)
22
        ),
23
    )
24
    .set_series_opts(
25
        label_opts=opts.LabelOpts(position='right')
26
    )
27
)
28
c.render_notebook()

1
from pyecharts.charts import Radar

1
v1 = [[4300,10000,28000,35000,50000,19000]]
2
v2 = [[5000,14000,28000,31000,42000,21000]]

1
c=(
2
    Radar()
3
    .add_schema(
4
        schema=[
5
            opts.RadarIndicatorItem(name='项目1',max_=6000),
6
            opts.RadarIndicatorItem(name='项目2',max_=16000),
7
            opts.RadarIndicatorItem(name='项目3',max_=30000),
8
            opts.RadarIndicatorItem(name='项目4',max_=38000),
9
            opts.RadarIndicatorItem(name='项目5',max_=60000),
10
            opts.RadarIndicatorItem(name='项目6',max_=22000)
11
        ]
12
    )
13
    .add('数据1',v1,color='red')
14
    .add('数据2',v2)
15
    .set_series_opts(
16
        label_opts=opts.LabelOpts(is_show=False),
17
        linestyle_opts=opts.LineStyleOpts(width=5)
18
    )
19
)
20

21
c.render_notebook()

1
from pyecharts.charts import Line

1
c=(
2
    Line()
3
    .add_xaxis(Faker.choose())
4
    .add_yaxis('商家A',Faker.values())
5
    .add_yaxis('商家B',Faker.values(),is_smooth=True)  #平滑曲线
6
    .set_global_opts(
7
        title_opts=opts.TitleOpts(
8
            title='折线图'
9
        ),
10
        tooltip_opts=opts.TooltipOpts(
11
            trigger='axis'
12
        ),
13
        yaxis_opts=opts.AxisOpts(
14
            splitline_opts=opts.SplitLineOpts(is_show=False),
15
            is_show=True,
16
            axisline_opts=opts.AxisLineOpts(
17
                is_show=True
18
            )
19
        ),
20
        xaxis_opts=opts.AxisOpts(
21
            splitline_opts=opts.SplitLineOpts(is_show=False)
22
        ),
23
    )
24
)
25
c.render_notebook()

1
c=(
2
    Line(init_opts=opts.InitOpts(width='1000px',height='500px'))
3
    .add_xaxis(xaxis_data=Faker.week)
4
    .add_yaxis(
5
        series_name='',
6
        y_axis=[120,200,150,80,70,110,130],
7
        symbol='triangle', #点类型
8
        symbol_size=20,
9
        #线条样式
10
        linestyle_opts=opts.LineStyleOpts(
11
            color='green',
12
            width=2,
13
            type_='dashed',
14

15
        ),
16
        label_opts=opts.LabelOpts(is_show=False),
17
        itemstyle_opts=opts.ItemStyleOpts(
18
            border_width=2,border_color='red',color='blue'
19
        ),
20
        markpoint_opts=opts.MarkPointOpts(
21
            data=[
22
                opts.MarkPointItem(type_='max'),
23
                opts.MarkPointItem(type_='min')
24
            ]
25
        ),
26
        markline_opts=opts.MarkLineOpts(
27
            data=[
28
                opts.MarkLineItem(type_='average')
29
            ],
30
        )
31
    )
32
    .set_global_opts(
33
        yaxis_opts=opts.AxisOpts(
34
            type_='value',
35
            splitline_opts=opts.SplitLineOpts(
36
                is_show=True
37
            )
38
        ),
39
        tooltip_opts=opts.TooltipOpts(trigger='axis')
40
    )
41
)
42

43
c.render_notebook()

1
c=(
2
    Line()
3
    .add_xaxis(Faker.week)
4
    .add_yaxis(
5
        '',
6
        y_axis=[120,130,100,140,90,200,150],
7
        areastyle_opts=opts.AreaStyleOpts(opacity=0.5)
8
    )
9
    .set_global_opts(
10
        title_opts=opts.TitleOpts(title='面积图'),
11
        tooltip_opts=opts.TooltipOpts(trigger='axis'),
12
        xaxis_opts=opts.AxisOpts(type_='category',boundary_gap=False)
13
    )
14
)
15

16
c.render_notebook()

1
c=(
2
    Line()
3
    .add_xaxis(Faker.week,)
4
    .add_yaxis(
5
        '广告',
6
        stack='堆叠',
7
        y_axis=[120,40,100,30,50,60,150],
8
        areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
9
        label_opts=opts.LabelOpts(is_show=False)
10
    )
11
    .add_yaxis(
12
        '销售',
13
        stack='堆叠',
14
        y_axis=[120,40,100,30,50,60,150],
15
        areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
16
        label_opts=opts.LabelOpts(is_show=False)
17
    )
18
    .add_yaxis(
19
        '流量',
20
        stack='堆叠',
21
        y_axis=[120,40,100,30,50,60,150],
22
        areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
23
        label_opts=opts.LabelOpts(is_show=False)
24
    )
25
    .add_yaxis(
26
        '浏览',
27
        stack='堆叠',
28
        y_axis=[120,40,100,30,50,60,150],
29
        areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
30
        label_opts=opts.LabelOpts(is_show=False)
31
    )
32
    .set_global_opts(
33
        title_opts=opts.TitleOpts(title='堆叠面积图'),
34
        xaxis_opts=opts.AxisOpts(type_='category',boundary_gap=False)
35
    )
36
)
37
c.render_notebook()

