python - 无法删除索引列并重命名第二列

Question

我有以下代码，但无法删除索引并重命名秒列。索引和第二列具有相同的名称“Date”。我该如何修复它？

              Date     Open     High      Low     Last    Close  \
Date                                                                 
2010-12-31 2010-12-31    71.50    74.00    71.50    72.05    72.40   
2011-01-31 2011-01-31    70.05    73.00    70.05    72.70    72.75   
2011-02-28 2011-02-28    77.00    77.00    74.80    74.90    74.85   
2011-03-31 2011-03-31    54.35    58.85    54.35    55.00    55.25   
2011-04-30 2011-04-29    60.50    60.50    58.10    58.10    58.20   
2011-05-31 2011-05-31    52.50    53.50    52.10    52.95    52.55   
2011-06-30 2011-06-30    46.30    46.95    45.60    46.60    46.65   
2011-07-31 2011-07-29    49.70    50.40    49.30    49.30    49.60   
2011-08-31 2011-08-30    45.10    47.90    43.05    47.85    47.45   
2011-09-30 2011-09-30    42.05    43.45    41.40    41.75    41.85   
2011-10-31 2011-10-31    43.70    43.70    41.10    43.70    43.70   
2011-11-30 2011-11-30    39.95    39.95    38.05    38.15    38.15   
2011-12-31 2011-12-30    31.55    35.80    31.15    34.00    34.10   
2012-01-31 2012-01-31    44.95    45.30    43.70    44.00    44.00   
2012-02-29 2012-02-29    47.90    49.00    46.15    47.00    46.25   
2012-03-31 2012-03-30    44.75    44.75    43.60    44.40    44.45   
2012-04-30 2012-04-30    70.00    75.60    66.70    75.60    75.60

Answer 1

使用rename_axis要更改索引名称，如果需要 index 中的列，请添加 reset_index如有必要，请使用重命名:

df = df.rename_axis('Date1').reset_index().rename(columns={'Date':'New'})
print (df)
         Date1         New   Open   High    Low   Last  Close
0   2010-12-31  2010-12-31  71.50  74.00  71.50  72.05  72.40
1   2011-01-31  2011-01-31  70.05  73.00  70.05  72.70  72.75
2   2011-02-28  2011-02-28  77.00  77.00  74.80  74.90  74.85
3   2011-03-31  2011-03-31  54.35  58.85  54.35  55.00  55.25
4   2011-04-30  2011-04-29  60.50  60.50  58.10  58.10  58.20
5   2011-05-31  2011-05-31  52.50  53.50  52.10  52.95  52.55
6   2011-06-30  2011-06-30  46.30  46.95  45.60  46.60  46.65
7   2011-07-31  2011-07-29  49.70  50.40  49.30  49.30  49.60
8   2011-08-31  2011-08-30  45.10  47.90  43.05  47.85  47.45
9   2011-09-30  2011-09-30  42.05  43.45  41.40  41.75  41.85
10  2011-10-31  2011-10-31  43.70  43.70  41.10  43.70  43.70
11  2011-11-30  2011-11-30  39.95  39.95  38.05  38.15  38.15
12  2011-12-31  2011-12-30  31.55  35.80  31.15  34.00  34.10
13  2012-01-31  2012-01-31  44.95  45.30  43.70  44.00  44.00
14  2012-02-29  2012-02-29  47.90  49.00  46.15  47.00  46.25
15  2012-03-31  2012-03-30  44.75  44.75  43.60  44.40  44.45
16  2012-04-30  2012-04-30  70.00  75.60  66.70  75.60  75.60

或者如果需要删除索引并重命名:

df = df.reset_index(drop=True).rename(columns={'Date':'New'})
print (df)
           New   Open   High    Low   Last  Close
0   2010-12-31  71.50  74.00  71.50  72.05  72.40
1   2011-01-31  70.05  73.00  70.05  72.70  72.75
2   2011-02-28  77.00  77.00  74.80  74.90  74.85
3   2011-03-31  54.35  58.85  54.35  55.00  55.25
4   2011-04-29  60.50  60.50  58.10  58.10  58.20
5   2011-05-31  52.50  53.50  52.10  52.95  52.55
6   2011-06-30  46.30  46.95  45.60  46.60  46.65
7   2011-07-29  49.70  50.40  49.30  49.30  49.60
8   2011-08-30  45.10  47.90  43.05  47.85  47.45
9   2011-09-30  42.05  43.45  41.40  41.75  41.85
10  2011-10-31  43.70  43.70  41.10  43.70  43.70
11  2011-11-30  39.95  39.95  38.05  38.15  38.15
12  2011-12-30  31.55  35.80  31.15  34.00  34.10
13  2012-01-31  44.95  45.30  43.70  44.00  44.00
14  2012-02-29  47.90  49.00  46.15  47.00  46.25
15  2012-03-30  44.75  44.75  43.60  44.40  44.45
16  2012-04-30  70.00  75.60  66.70  75.60  75.60

如果只需要重命名索引名称和列名称:

df = df.rename_axis('Date1').rename(columns={'Date':'New'})
print (df)
                   New   Open   High    Low   Last  Close
Date1                                                    
2010-12-31  2010-12-31  71.50  74.00  71.50  72.05  72.40
2011-01-31  2011-01-31  70.05  73.00  70.05  72.70  72.75
2011-02-28  2011-02-28  77.00  77.00  74.80  74.90  74.85
2011-03-31  2011-03-31  54.35  58.85  54.35  55.00  55.25
2011-04-30  2011-04-29  60.50  60.50  58.10  58.10  58.20
2011-05-31  2011-05-31  52.50  53.50  52.10  52.95  52.55
2011-06-30  2011-06-30  46.30  46.95  45.60  46.60  46.65
2011-07-31  2011-07-29  49.70  50.40  49.30  49.30  49.60
2011-08-31  2011-08-30  45.10  47.90  43.05  47.85  47.45
2011-09-30  2011-09-30  42.05  43.45  41.40  41.75  41.85
2011-10-31  2011-10-31  43.70  43.70  41.10  43.70  43.70
2011-11-30  2011-11-30  39.95  39.95  38.05  38.15  38.15
2011-12-31  2011-12-30  31.55  35.80  31.15  34.00  34.10
2012-01-31  2012-01-31  44.95  45.30  43.70  44.00  44.00
2012-02-29  2012-02-29  47.90  49.00  46.15  47.00  46.25
2012-03-31  2012-03-30  44.75  44.75  43.60  44.40  44.45
2012-04-30  2012-04-30  70.00  75.60  66.70  75.60  75.60