Python Pandas Key Error When Trying to Access Index

Question

I have the following data set of stocks along the columns, dates down the rows(downloaded using Bloomberg's Python API - please ignore fact that they are all 'NaN' - this is just for this portion of the data):

I am trying to extract the Month and Years from the Index in order to later do a pivot:

values['month'] = values['date'].apply(lambda x: x.month)

Where values is the name of the above DataFrame.

However this gives an error: 'KeyError 'date'

Running:

values.index

Looks fine:

DatetimeIndex(['2010-01-01', '2010-01-02', '2010-01-03', '2010-01-23',
           '2010-01-24', '2010-01-29', '2010-01-30', '2010-01-31',
           '2010-02-13', '2010-02-14',
           ...
           '2017-08-12', '2017-08-27', '2017-08-31', '2017-09-01',
           '2017-09-03', '2017-09-09', '2017-09-24', '2017-09-29',
           '2017-09-30', '2017-10-01'],
          dtype='datetime64[ns]', name='date', length=593, freq=None)

So I am just wondering what is going wrong and why I don't seem able to access the actual index here?

Answer 1

First columns is called index and date is index.name.

You can check it by:

print (df.index.name)

So you need DatetimeIndex.month and DatetimeIndex.year:

values.index.month

EDIT:

For custom string format dates are used as strftime:

values['name'] = values.index.strftime('%B - %Y')