示例#1
0
文件: charts.py 项目: analylx/learn
          radius_data=radius,
          type='barRadius',
          is_stack=True)
polar.show_config()
polar.render(path='./data/03-04极坐标.html')

# 雷达图
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()
radar.config(schema)
radar.add("预算分配", v1, is_splitline=True, is_axisline_show=True)
radar.add("实际开销", v2, label_color=["#4e79a7"], is_area_show=False)
radar.show_config()
radar.render(path='./data/03-05雷达图.html')
"""
#支持保持成各种格式,但是会有问题
bar = Bar("我的第一个图表", "这里是副标题")
bar.add("服装", ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"], [5, 20, 36, 10, 75, 90])
# bar.print_echarts_options()
bar.render(path='snapshot.html')
bar.render(path='snapshot.png')
bar.render(path='snapshot.pdf')
"""

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',
示例#2
0
def test_radar():

    # radar_0
    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("雷达图示例")
    radar.config(schema)
    radar.add("预算分配", v1, is_splitline=True, is_axisline_show=True)
    radar.add("实际开销", v2, label_color=["#4e79a7"], is_area_show=False)
    radar.show_config()
    radar.render()

    # radar_1
    value_bj = [[55, 9, 56, 0.46, 18, 6, 1], [25, 11, 21, 0.65, 34, 9, 2],
                [56, 7, 63, 0.3, 14, 5, 3], [33, 7, 29, 0.33, 16, 6, 4],
                [42, 24, 44, 0.76, 40, 16, 5], [82, 58, 90, 1.77, 68, 33, 6],
                [74, 49, 77, 1.46, 48, 27, 7], [78, 55, 80, 1.29, 59, 29, 8],
                [267, 216, 280, 4.8, 108, 64, 9],
                [185, 127, 216, 2.52, 61, 27, 10],
                [39, 19, 38, 0.57, 31, 15, 11], [41, 11, 40, 0.43, 21, 7, 12],
                [64, 38, 74, 1.04, 46, 22, 13],
                [108, 79, 120, 1.7, 75, 41, 14],
                [108, 63, 116, 1.48, 44, 26, 15], [33, 6, 29, 0.34, 13, 5, 16],
                [94, 66, 110, 1.54, 62, 31, 17],
                [186, 142, 192, 3.88, 93, 79, 18],
                [57, 31, 54, 0.96, 32, 14, 19], [22, 8, 17, 0.48, 23, 10, 20],
                [39, 15, 36, 0.61, 29, 13,
                 21], [94, 69, 114, 2.08, 73, 39, 22],
                [99, 73, 110, 2.43, 76, 48, 23], [31, 12, 30, 0.5, 32, 16, 24],
                [42, 27, 43, 1, 53, 22, 25], [154, 117, 157, 3.05, 92, 58, 26],
                [234, 185, 230, 4.09, 123, 69, 27],
                [160, 120, 186, 2.77, 91, 50, 28],
                [134, 96, 165, 2.76, 83, 41,
                 29], [52, 24, 60, 1.03, 50, 21, 30],
                [46, 5, 49, 0.28, 10, 6, 31]]
    value_sh = [[91, 45, 125, 0.82, 34, 23, 1], [65, 27, 78, 0.86, 45, 29, 2],
                [83, 60, 84, 1.09, 73, 27, 3], [109, 81, 121, 1.28, 68, 51, 4],
                [106, 77, 114, 1.07, 55, 51,
                 5], [109, 81, 121, 1.28, 68, 51, 6],
                [106, 77, 114, 1.07, 55, 51, 7], [89, 65, 78, 0.86, 51, 26, 8],
                [53, 33, 47, 0.64, 50, 17, 9], [80, 55, 80, 1.01, 75, 24, 10],
                [117, 81, 124, 1.03, 45, 24,
                 11], [99, 71, 142, 1.1, 62, 42, 12],
                [95, 69, 130, 1.28, 74, 50, 13],
                [116, 87, 131, 1.47, 84, 40, 14],
                [108, 80, 121, 1.3, 85, 37, 15],
                [134, 83, 167, 1.16, 57, 43, 16],
                [79, 43, 107, 1.05, 59, 37,
                 17], [71, 46, 89, 0.86, 64, 25, 18],
                [97, 71, 113, 1.17, 88, 31, 19],
                [84, 57, 91, 0.85, 55, 31, 20], [87, 63, 101, 0.9, 56, 41, 21],
                [104, 77, 119, 1.09, 73, 48, 22], [87, 62, 100, 1, 72, 28, 23],
                [168, 128, 172, 1.49, 97, 56, 24],
                [65, 45, 51, 0.74, 39, 17, 25], [39, 24, 38, 0.61, 47, 17, 26],
                [39, 24, 39, 0.59, 50, 19, 27], [93, 68, 96, 1.05, 79, 29, 28],
                [188, 143, 197, 1.66, 99, 51, 29],
                [174, 131, 174, 1.55, 108, 50, 30],
                [187, 143, 201, 1.39, 89, 53, 31]]
    c_schema = [{
        "name": "AQI",
        "max": 300,
        "min": 5
    }, {
        "name": "PM2.5",
        "max": 250,
        "min": 20
    }, {
        "name": "PM10",
        "max": 300,
        "min": 5
    }, {
        "name": "CO",
        "max": 5
    }, {
        "name": "NO2",
        "max": 200
    }, {
        "name": "SO2",
        "max": 100
    }]

