只有某些列的Pandas Sum＆Count

Question

I have just started learning pandas, and this is a very basic question. Believe me, I have searched for an answer, but can't find one.

Can you please run this python code?

import pandas as pd

df = pd.DataFrame({'A':[1,0], 'B':[2,4], 'C':[4,4], 'D':[1,4],'count__4s_abc':[1,2],'sum__abc':[7,8]})

df

How do I create column 'count__4s_abc' in which I want to count how many times the number 4 appears in just columns AC? (While ignoring column D.)

How do I create column 'sum__abc' in which I want to sum the amounts in just columns AC? (While ignoring column D.)

Thanks much for any help!

Answer 1

Using drop

df.assign(
    count__4s_abc=df.drop('D', 1).eq(4).sum(1),
    sum__abc=df.drop('D', 1).sum(1)
)

Or explicitly choosing the 3 columns.

df.assign(
    count__4s_abc=df[['A', 'B', 'C']].eq(4).sum(1),
    sum__abc=df[['A', 'B', 'C']].sum(1)
)

Or using iloc to get first 3 columns.

df.assign(
    count__4s_abc=df.iloc[:, :3].eq(4).sum(1),
    sum__abc=df.iloc[:, :3].sum(1)
)

All give

   A  B  C  D  count__4s_abc  sum__abc
0  1  2  4  1              1         7
1  0  4  4  4              2         8

Answer 2

One additional option:

In [158]: formulas = """
     ...: new_count__4s_abc = (A==4)*1 + (B==4)*1 + (C==4)*1
     ...: new_sum__abc = A + B + C
     ...: """

In [159]: df.eval(formulas)
Out[159]:
   A  B  C  D  count__4s_abc  sum__abc  new_count__4s_abc  new_sum__abc
0  1  2  4  1              1         7                  1             7
1  0  4  4  4              2         8                  2             8

DataFrame.eval() method can (but not always) be faster compared to regular Pandas arithmetic