dataframe - how to add specific row and columns from pandas -


i have data set below when tried sum column sum year. want sum jan dec.

the code tried isdata.sum(axis=0)

out[64]:      year  jan  feb  mar  apr  may  jun  jul  aug  sep  oct  nov  dec 0   1981   32   26   62   22   23   98   80  163   13  122  144  109 1   1982   42   30   54   50  192   37   52   77   48   46   74   52 2   1983   78   10  107   46   36  105   80   25  188   58   36   78 3   1984   72   29   34   11   29   97   67   51  145  114   51   51 4   1985   83   37   42   69   23   25  104   50   76   53   74   63 5   1986   50   12   69   51   77   39  121  234   56   45   54   89 6   1987   23   28   22    4   55   77   92  122   65   34   54   24 7   1988   72   64   40   37   41   51  106  173   36   69   38   66 8   1989    9   28   51   55   38   42   11   68   23   74   55   59 9   1990   74   79   56   46   30   25  128   42  153   79   60   42 10  1991   59   29   41   24   78  142   54  124   71   27   47   37

filter columns first , sum:

in [274]: df[df.columns[1:]].sum(axis=0)  out[274]: jan     594 feb     372 mar     578 apr     415 may     622 jun     738 jul     895 aug    1129 sep     874 oct     721 nov     687 dec     670 dtype: int64

if want sum row-wise pass axis=1:

in [291]: df['total'] = df[df.columns[1:]].sum(axis=1) df  out[291]:     year  jan  feb  mar  apr  may  jun  jul  aug  sep  oct  nov  dec  total 0   1981   32   26   62   22   23   98   80  163   13  122  144  109    894 1   1982   42   30   54   50  192   37   52   77   48   46   74   52    754 2   1983   78   10  107   46   36  105   80   25  188   58   36   78    847 3   1984   72   29   34   11   29   97   67   51  145  114   51   51    751 4   1985   83   37   42   69   23   25  104   50   76   53   74   63    699 5   1986   50   12   69   51   77   39  121  234   56   45   54   89    897 6   1987   23   28   22    4   55   77   92  122   65   34   54   24    600 7   1988   72   64   40   37   41   51  106  173   36   69   38   66    793 8   1989    9   28   51   55   38   42   11   68   23   74   55   59    513 9   1990   74   79   56   46   30   25  128   42  153   79   60   42    814 10  1991   59   29   41   24   78  142   54  124   71   27   47   37    733

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