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pyecharts各种图表实现（超级全）（下）

2022-11-27 143
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简介： 以下默认都是在Jupyter Notebook展示 也可以将每个图代码的最后一行换为 所创建的对象.render('名字.html')转换为html文件就可以查看啦

关系图

nodes = [
    {"name": "结点1", "symbolSize": 1},
    {"name": "结点2", "symbolSize": 2},
    {"name": "结点3", "symbolSize": 3},
    {"name": "结点4", "symbolSize": 4},
    {"name": "结点5", "symbolSize": 5},
    {"name": "结点6", "symbolSize": 6},
    {"name": "结点7", "symbolSize": 7},
    {"name": "结点8", "symbolSize": 8},
]
links = [{'source': '结点1', 'target': '结点2'},
         {'source': '结点1', 'target': '结点3'},
         {'source': '结点1', 'target': '结点4'},
         {'source': '结点2', 'target': '结点1'},
         {'source': '结点3', 'target': '结点4'},
         {'source': '结点3', 'target': '结点5'},
         {'source': '结点3', 'target': '结点6'},
         {'source': '结点4', 'target': '结点1'},
         {'source': '结点4', 'target': '结点2'},
         {'source': '结点4', 'target': '结点7'},
         {'source': '结点4', 'target': '结点8'},
         {'source': '结点5', 'target': '结点1'},
         {'source': '结点5', 'target': '结点4'},
         {'source': '结点5', 'target': '结点6'},
         {'source': '结点5', 'target': '结点7'},
         {'source': '结点5', 'target': '结点8'},
         {'source': '结点6', 'target': '结点1'},
         {'source': '结点6', 'target': '结点7'},
         {'source': '结点6', 'target': '结点8'},
         {'source': '结点7', 'target': '结点1'},
         {'source': '结点7', 'target': '结点2'},
         {'source': '结点7', 'target': '结点8'},
         {'source': '结点8', 'target': '结点1'},
         {'source': '结点8', 'target': '结点2'},
         {'source': '结点8', 'target': '结点3'},
         ]
graph = (
    Graph()
    .add("", nodes, links)
)
graph.render_notebook()

2345_image_file_copy_47.jpg

平行坐标系

# 虚假数据
data = [
    ['一班', 78, 91, 123, 78, 82, 67, "优秀"],
    ['二班', 89, 101, 127, 88, 86, 75, "良好"],
    ['三班', 86, 93, 101, 84, 90, 73, "合格"],
]
parallel = (
    Parallel()
    .add_schema(
        [
            opts.ParallelAxisOpts(
                dim=0,
                name="班级",
                type_="category",
                data=["一班", "二班", "三班"],
            ),
            opts.ParallelAxisOpts(dim=1, name="英语"),
            opts.ParallelAxisOpts(dim=2, name="数学"),
            opts.ParallelAxisOpts(dim=3, name="语文"),
            opts.ParallelAxisOpts(dim=4, name="物理"),
            opts.ParallelAxisOpts(dim=5, name="生物"),
            opts.ParallelAxisOpts(dim=6, name="化学"),
            opts.ParallelAxisOpts(
                dim=7,
                name="评级",
                type_="category",
                data=["优秀", "良好", "合格"],
            ),
        ]
    )
    .add("", data)
)
parallel.render_notebook()

2345_image_file_copy_48.jpg

极坐标系

# 虚假数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data = [123, 153, 89, 107, 98, 23]
polar = (
    Polar()
    .add_schema(
        radiusaxis_opts=opts.RadiusAxisOpts(data=cate, type_="category"),
    )
    .add("", data, type_='bar')
)
polar.render_notebook()

