Python 如何用这样的标题组织数据帧？

我的程序返回一个有多个层的字典。在Excel中绘制时，如下所示：

Excel模板：

代码将返回此词典（已组织该词典以帮助您可视化）：

我希望在xlsx中保持数据帧的组织方式与上面的一样。

只需两个步骤

pd.json\u normalize（）

从json生成数据帧

使用

pd.MultiIndex.from_tuples（）

样本输出 看见

{'Parity': 'BITCOIN / TETHERUS', '1m': {'Datas': {'Price': {'Initial Price': '58239.43', 'Final Price': '58236.50'}, 'Oscillators': {'Buy': 1, 'Neutral': 8, 'Sell': 2}, 'MovingAverages': {'Buy': 6, 'Neutral': 1, 'Sell': 8}}}, '5m': {'Datas': {'Price': {'Initial Price': '58239.43', 'Final Price': '58231.56'}, 'Oscillators': {'Buy': 0, 'Neutral': 9, 'Sell': 2}, 'MovingAverages': {'Buy': 13, 'Neutral': 1, 'Sell': 1}}}, '15m': {'Datas': {'Price': {'Initial Price': '58239.43', 'Final Price': '58231.56'}, 'Oscillators': {'Buy': 1, 'Neutral': 6, 'Sell': 4}, 'MovingAverages': {'Buy': 13, 'Neutral': 1, 'Sell': 1}}}, '1h': {'Datas': {'Price': {'Initial Price': '58239.43', 'Final Price': '58231.55'}, 'Oscillators': {'Buy': 2, 'Neutral': 7, 'Sell': 2}, 'MovingAverages': {'Buy': 14, 'Neutral': 1, 'Sell': 0}}}, '4h': {'Datas': {'Price': {'Initial Price': '58239.43', 'Final Price':'58231.56'}, 'Oscillators': {'Buy': 3, 'Neutral': 8, 'Sell': 0}, 'MovingAverages': {'Buy': 14, 'Neutral': 1, 'Sell': 0}}}, '1D': {'Datas': {'Price': {'Initial Price': '58239.43', 'Final Price': '58231.56'}, 'Oscillators': {'Buy': 2, 'Neutra
l': 9, 'Sell': 0}, 'MovingAverages': {'Buy': 14, 'Neutral': 1, 'Sell': 0}}}, '1W': {'Datas': {'Price': {'Initial Price': '58239.43', 'Final Price': '58230.02'}, 'Oscillators': {'Buy': 1, 'Neutral': 9, 'Sell': 1}, 'MovingAverages': {'Buy': 12, 'Neutral': 3, 'Sell': 0}}}}

js = {"Parity": "BITCOIN / TETHERUS", "1m": {"Datas": {"Price": {"Initial Price": "58239.43", "Final Price": "58236.50"}, "Oscillators": {"Buy": 1, "Neutral": 8, "Sell": 2}, "MovingAverages": {"Buy": 6, "Neutral": 1, "Sell": 8}}}, "5m": {"Datas": {"Price": {"Initial Price": "58239.43", "Final Price": "58231.56"}, "Oscillators": {"Buy": 0, "Neutral": 9, "Sell": 2}, "MovingAverages": {"Buy": 13, "Neutral": 1, "Sell": 1}}}, "15m": {"Datas": {"Price": {"Initial Price": "58239.43", "Final Price": "58231.56"}, "Oscillators": {"Buy": 1, "Neutral": 6, "Sell": 4}, "MovingAverages": {"Buy": 13, "Neutral": 1, "Sell": 1}}}, "1h": {"Datas": {"Price": {"Initial Price": "58239.43", "Final Price": "58231.55"}, "Oscillators": {"Buy": 2, "Neutral": 7, "Sell": 2}, "MovingAverages": {"Buy": 14, "Neutral": 1, "Sell": 0}}}, "4h": {"Datas": {"Price": {"Initial Price": "58239.43", "Final Price": "58231.56"}, "Oscillators": {"Buy": 3, "Neutral": 8, "Sell": 0}, "MovingAverages": {"Buy": 14, "Neutral": 1, "Sell": 0}}}, "1D": {"Datas": {"Price": {"Initial Price": "58239.43", "Final Price": "58231.56"}, "Oscillators": {"Buy": 2, "Neutral": 9, "Sell": 0}, "MovingAverages": {"Buy": 14, "Neutral": 1, "Sell": 0}}}, "1W": {"Datas": {"Price": {"Initial Price": "58239.43", "Final Price": "58230.02"}, "Oscillators": {"Buy": 1, "Neutral": 9, "Sell": 1}, "MovingAverages": {"Buy": 12, "Neutral": 3, "Sell": 0}}}}

df = pd.json_normalize(js).set_index("Parity")
df.columns=pd.MultiIndex.from_tuples([tuple(c.split(".")) for c in df.columns], names=["tenor","datas","type","measure"])
df = df.droplevel("datas",1)

tenor                         1m                                                                             5m                                                                 
type                       Price             Oscillators              MovingAverages                      Price             Oscillators              MovingAverages             
measure            Initial Price Final Price         Buy Neutral Sell            Buy Neutral Sell Initial Price Final Price         Buy Neutral Sell            Buy Neutral Sell
Parity                                                                                                                                                                          
BITCOIN / TETHERUS      58239.43    58236.50           1       8    2              6       1    8      58239.43    58231.56           0       9    2             13       1    1