Pandas避免比較2個資料幀的多維鍵錯誤

我陷入了多維鍵值錯誤。我有一個看起來像這樣的資料框：

    year      RMSE  index  cyear  Corr_to_CY
0   2000  0.279795      5   1997    0.997975
1   2011  0.299011      2   1994    0.997792
2   2003  0.368341      1   1993    0.977143
3   2013  0.377902     23   2015    0.824441
4   1999   0.41495     10   2002    0.804633
5   1997  0.435813      8   2000    0.752724
6   2018  0.491003     24   2016    0.703359
7   2002  0.505771      3   1995    0.684926
8   2009  0.529308     17   2009    0.580481
9   2015  0.584146     27   2019    0.556555
10  2004  0.620946     26   2018    0.500790
11  2016  0.659388     22   2014    0.443543
12  1993  0.700942     19   2011    0.431615
13  2006  0.748086     11   2003    0.375111
14  2007  0.766675     21   2013    0.323143
15  2020  0.827913     12   2004    0.149202
16  2014  0.884109      7   1999    0.002438
17  2012  0.900184      0   1992   -0.351615
18  1995  0.919482     28   2020   -0.448915
19  1992  0.930512     20   2012   -0.563762
20  2001  0.967834     18   2010   -0.613170
21  2019   1.00497      9   2001   -0.677590
22  2005   1.00885     13   2005   -0.695690
23  2010  1.159125     14   2006   -0.843122
24  2017  1.173262     15   2007   -0.931034
25  1994  1.179737      6   1998   -0.939697
26  2008  1.212915     25   2017   -0.981626
27  1996  1.308853     16   2008   -0.985893
28  1998  1.396771      4   1996   -0.999990

我選擇了'Corr_to_CY' >= 0.70 的列值的條件，并將'cyear' 列的值回傳到一個名為'cyears' 的新df 中。我需要使用它作為索引來查找“年份”列在 cyears df 中的年份和 RMSE 值。這是我最好的嘗試，我得到了值錯誤：無法使用多維鍵進行索引。我是否需要將索引 df "cyears" 更改為其他內容 - 系列、串列等才能使其正常作業？謝謝，這是我產生錯誤的代碼：

cyears = comp.loc[comp['Corr_to_CY']>= 0.7,'cyear']
cyears = cyears.to_frame()
result = comp.loc[comp['year'] == cyears,'RMSE']

ValueError: Cannot index with multidimensional key

uj5u.com熱心網友回復：

您可以使用isin方法：

import pandas as pd

# Sample creation
import io
comp = pd.read_csv(io.StringIO('year,RMSE,index,cyear,Corr_to_CY\n2000,0.279795,5,1997,0.997975\n2011,0.299011,2,1994,0.997792\n2003,0.368341,1,1993,0.977143\n2013,0.377902,23,2015,0.824441\n1999,0.41495,10,2002,0.804633\n1997,0.435813,8,2000,0.752724\n2018,0.491003,24,2016,0.703359\n2002,0.505771,3,1995,0.684926\n2009,0.529308,17,2009,0.580481\n2015,0.584146,27,2019,0.556555\n2004,0.620946,26,2018,0.500790\n2016,0.659388,22,2014,0.443543\n1993,0.700942,19,2011,0.431615\n2006,0.748086,11,2003,0.375111\n2007,0.766675,21,2013,0.323143\n2020,0.827913,12,2004,0.149202\n2014,0.884109,7,1999,0.002438\n2012,0.900184,0,1992,-0.351615\n1995,0.919482,28,2020,-0.448915\n1992,0.930512,20,2012,-0.563762\n2001,0.967834,18,2010,-0.613170\n2019,1.00497,9,2001,-0.677590\n2005,1.00885,13,2005,-0.695690\n2010,1.159125,14,2006,-0.843122\n2017,1.173262,15,2007,-0.931034\n1994,1.179737,6,1998,-0.939697\n2008,1.212915,25,2017,-0.981626\n1996,1.308853,16,2008,-0.985893\n1998,1.396771,4,1996,-0.999990\n'))

# Operations
cyears = comp.loc[comp['Corr_to_CY']>= 0.7,'cyear']
result = comp.loc[comp['year'].isin(cyears),'RMSE']

如果要保留cyears為 pandas DataFrame 而不是 Series，請嘗試以下操作：

# Operations
cyears = comp.loc[comp['Corr_to_CY']>= 0.7, ['cyear']]
result = comp.loc[comp['year'].isin(cyears.cyear),'RMSE']

標籤：熊猫 多维数组 索引 筛选

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