关于基金主题数据如何获取,在后面的博文中会介绍,这里只介绍下,Json数据转DataFrame方便进行数据分析。
从互联网中得到的json数据如下:
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- "BKCode":"BK0900",
- "BKName":"新能源车",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1588.47,
- "ZDF":2.08,
- "ZS_3":-0.01,
- "ZS_5":0.05,
- "Cinflow":2409237504,
- "SYL_W":2.2708,
- "SYL_M":-1.2993,
- "SYL_Q":17.9353,
- "SYL_1N":50.0113,
- "SYL_JN":-0.4868,
- "Cinflow_W":-9040646656,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":0,
- "JLCTS":2,
- "TYPE":"https://files.jxasp.com/image/2"
- },
- {
- "IndexCode":"861302",
- "BKCode":"BK0903",
- "BKName":"云游戏",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1206.95,
- "ZDF":3.22,
- "ZS_3":0.02,
- "ZS_5":0.11,
- "Cinflow":287625088,
- "SYL_W":1.2712,
- "SYL_M":0.7336,
- "SYL_Q":35.4784,
- "SYL_1N":42.4416,
- "SYL_JN":2.1091,
- "Cinflow_W":-2058284880,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":0,
- "JLCTS":7,
- "TYPE":"https://files.jxasp.com/image/2"
- },
- {
- "IndexCode":"861304",
- "BKCode":"BK0905",
- "BKName":"传感器",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1483.14,
- "ZDF":2.97,
- "ZS_3":-0.02,
- "ZS_5":0.05,
- "Cinflow":578024000,
- "SYL_W":2.8002,
- "SYL_M":0.7239,
- "SYL_Q":17.9257,
- "SYL_1N":30.3286,
- "SYL_JN":-0.7807,
- "Cinflow_W":-1091329200,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":1,
- "JLCTS":0,
- "TYPE":"https://files.jxasp.com/image/2"
- },
- {
- "IndexCode":"861346",
- "BKCode":"BK0952",
- "BKName":"第三代半导体",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1482.57,
- "ZDF":2.04,
- "ZS_3":0,
- "ZS_5":0.04,
- "Cinflow":884623712,
- "SYL_W":2.1567,
- "SYL_M":-4.4459,
- "SYL_Q":9.7875,
- "SYL_1N":38.2853,
- "SYL_JN":-3.2896,
- "Cinflow_W":-802432608,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":1,
- "JLCTS":0,
- "TYPE":"https://files.jxasp.com/image/2"
- },
- {
- "IndexCode":"861361",
- "BKCode":"BK0968",
- "BKName":"固态电池",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1952.46,
- "ZDF":1.67,
- "ZS_3":0.03,
- "ZS_5":0.06,
- "Cinflow":552513792,
- "SYL_W":2.3833,
- "SYL_M":-8.3529,
- "SYL_Q":-0.0236,
- "SYL_1N":64.6007,
- "SYL_JN":-3.8349,
- "Cinflow_W":601349696,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":1,
- "JLCTS":0,
- "TYPE":"https://files.jxasp.com/image/2"
- },
- {
- "IndexCode":"861362",
- "BKCode":"BK0969",
- "BKName":"汽车芯片",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1297.51,
- "ZDF":2.52,
- "ZS_3":0.04,
- "ZS_5":0.11,
- "Cinflow":546226960,
- "SYL_W":2.2974,
- "SYL_M":-1.6822,
- "SYL_Q":9.7817,
- "SYL_1N":null,
- "SYL_JN":-2.7565,
- "Cinflow_W":-132055184,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":1,
- "JLCTS":0,
- "TYPE":"https://files.jxasp.com/image/2"
- },
- {
- "IndexCode":"861368",
- "BKCode":"BK0976",
- "BKName":"被动元件",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1427.96,
- "ZDF":2.39,
- "ZS_3":0.02,
- "ZS_5":0.02,
- "Cinflow":29287488,
- "SYL_W":1.7123,
- "SYL_M":-4.3864,
- "SYL_Q":10.6723,
- "SYL_1N":null,
- "SYL_JN":-6.0812,
- "Cinflow_W":-792292720,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":1,
- "JLCTS":0,
- "TYPE":"https://files.jxasp.com/image/2"
- },
- {
- "IndexCode":"861369",
- "BKCode":"BK0977",
- "BKName":"碳化硅",
- "TradeDate":"/Date(1642348800000-0000)/",
- "NewPrice":1391.02,
- "ZDF":1.77,
- "ZS_3":-0.01,
- "ZS_5":0.04,
- "Cinflow":215858352,
- "SYL_W":1.0886,
- "SYL_M":-7.1514,
- "SYL_Q":7.046,
- "SYL_1N":null,
- "SYL_JN":-5.5501,
- "Cinflow_W":-751877728,
- "LZTS":1,
- "LDTS":0,
- "JLRTS":1,
- "JLCTS":0,
- "TYPE":"https://files.jxasp.com/image/2"
- }
- ]
- },
- "ErrCode":0,
- "ErrMsg":null,
- "TotalCount":0,
- "Expansion":null,
- "PageSize":0,
- "PageIndex":0
- }
其中比较关键的数据:
①hy为行业,gn为概念,都代表基金的主题;
②TradeData为日期,这里面的数据是2022-01-17到一年前的,某交易所统计的数据;
③SYL_XX:这个SYL为收益率。
SYL_W:近一周收益率;
SYL_M:近一月收益率;
SYL_Q:近三月收益率;
SYL_1N:近一年收益率;
Python代码如下:
- # -*- coding: utf-8 -*-
-
- import pandas as pd
- import json
-
- if __name__ == '__main__':
- dataStr = open('fund_index.json').read()
- dataObject = json.loads(s=dataStr)
- hyData = json.dumps(dataObject["Data"]["hy"])
- gnData = json.dumps(dataObject["Data"]["gn"])
- hyDf = pd.read_json(hyData)
- gnDf = pd.read_json(gnData)
-
- hyDf = hyDf.set_index("IndexCode")
- gnDf = gnDf.set_index("IndexCode")
-
- # 合并数据
- df = hyDf.combine_first(gnDf)
- print(df)
-
- pass
运行截图如下: