Closing_Date AAL_Close AAPL_Close
665 2015-01-12 49.580002 27.312500
666 2015-01-13 50.400002 27.555000
667 2015-01-14 49.410000 27.450001
668 2015-01-15 49.410000 26.705000
669 2015-01-16 49.810001 26.497499
我想用今天的股價除以昨天的股價。第一行將導致 Nan 或 empty 。它正在計算每日收益。
我想用今天的股價除以昨天的股價。第一行將導致 Nan 或 empty 。它正在計算每日收益。
uj5u.com熱心網友回復:
假設您有所有連續的日期:
df['Closing_Date'] = pd.to_datetime(df['Closing_Date'])
df2 = df.set_index('Closing_Date')
df2.div(df2.shift(1))
或者,如果您真的想依賴上一個日期:
df['Closing_Date'] = pd.to_datetime(df['Closing_Date'])
df2 = df.set_index('Closing_Date')
df2.div(df2.reindex(df2.index-pd.Timedelta('1d')).values)
輸出:
AAL_Close AAPL_Close
Closing_Date
2015-01-12 NaN NaN
2015-01-13 1.016539 1.008879
2015-01-14 0.980357 0.996189
2015-01-15 1.000000 0.972860
2015-01-16 1.008096 0.992230
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