同花顺Supermind量化交易 了解热力图、雷达图、水球图、河流图等--附源代码

Supermind量化交易
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使用python语言来了解热力图、雷达图、水球图、河流图、关系图和仪表盘，附完整代码。

了解热力图、雷达图、水球图、河流图、水球图等

In [5]:

import random
from pyecharts import HeatMap

x_axis = [
    "12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a", "11a",
    "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p", "10p", "11p"]
y_axis = [
    "Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"]
data = [[i, j, random.randint(0, 100)] for i in range(24) for j in range(7)]
heatmap = HeatMap()
heatmap.add(
    "热力图直角坐标系",
    x_axis,
    y_axis,
    data,
    is_visualmap=True,
    visual_text_color="#000",
    visual_orient="horizontal",
)
heatmap

Out[5]:

In [6]:

from pyecharts import Kline

v1 = [[2320.26, 2320.26, 2287.3, 2362.94], [2300, 2291.3, 2288.26, 2308.38],
      [2295.35, 2346.5, 2295.35, 2345.92], [2347.22, 2358.98, 2337.35, 2363.8],
      [2360.75, 2382.48, 2347.89, 2383.76], [2383.43, 2385.42, 2371.23, 2391.82],
      [2377.41, 2419.02, 2369.57, 2421.15], [2425.92, 2428.15, 2417.58, 2440.38],
      [2411, 2433.13, 2403.3, 2437.42], [2432.68, 2334.48, 2427.7, 2441.73],
      [2430.69, 2418.53, 2394.22, 2433.89], [2416.62, 2432.4, 2414.4, 2443.03],
      [2441.91, 2421.56, 2418.43, 2444.8], [2420.26, 2382.91, 2373.53, 2427.07],
      [2383.49, 2397.18, 2370.61, 2397.94], [2378.82, 2325.95, 2309.17, 2378.82],
      [2322.94, 2314.16, 2308.76, 2330.88], [2320.62, 2325.82, 2315.01, 2338.78],
      [2313.74, 2293.34, 2289.89, 2340.71], [2297.77, 2313.22, 2292.03, 2324.63],
      [2322.32, 2365.59, 2308.92, 2366.16], [2364.54, 2359.51, 2330.86, 2369.65],
      [2332.08, 2273.4, 2259.25, 2333.54], [2274.81, 2326.31, 2270.1, 2328.14],
      [2333.61, 2347.18, 2321.6, 2351.44], [2340.44, 2324.29, 2304.27, 2352.02],
      [2326.42, 2318.61, 2314.59, 2333.67], [2314.68, 2310.59, 2296.58, 2320.96],
      [2309.16, 2286.6, 2264.83, 2333.29], [2282.17, 2263.97, 2253.25, 2286.33],
      [2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例")
kline.add("指数日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1)
kline

Out[6]:

In [7]:

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()
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

Out[7]:

In [8]:

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")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2)
scatter

Out[8]:

In [9]:

