Extracting just Month and Year separately from Pandas Datetime column

Question

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   2012-1         


        

Answer 1

@KieranPC's solution is the correct approach for Pandas, but is not easily extendible for arbitrary attributes. For this, you can use getattr within a generator comprehension and combine using pd.concat:

# input data
list_of_dates = ['2012-12-31', '2012-12-29', '2012-12-30']
df = pd.DataFrame({'ArrivalDate': pd.to_datetime(list_of_dates)})

# define list of attributes required    
L = ['year', 'month', 'day', 'dayofweek', 'dayofyear', 'weekofyear', 'quarter']

# define generator expression of series, one for each attribute
date_gen = (getattr(df['ArrivalDate'].dt, i).rename(i) for i in L)

# concatenate results and join to original dataframe
df = df.join(pd.concat(date_gen, axis=1))

print(df)

  ArrivalDate  year  month  day  dayofweek  dayofyear  weekofyear  quarter
0  2012-12-31  2012     12   31          0        366           1        4
1  2012-12-29  2012     12   29          5        364          52        4
2  2012-12-30  2012     12   30          6        365          52        4