2

I have column names in list within list with different size like [["a","b","c"],["d","e"],["f"]] also few of the columns contains NaN.

|a b c d e f|

|1 2 3 4 5 6|

|1 2 3 Nan NaN 6|

|1 2 3 4 inf 6|

The result should be the sum of a list within a list like g=a+b+c, h=d+e, i=f which are column names. NaN sum should result NaN, not 0. How to do that in a loop?

Expected Output

|g h i|

|6 9 6|

|6 NaN 6|

|6 inf 6|

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3
  • Can you add expected output? Commented Feb 12, 2020 at 6:14
  • Expected Output added Commented Feb 12, 2020 at 6:44
  • Super, answer was edited, please check it. Commented Feb 12, 2020 at 6:48

1 Answer 1

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3

Use list comprehension:

L = [["a","b","c"],["d","e"],["f"]]

a = [df[x].sum(axis=1, min_count=1) for x in L]

Loop solution:

a = []
for x in L:
    a.append(df[x].sum(axis=1, min_count=1))

print (a)
[0    6
1    6
2    6
dtype: int64, 0    9.0
1    NaN
2    inf
dtype: float64, 0    6
1    6
2    6
dtype: int64]

And then add concat:

df1 = pd.concat(a, axis=1, keys=['g','h','i'])
print (df1)
   g    h  i
0  6  9.0  6
1  6  NaN  6
2  6  inf  6
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