from pyecharts import ThemeRiver

data = [    ['2015/11/08', 10, 'DQ'], ['2015/11/09', 15, 'DQ'], ['2015/11/10', 35, 'DQ'],
    ['2015/11/14', 7, 'DQ'], ['2015/11/15', 2, 'DQ'], ['2015/11/16', 17, 'DQ'],
    ['2015/11/17', 33, 'DQ'], ['2015/11/18', 40, 'DQ'], ['2015/11/19', 32, 'DQ'],
    ['2015/11/20', 26, 'DQ'], ['2015/11/21', 35, 'DQ'], ['2015/11/22', 40, 'DQ'],
    ['2015/11/23', 32, 'DQ'], ['2015/11/24', 26, 'DQ'], ['2015/11/25', 22, 'DQ'],
    ['2015/11/08', 35, 'TY'], ['2015/11/09', 36, 'TY'], ['2015/11/10', 37, 'TY'],
    ['2015/11/11', 22, 'TY'], ['2015/11/12', 24, 'TY'], ['2015/11/13', 26, 'TY'],
    ['2015/11/14', 34, 'TY'], ['2015/11/15', 21, 'TY'], ['2015/11/16', 18, 'TY'],
    ['2015/11/17', 45, 'TY'], ['2015/11/18', 32, 'TY'], ['2015/11/19', 35, 'TY'],
    ['2015/11/20', 30, 'TY'], ['2015/11/21', 28, 'TY'], ['2015/11/22', 27, 'TY'],
    ['2015/11/23', 26, 'TY'], ['2015/11/24', 15, 'TY'], ['2015/11/25', 30, 'TY'],
    ['2015/11/26', 35, 'TY'], ['2015/11/27', 42, 'TY'], ['2015/11/28', 42, 'TY'],
    ['2015/11/08', 21, 'SS'], ['2015/11/09', 25, 'SS'], ['2015/11/10', 27, 'SS'],
    ['2015/11/11', 23, 'SS'], ['2015/11/12', 24, 'SS'], ['2015/11/13', 21, 'SS'],
    ['2015/11/14', 35, 'SS'], ['2015/11/15', 39, 'SS'], ['2015/11/16', 40, 'SS'],
    ['2015/11/17', 36, 'SS'], ['2015/11/18', 33, 'SS'], ['2015/11/19', 43, 'SS'],
    ['2015/11/20', 40, 'SS'], ['2015/11/21', 34, 'SS'], ['2015/11/22', 28, 'SS'],
    ['2015/11/14', 7, 'QG'], ['2015/11/15', 2, 'QG'], ['2015/11/16', 17, 'QG'],
    ['2015/11/17', 33, 'QG'], ['2015/11/18', 40, 'QG'], ['2015/11/19', 32, 'QG'],
    ['2015/11/20', 26, 'QG'], ['2015/11/21', 35, 'QG'], ['2015/11/22', 40, 'QG'],
    ['2015/11/23', 32, 'QG'], ['2015/11/24', 26, 'QG'], ['2015/11/25', 22, 'QG'],
    ['2015/11/26', 16, 'QG'], ['2015/11/27', 22, 'QG'], ['2015/11/28', 10, 'QG'],
    ['2015/11/08', 10, 'SY'], ['2015/11/09', 15, 'SY'], ['2015/11/10', 35, 'SY'],
    ['2015/11/11', 38, 'SY'], ['2015/11/12', 22, 'SY'], ['2015/11/13', 16, 'SY'],
    ['2015/11/14', 7, 'SY'], ['2015/11/15', 2, 'SY'], ['2015/11/16', 17, 'SY'],
    ['2015/11/17', 33, 'SY'], ['2015/11/18', 40, 'SY'], ['2015/11/19', 32, 'SY'],
    ['2015/11/20', 26, 'SY'], ['2015/11/21', 35, 'SY'], ['2015/11/22', 4, 'SY'],
    ['2015/11/23', 32, 'SY'], ['2015/11/24', 26, 'SY'], ['2015/11/25', 22, 'SY'],
    ['2015/11/26', 16, 'SY'], ['2015/11/27', 22, 'SY'], ['2015/11/28', 10, 'SY'],
    ['2015/11/08', 10, 'DD'], ['2015/11/09', 15, 'DD'], ['2015/11/10', 35, 'DD'],
    ['2015/11/11', 38, 'DD'], ['2015/11/12', 22, 'DD'], ['2015/11/13', 16, 'DD'],
    ['2015/11/14', 7, 'DD'], ['2015/11/15', 2, 'DD'], ['2015/11/16', 17, 'DD'],
    ['2015/11/17', 33, 'DD'], ['2015/11/18', 4, 'DD'], ['2015/11/19', 32, 'DD'],
    ['2015/11/20', 26, 'DD'], ['2015/11/21', 35, 'DD'], ['2015/11/22', 40, 'DD'],
    ['2015/11/23', 32, 'DD'], ['2015/11/24', 26, 'DD'], ['2015/11/25', 22, 'DD']
]
tr = ThemeRiver("主题河流图示例图")
tr.add(['DQ', 'TY', 'SS', 'QG', 'SY', 'DD'], data, is_label_show=True)
tr

Out[9]:

In [10]:

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

Out[10]:

In [11]:

from pyecharts import Graph

nodes = [{"name": "结点1", "symbolSize": 10},         {"name": "结点2", "symbolSize": 10},         {"name": "结点3", "symbolSize": 10},         {"name": "结点4", "symbolSize": 40},         {"name": "结点5", "symbolSize": 10},         {"name": "结点6", "symbolSize": 10},         {"name": "结点7", "symbolSize": 10},         {"name": "结点8", "symbolSize": 10}]
links = []
for i in nodes:
    for j in nodes:
        links.append({"source": i.get('name'), "target": j.get('name')})
graph = Graph("关系图-力引导布局示例")
graph.add("", nodes, links, repulsion=8000)
graph

Out[11]:

In [12]:

from pyecharts import Liquid

liquid = Liquid("水球图示例")
liquid.add("Liquid", [0.6])
liquid

Out[12]:

In [13]:

from pyecharts import Gauge

gauge = Gauge("仪表盘示例")
gauge.add("业务指标", "完成率", 66.66)
gauge

Out[13]:

In [ ]:

查看以上策略详情请到supermind量化交易官网查看：同花顺Supermind量化交易 了解热力图、雷达图、水球图、河流图等--附源代码

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