python - 比较数据框日期列并返回新列

Question

我有一个数据框 df，由标识符列和 4 列日期组成。请参阅下面的数据框头部。

   Identifier                    A \
0       12253  1989-11-09 00:00:00   
1       11413  1990-09-03 00:00:00   
2       12337  1977-09-07 00:00:00   
3       10610  1994-08-24 00:00:00   
4        7493  1993-08-22 00:00:00   

                      B                              C  \
0   2012-03-01 00:00:00            2015-04-01 00:00:00   
1   2009-08-16 00:00:00            2015-05-18 00:00:00   
2   1977-09-07 00:00:00            1977-09-07 00:00:00   
3   2009-01-09 00:00:00            2015-03-01 00:00:00   
4   2002-06-03 00:00:00            2015-02-16 00:00:00   

                      D  \
0   2012-01-03 00:00:00   
1   2015-05-18 00:00:00   
2   1977-09-07 00:00:00   
3   2015-03-01 00:00:00   
4   2015-02-16 00:00:00 

我试图将日期列相互比较，如果 A>=B>=C>=D 则在新列中检查应返回 True，否则返回 False。

因此生成的数据框将如下所示:

   Identifier                    A \
0       12253  1989-11-09 00:00:00   
1       11413  1990-09-03 00:00:00   
2       12337  1977-09-07 00:00:00   
3       10610  1994-08-24 00:00:00   
4        7493  1993-08-22 00:00:00   

                      B                              C  \
0   2012-03-01 00:00:00            2015-04-01 00:00:00   
1   2009-08-16 00:00:00            2015-05-18 00:00:00   
2   1977-09-07 00:00:00            1977-09-07 00:00:00   
3   2009-01-09 00:00:00            2015-03-01 00:00:00   
4   2002-06-03 00:00:00            2015-02-16 00:00:00   

                      D       Check\
0   2012-01-03 00:00:00       False
1   2015-05-18 00:00:00       True
2   1977-09-07 00:00:00       True 
3   2015-03-01 00:00:00       True
4   2015-02-16 00:00:00       True

我已经尝试过

df['Check'] = np.where(df['A'] >= df['B']>= df['C']>= df['D'], 'True', 'False')

但无法让它发挥作用。接下来我可以尝试什么？

Answer 1

使用DataFrame.eval :

df['Check'] = df.eval('A <= B <= C <= D')
print (df)
   Identifier          A          B          C          D  Check
0       12253 1989-11-09 2012-03-01 2015-04-01 2012-01-03  False
1       11413 1990-09-03 2009-08-16 2015-05-18 2015-05-18   True
2       12337 1977-09-07 1977-09-07 1977-09-07 1977-09-07   True
3       10610 1994-08-24 2009-01-09 2015-03-01 2015-03-01   True
4        7493 1993-08-22 2002-06-03 2015-02-16 2015-02-16   True