2345_image_file_copy_49.jpg

雷达图

# 虚假数据
data = [
    [78, 91, 123, 78, 82, 67],
    [89, 101, 127, 88, 86, 75],
    [86, 93, 101, 84, 90, 73],
]
radar = (Radar()
         .add_schema(schema=[
             opts.RadarIndicatorItem(name="语文", max_=150),
             opts.RadarIndicatorItem(name="数学", max_=150),
             opts.RadarIndicatorItem(name="英语", max_=150),
             opts.RadarIndicatorItem(name="物理", max_=100),
             opts.RadarIndicatorItem(name="生物", max_=100),
             opts.RadarIndicatorItem(name="化学", max_=100),
         ]
)
    .add('', data)
)
radar.render_notebook()

2345_image_file_copy_50.jpg

旭日图

# 虚假数据
data = [
    {"name": "湖南",
     "children": [
             {"name": "长沙",
              "children": [
                  {"name": "雨花区", "value": 55},
                  {"name": "岳麓区", "value": 34},
                  {"name": "天心区", "value": 144},
              ]},
             {"name": "常德",
              "children": [
                      {"name": "武陵区", "value": 156},
                      {"name": "鼎城区", "value": 134},
              ]},
             {"name": "湘潭", "value": 87},
             {"name": "株洲", "value": 23},
     ],
     },
    {"name": "湖北",
     "children": [
             {"name": "武汉",
              "children": [
                  {"name": "洪山区", "value": 55},
                  {"name": "东湖高新", "value": 78},
                  {"name": "江夏区", "value": 34},
              ]},
             {"name": "鄂州", "value": 67},
             {"name": "襄阳", "value": 34},
     ],
     },
    {"name": "北京", "value": 235}
]
sunburst = (Sunburst()
            .add("", data_pair=data)
            )
sunburst.render_notebook()

2345_image_file_copy_55.jpg

桑基图

# 虚假数据
nodes = [
    {"name": "访问"},
    {"name": "注册"},
    {"name": "付费"},
]
links = [
    {"source": "访问", "target": "注册", "value": 50},
    {"source": "注册", "target": "付费", "value": 30},
]
sankey = (
    Sankey()
    .add("", nodes, links)
)
sankey.render_notebook()

2345_image_file_copy_56.jpg

河流图

# 虚假数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
date_list = ["2020/4/{}".format(i + 1) for i in range(30)]
data = [[day, random.randint(10, 50), c] for day in date_list for c in cate]
river = (
    ThemeRiver()
    .add(
        series_name=cate,
        data=data,
        singleaxis_opts=opts.SingleAxisOpts(type_="time")
    )
)
river.render_notebook()

2345_image_file_copy_57.jpg

词云图

words = [
    ("hey", 230),
    ("jude", 124),
    ("dont", 436),
    ("make", 255),
    ("it", 247),
    ("bad", 244),
    ("Take", 138),
    ("a sad song", 184),
    ("and", 12),
    ("make", 165),
    ("it", 247),
    ("better", 182),
    ("remember", 255),
    ("to", 150),
    ("let", 162),
    ("her", 266),
    ("into", 60),
    ("your", 82),
    ("heart", 173),
    ("then", 365),
    ("you", 360),
    ("can", 282),
    ("start", 273),
    ("make", 265),
]
wc = (
    WordCloud()
    .add("", words)
)
wc.render_notebook()

2345_image_file_copy_58.jpg

表格

from pyecharts.components import Table
table = Table()
headers = ["City name", "Area", "Population", "Annual Rainfall"]
rows = [
    ["Brisbane", 5905, 1857594, 1146.4],
    ["Adelaide", 1295, 1158259, 600.5],
    ["Darwin", 112, 120900, 1714.7],
    ["Hobart", 1357, 205556, 619.5],
    ["Sydney", 2058, 4336374, 1214.8],
    ["Melbourne", 1566, 3806092, 646.9],
    ["Perth", 5386, 1554769, 869.4],
]
table.add(headers, rows)
table.render_notebook()