1
from pyecharts.charts import Scatter

1
data=[
2
    [10.0,8.04],
3
    [8.0,6.95],
4
    [13.0,7.58],
5
    [9.0,8.81],
6
    [11.0,8.33],
7
    [14.0,9.96],
8
    [6.0,7.24],
9
    [4.0,4.26],
10
    [12.0,10.84],
11
    [7.0,4.82],
12
    [5.0,5.68]
13
]

1
data.sort(key=lambda x: x[0])

1
x_data = [d[0] for d in data]
2
y_data = [d[1] for d in data]
3
display(x_data,y_data)

1
[4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0]
2

3

4

5
[4.26, 5.68, 7.24, 4.82, 6.95, 8.81, 8.04, 8.33, 10.84, 7.58, 9.96]

1
c=(
2
    Scatter(
3
        init_opts=opts.InitOpts(width='800px',height='400px')
4
    )
5
    .add_xaxis(xaxis_data=x_data)
6
    .add_yaxis(
7
        '',
8
        y_axis=y_data,
9
        symbol_size=20,
10
        label_opts=opts.LabelOpts(is_show=True,position='top')
11
    )
12
    .set_global_opts(
13
        xaxis_opts=opts.AxisOpts(
14
            min_=2,
15
            type_='value',
16

17
        )
18
    )
19
)
20
c.render_notebook()

1
from pyecharts.charts import EffectScatter
2
from pyecharts.globals import SymbolType

1
c=(
2
    EffectScatter()
3
    .add_xaxis(Faker.choose())
4
    .add_yaxis(
5
        '',
6
        Faker.values(),
7
        symbol=SymbolType.ARROW,
8
        symbol_size=25,
9
        color='red',
10
        label_opts=opts.LabelOpts(position='top')
11
    )
12
    .set_global_opts(
13
        title_opts=opts.TitleOpts(title='涟漪散点图'),
14
    )
15
)
16
c.render_notebook()

1
from pyecharts.charts import HeatMap
2
import random

1
value = [[i,j,random.randint(0,100)] for i in range(24) for j in range(7)]

1
c=(
2
    HeatMap()
3
    .add_xaxis(Faker.clock)
4
    .add_yaxis(
5
        '',
6
        Faker.week,
7
        value,
8
        label_opts=opts.LabelOpts(color='auto'),
9
    )
10
)
11
c.render_notebook()

1
from pyecharts.charts import Calendar
2
import datetime

1
begin = datetime.date(2023,1,1)
2
end = datetime.date(2024,1,1)

1
(end-begin).days

1
365

1
data = [[str(begin+datetime.timedelta(days=i)),random.randint(1000,25000)]
2
        for i in range((end-begin).days)]

1
data[0],data[-1]

1
(['2023-01-01', 4652], ['2023-12-31', 15378])

1
c = (
2
    Calendar(
3
        init_opts=opts.InitOpts(height='220px')
4
    )
5
    .add(
6
        '',
7
        data,
8
        calendar_opts=opts.CalendarOpts(
9
            range_='2023',
10
            daylabel_opts=opts.CalendarDayLabelOpts(name_map='cn'),
11
            monthlabel_opts=opts.CalendarMonthLabelOpts(name_map="cn")
12
        )
13
    )
14
    .set_global_opts(
15
        visualmap_opts=opts.VisualMapOpts(
16
            max_=25000,
17
            min_=1000,
18
            orient="horizontal",
19
            is_piecewise=True,
20
            pos_top="230px",
21
            pos_left="100px",
22
        )
23
    )
24
)
25
c.render_notebook()

1
from pyecharts.charts import Boxplot

1
v1 = [
2
    [850,740,900,1070,930,850,950,980,980,880,1000,980],
3
    [960,940,960,940,880,800,850,880,900,840,830,790],
4
]
5
v2 = [
6
    [890,810,810,820,800,770,760,740,750,760,910,920],
7
    [890,840,780,810,760,810,790,810,820,850,870,870],
8
]

1
c=Boxplot()
2
c.add_xaxis(['demo1','demo2'])
3
c.add_yaxis('A',c.prepare_data(v1))
4
c.add_yaxis('B',c.prepare_data(v2))
5
c.render_notebook()

1
from pyecharts.charts import WordCloud

1
# wordcloud = (
2
#     WordCloud()
3
#     .add("", data_pair = words, word_size_range=[6,60],textstyle_opts=opts.TextStyleOpts(font_family='Microsoft YaHei',font_weight='bold'))
4
#     .set_global_opts(title_opts=opts.TitleOpts(title="《政府工作报告（2021）》新词",title_textstyle_opts = opts.TextStyleOpts(font_size = 25,color="midnightblue")))
5
# )
6
# wordcloud.render_notebook()

