Num day to Name day with Pandas

Last versions you can use dt.day_name:

df['weekday'] = df['datetime'].dt.day_name
print df
             datetime  season  holiday  workingday  weather   temp   atemp  \
0 2011-01-01 00:00:00       1        0           0        1   9.84  14.395   
1 2011-01-01 01:00:00       1        0           0        1   9.02  13.635   
2 2011-01-01 02:00:00       1        0           0        1   9.02  13.635   
3 2011-01-01 03:00:00       1        0           0        1   9.84  14.395   
4 2011-01-01 04:00:00       1        0           0        1   9.84  14.395   
5 2011-01-01 05:00:00       1        0           0        2   9.84  12.880   
6 2011-01-01 06:00:00       1        0           0        1   9.02  13.635   
7 2011-01-01 07:00:00       1        0           0        1   8.20  12.880   
8 2011-01-01 08:00:00       1        0           0        1   9.84  14.395   
9 2011-01-01 09:00:00       1        0           0        1  13.12  17.425   

   humidity  windspeed  count   weekday  
0        81     0.0000     16  Saturday  
1        80     0.0000     40  Saturday  
2        80     0.0000     32  Saturday  
3        75     0.0000     13  Saturday  
4        75     0.0000      1  Saturday  
5        75     6.0032      1  Saturday  
6        80     0.0000      2  Saturday  
7        86     0.0000      3  Saturday  
8        75     0.0000      8  Saturday  
9        76     0.0000     14  Saturday  

One method, so long as datetime is already a datetime column is to apply datetime.strftime to get the string for the weekday:

In [105]:

df['weekday'] = df[['datetime']].apply(lambda x: dt.datetime.strftime(x['datetime'], '%A'), axis=1)
df
Out[105]:
             datetime  season  holiday  workingday  weather   temp   atemp  \
0 2011-01-01 00:00:00       1        0           0        1   9.84  14.395   
1 2011-01-01 01:00:00       1        0           0        1   9.02  13.635   
2 2011-01-01 02:00:00       1        0           0        1   9.02  13.635   
3 2011-01-01 03:00:00       1        0           0        1   9.84  14.395   
4 2011-01-01 04:00:00       1        0           0        1   9.84  14.395   
5 2011-01-01 05:00:00       1        0           0        2   9.84  12.880   
6 2011-01-01 06:00:00       1        0           0        1   9.02  13.635   
7 2011-01-01 07:00:00       1        0           0        1   8.20  12.880   
8 2011-01-01 08:00:00       1        0           0        1   9.84  14.395   
9 2011-01-01 09:00:00       1        0           0        1  13.12  17.425   

   humidity  windspeed  count   weekday  
0        81     0.0000     16  Saturday  
1        80     0.0000     40  Saturday  
2        80     0.0000     32  Saturday  
3        75     0.0000     13  Saturday  
4        75     0.0000      1  Saturday  
5        75     6.0032      1  Saturday  
6        80     0.0000      2  Saturday  
7        86     0.0000      3  Saturday  
8        75     0.0000      8  Saturday  
9        76     0.0000     14  Saturday  

As to your other question, there is no difference between dayofweek and weekday.

It will be quicker to define a map of the weekday to String equivalent and call map on the weekday:

dayOfWeek={0:'Monday', 1:'Tuesday', 2:'Wednesday', 3:'Thursday', 4:'Friday', 5:'Saturday', 6:'Sunday'}
df['weekday'] = df['datetime'].dt.dayofweek.map(dayOfWeek)

For version prior to 0.15.0 the following should work:

import datetime as dt
df['weekday'] = df['datetime'].apply(lambda x: dt.datetime.strftime(x, '%A'))

Version 0.18.1 and newer

There is now a new convenience method dt.weekday_name to do the above

Version 0.23.0 and newer

weekday_name is now depricated in favour of dt.day_name.


Using dt.weekday_name is deprecated since pandas 0.23.0, instead, use dt.day_name():

df.datetime.dt.day_name()

0    Saturday
1    Saturday
2    Saturday
3    Saturday
4    Saturday
5    Saturday
6    Saturday
7    Saturday
8    Saturday
9    Saturday
Name: datetime, dtype: object