City name Area Population Annual Rainfall

Brisbane 5905 1857594 1146.4

Adelaide 1295 1158259 600.5

Darwin 112 120900 1714.7

Hobart 1357 205556 619.5

Sydney 2058 4336374 1214.8

Melbourne 1566 3806092 646.9

Perth 5386 1554769 869.4

3D图表

3D散点图

data = [(random.randint(0, 100), random.randint(0, 100), random.randint(0, 100)) for _ in range(100)]
scatter3D = (Scatter3D()
             .add("", data)
             )
scatter3D.render_notebook()

3D折线图

data = []
for t in range(0, 1000):
    x = math.cos(t/10)
    y = math.sin(t/10)
    z = t/10
    data.append([x, y, z])
line3D = (Line3D()
          .add("", data,
               xaxis3d_opts=opts.Axis3DOpts(type_="value"),
               yaxis3d_opts=opts.Axis3DOpts(type_="value"))
          )
line3D.render_notebook()

3D直方图

data = [[i, j, random.randint(0, 100)] for i in range(24) for j in range(7)]
hour_list = [str(i) for i in range(24)]
week_list = ['周日', '周一', '周二', '周三', '周四', '周五', '周六']
bar3D = (
    Bar3D()
    .add(
        "",
        data,
        xaxis3d_opts=opts.Axis3DOpts(hour_list, type_="category"),
        yaxis3d_opts=opts.Axis3DOpts(week_list, type_="category"),
        zaxis3d_opts=opts.Axis3DOpts(type_="value"),
    )
)
bar3D.render_notebook()

3D地图

# 虚假数据
province = [
    '广东',
    '湖北',
    '湖南',
    '四川',
    '重庆',
    '黑龙江',
    '浙江',
    '山西',
    '河北',
    '安徽',
    '河南',
    '山东',
    '西藏']
data = [(i, random.randint(50, 150)) for i in province]
map3d = (
    Map3D()
    .add("", data_pair=data, maptype='china')
)
map3d.render_notebook()
3D地球
from pyecharts.faker import POPULATION
mapglobe = (
    MapGlobe()
    .add_schema()
    .add(
        series_name="",
        maptype="world",
        data_pair=POPULATION[1:]
    )
)
mapglobe.render_notebook()

树型图表

树图

# 虚假数据
data = [
    {"name": "湖南",
     "children": [
             {"name": "长沙",
              "children": [
                  {"name": "雨花区", "value": 55},
                  {"name": "岳麓区", "value": 34},
                  {"name": "天心区", "value": 144},
              ]},
             {"name": "常德",
              "children": [
                      {"name": "武陵区", "value": 156},
                      {"name": "鼎城区", "value": 134},
              ]},
             {"name": "湘潭", "value": 87},
             {"name": "株洲", "value": 23},
     ],
     }
]
tree = (
    Tree()
    .add("", data)
)
tree.render_notebook()

2345_image_file_copy_59.jpg

矩形树图

# 虚假数据
data = [
    {"name": "湖南",
     "children": [
             {"name": "长沙",
              "children": [
                  {"name": "雨花区", "value": 55},
                  {"name": "岳麓区", "value": 34},
                  {"name": "天心区", "value": 144},
              ]},
             {"name": "常德",
              "children": [
                      {"name": "武陵区", "value": 156},
                      {"name": "鼎城区", "value": 134},
              ]},
             {"name": "湘潭", "value": 87},
             {"name": "株洲", "value": 23},
     ],
     },
    {"name": "湖北",
     "children": [
             {"name": "武汉",
              "children": [
                  {"name": "洪山区", "value": 55},
                  {"name": "东湖高新", "value": 78},
                  {"name": "江夏区", "value": 34},
              ]},
             {"name": "鄂州", "value": 67},
             {"name": "襄阳", "value": 34},
     ],
     },
    {"name": "北京", "value": 235}
]
treemap = (
    TreeMap()
    .add("", data)
)
treemap.render_notebook()

2345_image_file_copy_60.jpg

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