    radar = Radar("雷达图示例")
    radar.config(c_schema=c_schema, shape='circle')
    radar.add("北京", value_bj, item_color="#f9713c", symbol=None)
    radar.add("上海", value_sh, item_color="#b3e4a1", symbol=None)
    radar.show_config()
    radar.render()
示例#3
0
def test_radar():

    # radar_0
    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("雷达图示例")
    radar.config(schema)
    radar.add("预算分配", v1, is_splitline=True, is_axisline_show=True)
    radar.add("实际开销", v2, label_color=["#4e79a7"], is_area_show=False, legend_selectedmode='single')
    radar.show_config()
    radar.render()

    # radar_1
    value_bj = [
        [55, 9, 56, 0.46, 18, 6, 1],
        [25, 11, 21, 0.65, 34, 9, 2],
        [56, 7, 63, 0.3, 14, 5, 3],
        [33, 7, 29, 0.33, 16, 6, 4],
        [42, 24, 44, 0.76, 40, 16, 5],
        [82, 58, 90, 1.77, 68, 33, 6],
        [74, 49, 77, 1.46, 48, 27, 7],
        [78, 55, 80, 1.29, 59, 29, 8],
        [267, 216, 280, 4.8, 108, 64, 9],
        [185, 127, 216, 2.52, 61, 27, 10],
        [39, 19, 38, 0.57, 31, 15, 11],
        [41, 11, 40, 0.43, 21, 7, 12],
        [64, 38, 74, 1.04, 46, 22, 13],
        [108, 79, 120, 1.7, 75, 41, 14],
        [108, 63, 116, 1.48, 44, 26, 15],
        [33, 6, 29, 0.34, 13, 5, 16],
        [94, 66, 110, 1.54, 62, 31, 17],
        [186, 142, 192, 3.88, 93, 79, 18],
        [57, 31, 54, 0.96, 32, 14, 19],
        [22, 8, 17, 0.48, 23, 10, 20],
        [39, 15, 36, 0.61, 29, 13, 21],
        [94, 69, 114, 2.08, 73, 39, 22],
        [99, 73, 110, 2.43, 76, 48, 23],
        [31, 12, 30, 0.5, 32, 16, 24],
        [42, 27, 43, 1, 53, 22, 25],
        [154, 117, 157, 3.05, 92, 58, 26],
        [234, 185, 230, 4.09, 123, 69, 27],
        [160, 120, 186, 2.77, 91, 50, 28],
        [134, 96, 165, 2.76, 83, 41, 29],
        [52, 24, 60, 1.03, 50, 21, 30],
        [46, 5, 49, 0.28, 10, 6, 31]
        ]
    value_sh = [
        [91, 45, 125, 0.82, 34, 23, 1],
        [65, 27, 78, 0.86, 45, 29, 2],
        [83, 60, 84, 1.09, 73, 27, 3],
        [109, 81, 121, 1.28, 68, 51, 4],
        [106, 77, 114, 1.07, 55, 51, 5],
        [109, 81, 121, 1.28, 68, 51, 6],
        [106, 77, 114, 1.07, 55, 51, 7],
        [89, 65, 78, 0.86, 51, 26, 8],
        [53, 33, 47, 0.64, 50, 17, 9],
        [80, 55, 80, 1.01, 75, 24, 10],
        [117, 81, 124, 1.03, 45, 24, 11],
        [99, 71, 142, 1.1, 62, 42, 12],
        [95, 69, 130, 1.28, 74, 50, 13],
        [116, 87, 131, 1.47, 84, 40, 14],
        [108, 80, 121, 1.3, 85, 37, 15],
        [134, 83, 167, 1.16, 57, 43, 16],