1
from pyecharts.charts import Funnel

1
[list(i) for i in zip(Faker.choose(),Faker.values())]

1
[['小米', 22],
2
 ['三星', 81],
3
 ['华为', 54],
4
 ['苹果', 46],
5
 ['魅族', 55],
6
 ['VIVO', 124],
7
 ['OPPO', 40]]

1
c=(
2
    Funnel()
3
    .add('商品',[list(i) for i in zip(Faker.choose(),Faker.values())])
4
    .set_global_opts(
5
        title_opts=opts.TitleOpts(title='漏斗图')
6
    )
7
)
8
c.render_notebook()

1
x_data=['访问','点击','咨询','加购','下单']
2
y_data=[100,80,60,40,20]
3

4
data=[[x_data[i],y_data[i]] for i in range(len(x_data))]

1
c=(
2
    Funnel(
3
        init_opts=opts.InitOpts(width='600px',height='400px')
4
    )
5
    .add(
6
        '漏斗图',
7
        data_pair=data,
8
        gap=5,
9
        tooltip_opts=opts.TooltipOpts(
10
            trigger='item',
11
            formatter='{a}<br/> {b}:{c}'
12
        ),
13
        label_opts=opts.LabelOpts(
14
            is_show=True,
15
            position='inside',
16
            font_size=16
17
        )
18
    )
19
    .set_global_opts(
20
        title_opts=opts.TitleOpts(title='漏斗图')
21
    )
22
)
23
c.render_notebook()

1
from pyecharts.charts import Polar

1
data=[(i,random.randint(1,100)) for i in range(100)]

1
c=(
2
    Polar()
3
    .add(
4
        '极坐标',
5
        data,
6
        type_='scatter',
7
        label_opts=opts.LabelOpts(
8
            is_show=False,
9
        ),
10
        symbol_size=10
11
        # effect_opts=opts.EffectOpts(
12
        #     scale=10
13
        # )
14
    )
15
    .set_global_opts(
16
        title_opts=opts.TitleOpts(
17
            title='极坐标图'
18
        )
19
    )
20
)
21
c.render_notebook()

1
c=(
2
    Polar()
3
    .add_schema(
4
        radiusaxis_opts=opts.RadiusAxisOpts(
5
            data=Faker.week,
6
            type_='category'
7
        ),
8
        angleaxis_opts=opts.AngleAxisOpts(
9
            is_clockwise=True,
10
            max_=10
11
        )
12
    )
13
    .add('商品',[1,2,3,4,3,5,1],type_='bar')
14
)
15
c.render_notebook()

1
c=(
2
    Polar()
3
    .add_schema(
4
        # radiusaxis_opts=opts.RadiusAxisOpts(
5
        #     data=Faker.week,
6
        #     type_='category'
7
        # ),
8
        angleaxis_opts=opts.AngleAxisOpts(
9
            data=Faker.week,
10
            type_='category'
11
        )
12
    )
13
    .add('商品A',[1,2,3,4,3,5,1],type_='bar',stack='abc')
14
    .add('商品B',[2,4,3,5,2,3,1],type_='bar',stack='abc')
15
    .add('商品C',[1,2,3,4,3,5,1],type_='bar',stack='abc')
16
    .set_global_opts(
17
        title_opts=opts.TitleOpts(
18
            title='极坐标图+堆叠柱形图'
19
        )
20
    )
21
)
22
c.render_notebook()

1
from pyecharts.charts import Liquid

1
# c =(
2
#     Liquid()
3
#     .add('',[0.2,0.7]) #0.7水百分之七十，0.2显示数值
4
#     .set_global_opts(title_opts=opts.TitleOpts(title='水球图'))
5
# )
6
# c.render_notebook()

1
from pyecharts.charts import Sankey

1
nodes = [
2
    {'name':'c1'},
3
    {'name':'c2'},
4
    {'name':'c3'},
5
    {'name':'c4'},
6
    {'name':'c5'},
7
    {'name':'c6'},
8
    {'name':'c7'}
9
]
10

11
links=[
12
    {'source':'c1','target':'c2','value':10},
13
    {'source':'c2','target':'c3','value':20},
14
    {'source':'c3','target':'c4','value':30},
15
    {'source':'c5','target':'c6','value':50},
16
    {'source':'c6','target':'c7','value':60},
17
]

1
c=(
2
    Sankey()
3
    .add(
4
        '',
5
        nodes,  #所有节点
6
        links,  #节点之间的链接关系
7
        linestyle_opt=opts.LineStyleOpts(
8
            opacity=0.2, #透明度
9
            curve=0.6,   #曲线幅度
10
            color='red'
11
        ),
12
        # label_opts=opts.LabelOpts(position='right')
13
    )
14
    .set_global_opts(title_opts=opts.TitleOpts(title='桑基图'))
15
)
16
c.render_notebook()