[FIXED] Extracting just Month and Year separately from Pandas Datetime column

Issue

I have a Dataframe, df, with the following column:

df['ArrivalDate'] =
...
936   2012-12-31
938   2012-12-29
965   2012-12-31
966   2012-12-31
967   2012-12-31
968   2012-12-31
969   2012-12-31
970   2012-12-29
971   2012-12-31
972   2012-12-29
973   2012-12-29
...

The elements of the column are pandas.tslib.Timestamp.

I want to just include the year and month. I thought there would be simple way to do it, but I can't figure it out.

Here's what I've tried:

df['ArrivalDate'].resample('M', how = 'mean')

I got the following error:

Only valid with DatetimeIndex or PeriodIndex 

Then I tried:

df['ArrivalDate'].apply(lambda(x):x[:-2])

I got the following error:

'Timestamp' object has no attribute '__getitem__' 

Any suggestions?

Edit: I sort of figured it out.

df.index = df['ArrivalDate']

Then, I can resample another column using the index.

But I'd still like a method for reconfiguring the entire column. Any ideas?

Solution

If you want new columns showing year and month separately you can do this:

df['year'] = pd.DatetimeIndex(df['ArrivalDate']).year
df['month'] = pd.DatetimeIndex(df['ArrivalDate']).month

or...

df['year'] = df['ArrivalDate'].dt.year
df['month'] = df['ArrivalDate'].dt.month

Then you can combine them or work with them just as they are.

Answered By - KieranPC