将您的问题理解为询问前一天收盘价与前六天平均值的比率,我创建了以下代码。将检索到的股票的收盘价按降序排列。在新列中,使用滚动函数计算六天平均值并将其相加。然后移动数据以使新列与要比较的收盘价对齐。然后我们添加了比率计算。
import yfinance as yf
data = yf.download("AAPL", start="2020-11-17", end="2020-12-18")['Adj Close'].to_frame()
data.sort_index(ascending=False, inplace=True)
data['pre_6'] = data.rolling(6).mean()
data['pre_6'] = data['pre_6'].shift(-5)
data['check'] = data['Adj Close'] /data['pre_6']
data
Adj Close pre_6 check
Date
2020-12-17 128.699997 125.303332 1.027108
2020-12-16 127.809998 124.149999 1.029480
2020-12-15 127.879997 123.578332 1.034809
2020-12-14 121.779999 122.889999 0.990968
2020-12-11 122.410004 122.968333 0.995460
2020-12-10 123.239998 123.056666 1.001490
2020-12-09 121.779999 123.030000 0.989840
2020-12-08 124.379997 123.186667 1.009687
2020-12-07 123.750000 122.298335 1.011870
2020-12-04 122.250000 121.105001 1.009455
2020-12-03 122.940002 120.068334 1.023917
2020-12-02 123.080002 118.773333 1.036260
2020-12-01 122.720001 117.234999 1.046786
2020-11-30 119.050003 116.338332 1.023308
2020-11-27 116.589996 116.269998 1.002752
2020-11-25 116.029999 116.509998 0.995880
2020-11-24 115.169998 117.069998 0.983770
2020-11-23 113.849998 117.924999 0.965444
2020-11-20 117.339996 NaN NaN
2020-11-19 118.639999 NaN NaN
2020-11-18 118.029999 NaN NaN
2020-11-17 119.389999 NaN NaN
2020-11-16 120.300003 NaN NaN