        [79, 43, 107, 1.05, 59, 37, 17],
        [71, 46, 89, 0.86, 64, 25, 18],
        [97, 71, 113, 1.17, 88, 31, 19],
        [84, 57, 91, 0.85, 55, 31, 20],
        [87, 63, 101, 0.9, 56, 41, 21],
        [104, 77, 119, 1.09, 73, 48, 22],
        [87, 62, 100, 1, 72, 28, 23],
        [168, 128, 172, 1.49, 97, 56, 24],
        [65, 45, 51, 0.74, 39, 17, 25],
        [39, 24, 38, 0.61, 47, 17, 26],
        [39, 24, 39, 0.59, 50, 19, 27],
        [93, 68, 96, 1.05, 79, 29, 28],
        [188, 143, 197, 1.66, 99, 51, 29],
        [174, 131, 174, 1.55, 108, 50, 30],
        [187, 143, 201, 1.39, 89, 53, 31]
        ]
    c_schema = [{"name":"AQI", "max": 300, "min": 5},
              {"name":"PM2.5", "max": 250, "min": 20},
                {"name":"PM10", "max":300, "min": 5},
                {"name":"CO", "max":5},
                {"name":"NO2", "max":200},
                {"name":"SO2", "max":100}]

    radar = Radar("雷达图示例")
    radar.config(c_schema=c_schema, shape='circle')
    radar.add("北京", value_bj, item_color="#f9713c", symbol=None)
    radar.add("上海", value_sh, item_color="#b3e4a1", symbol=None, legend_selectedmode='signle')
    radar.show_config()
    radar.render()

    # radar_2
    radar = Radar("雷达图示例")
    radar.config(c_schema=c_schema, shape='circle')
    radar.add("北京", value_bj, item_color="#f9713c", symbol=None)
    radar.add("上海", value_sh, item_color="#b3e4a1", symbol=None)
    radar.show_config()
    radar.render()
Python 3.6.3 (v3.6.3:2c5fed8, Oct  3 2017, 17:26:49) [MSC v.1900 32 bit (Intel)] on win32
Type "copyright", "credits" or "license()" for more information.
>>> # Part 6 Create Radar with Pyecharts
>>> from pyecharts import Radar
>>> schema=[("Sales",6500),("Magagement",16000),("IT",30000),("CustomerService",38000),("R&D",52000),("Marketing",25000)]
>>> v1=[[4300,10000,28000,35000,50000,19000]]
>>> v2=[[5000,14000,28000,31000,42000,21000]]
>>> radar=Radar()
>>> radar.config(schema)
<pyecharts.charts.radar.Radar object at 0x038A7930>
>>> radar.add("budget",v1,is_splitline=True,is_axisline_show=True)
<pyecharts.charts.radar.Radar object at 0x038A7930>
>>> radar.add("spent",v2,label_color=["#4e79a7"],is_area_show=False)
<pyecharts.charts.radar.Radar object at 0x038A7930>
>>> radar.show_config()

{
    "title": [
        {
            "left": "auto",
            "top": "auto",
            "textStyle": {
                "fontSize": 18
            },
            "subtextStyle": {
                "fontSize": 12
            }
        }
    ],
    "toolbox": {
        "show": true,