将列标题更改为日期格式在 dataframe 中不起作用

Question

I have a dataframe where all of the headers are in string format. However most of the headers are actually YYYY-MM dates and I would like to change these into date formate.

ldnCrimes.columns:

Index(['WardCode', 'Ward Name', 'Borough', 'Major Category', 'Minor Category',
       '2010-04', '2010-05', '2010-06', '2010-07', '2010-08',
       ...
       '2018-03', '2018-04', '2018-05', '2018-06', '2018-07', '2018-08',
       '2018-09', '2018-10', '2018-11', '2018-12'],
      dtype='object', length=110)`

When trying:

ldnCrime.columns = ldnCrime.columns[:1].tolist() + pd.to_datetime(ldnCrime.columns[5:]).tolist()

but then I get the following error:

ValueError: Length mismatch: Expected axis has 110 elements, new values have 106 elements

The 4 elements are non-date headers and I don't want to change their format.

but then I get the following error:

ValueError: Length mismatch: Expected axis has 110 elements, new values have 106 elements

The 4 elements are non-date headers and I don't want to change their format.

Thanks in advance any help you may provide.

Answer 1

Use solution from comment of @Henry Yik - select first 5 values:

idx = ['WardCode', 'Ward Name', 'Borough', 'Major Category', 'Minor Category',
       '2010-04', '2010-05', '2010-06', '2010-07', '2010-08',
       '2018-03', '2018-04', '2018-05', '2018-06', '2018-07', '2018-08',
       '2018-09', '2018-10', '2018-11', '2018-12']

ldnCrime = pd.DataFrame(columns=idx)

ldnCrime.columns = ldnCrime.columns[:5].tolist()+pd.to_datetime(ldnCrime.columns[5:]).tolist()

Another idea is convert values to Series and use fillna :

c = ldnCrime.columns.to_series()
ldnCrime.columns = pd.to_datetime(c, errors='coerce').fillna(c)

print (ldnCrime.columns)
Index([         'WardCode',         'Ward Name',           'Borough',
          'Major Category',    'Minor Category', 2010-04-01 00:00:00,
       2010-05-01 00:00:00, 2010-06-01 00:00:00, 2010-07-01 00:00:00,
       2010-08-01 00:00:00, 2018-03-01 00:00:00, 2018-04-01 00:00:00,
       2018-05-01 00:00:00, 2018-06-01 00:00:00, 2018-07-01 00:00:00,
       2018-08-01 00:00:00, 2018-09-01 00:00:00, 2018-10-01 00:00:00,
       2018-11-01 00:00:00, 2018-12-01 00:00:00],
      dtype='object')