如何在我的 python 烛台扫描仪中同时扫描多个变量？

如何解决如何在我的 python 烛台扫描仪中同时扫描多个变量？

这是我的烛台扫描仪的代码。我的目标是同时扫描多个变量，但是当我的代码运行时，它只会导致一列错误。如果有人知道如何一次扫描多个股票代码，那将大有帮助。

import datetime as dt 
import pandas_datareader as web
import pandas as pd

start = dt.datetime(2020,12,31)
end = dt.datetime.now()
Stock = ('ANZ.AX','APT.AX','FMG.AX')

df = web.DataReader(Stock,'yahoo',start,end)

# Change data to omit volume and adjusted close (can change later to display volume)
data = df[['Open','High','Low','Close']]

for i in range(2,df.shape[0]):
    current = df.iloc[i,:]
    prev = df.iloc[i - 1,:]
    prev_2 = df.iloc[i - 2,:]

    realbody = abs(current['Open'] - current['Close'])
    candle_range = current['High'] - current['Low']

    idx = df.index[i]

    # Bullish engulfing
    df.loc[idx,'Bullish Engulfing'] = (prev['Open'] > prev['Close']) & (current['Close'] > current['Open']) \
    & (current['High'] > prev['High']) & (current['Low'] < prev['Low'])

df.fillna(False,inplace=True)

pd.set_option('display.max_columns',None)
pd.set_option('display.max_rows',None)
print(df['Bullish Engulfing'])

结果代码：

Date
2020-12-30    False
2021-01-03    False
2021-01-05    False
Name: Bullish Engulfing,dtype: bool

解决方法

问题是列上有多重索引

import datetime as dt 
import pandas_datareader as web
import pandas as pd

start = dt.datetime(2020,12,31)
end = dt.datetime.now()
Stock = ('ANZ.AX','APT.AX','FMG.AX')

df = web.DataReader(Stock,'yahoo',start,end)

df.columns

给予

MultiIndex([('Adj Close','ANZ.AX'),('Adj Close','APT.AX'),'FMG.AX'),(    'Close',(     'High',(      'Low',(     'Open',(   'Volume','FMG.AX')],names=['Attributes','Symbols'])

你在代码中的位置current = df.iloc[i,:]它没有给你你的想法，因为你仍然有一个多索引

current = df.iloc[1,:]

例如产量

Attributes  Symbols
Adj Close   ANZ.AX     2.304000e+01
            APT.AX     1.190000e+02
            FMG.AX     2.480000e+01
Close       ANZ.AX     2.304000e+01
            APT.AX     1.190000e+02
            FMG.AX     2.480000e+01
High        ANZ.AX     2.314000e+01
            APT.AX     1.223000e+02
            FMG.AX     2.480000e+01
Low         ANZ.AX     2.276000e+01
            APT.AX     1.190000e+02
            FMG.AX     2.370000e+01
Open        ANZ.AX     2.276000e+01
            APT.AX     1.196800e+02
            FMG.AX     2.371000e+01
Volume      ANZ.AX     3.207879e+06
            APT.AX     9.625380e+05
            FMG.AX     6.402739e+06
Name: 2021-01-03 00:00:00,dtype: float64

所以当您回信 df.loc[idx,'Bullish Engulfing'] 时，这不是特定于股票的。

您最好使用 groupby 并逐个库存地完成所有工作。

Pandas Multiindex Groupby on Columns 将向您展示如何做到这一点。