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I'm sure this has been asked before but I can't find the correct way to go about doing this. I have a dataframe with a datetime index

df = col2 test | 04-05-2018 | 56 | | 04-06-2018 | 23 | | 04-07-2018 | 87 | | 04-08-2018 | 11 |

What I would like to do is to access (and consequently create a new column from) the month property of the datetime index. I have tried to just access the property using print(df['test'].datetime.month) but I receive the expected KeyError (I know that the title of the dataframe is 'test' and not the index itself, I just don't know what to do).

Any help is greatly appreciated, and thanks in advance.

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    You can access the index as a column after calling df.reset_index() or the index directly with df.index Commented Oct 24, 2019 at 19:39
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    df.index.month or df.reset_index()['test'].dt.month. Commented Oct 24, 2019 at 19:42
  • thanks both, didn't know i could do it that way! @QuangHoang first solution is what i'm looking for as I would like to keep it as the index Commented Oct 24, 2019 at 19:45

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Hope this is what you're looking for:

import pandas as pd data = [['04-05-2018',56] , ['04-06-2018',23], ['04-07-2018',87], ['04-08-2018',11]] df = pd.DataFrame(data, columns =['test', 'col2']) df.set_index('test', inplace=True) df['MONTH'] = pd.to_datetime(df.index).month df col2 Month test 04-05-2018 56 4 04-06-2018 23 4 04-07-2018 87 4 04-08-2018 11 4
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import pandas as pd data = [['04-05-2018',56] , ['04-06-2018',23], ['04-07-2018',87], ['04-08-2018',11]] df = pd.DataFrame(data, columns =['test', 'col2']) df.set_index('test', inplace=True) df col2 test 04-05-2018 56 04-06-2018 23 04-07-2018 87 04-08-2018 11 df=dfT.reset_index() df['Months'] = list(dfT['test'].astype(str).str[3:5]) df col2 Months test 04-05-2018 56 05 04-06-2018 23 06 04-07-2018 87 07 04-08-2018 11 08

Done ✅✅

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Like this?

import pandas as pd ind = ['04-05-2018','04-06-2018', '04-07-2018', '04-08-2018'] col2 = [56,23,87,11] df = pd.DataFrame(col2, index = ind, columns = ['col2']) Out[1]: col2 04-05-2018 56 04-06-2018 23 04-07-2018 87 04-08-2018 11 df['month'] = pd.to_datetime(df.index).month df Out[2]: col2 month 04-05-2018 56 4 04-06-2018 23 4 04-07-2018 87 4 04-08-2018 11 4

upd for zeros in first char

df['month_s'] = [str(mnth).zfill(2) for mnth in pd.to_datetime(df.index).month] df Out[3]: col2 month month_s 04-05-2018 56 4 04 04-06-2018 23 4 04 11-07-2018 87 4 04 04-08-2018 11 4 04
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Basically yes! I was just trying to keep the leading zero for the month - is that possible?

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