Python code to find sum of column values across columns(axis = 1)?-CodePudding

I have data frame which looks similar to the one mentioned below:

a = dict({'Id' : [1, 2, 3, 4, 5, 6],
          'Age' : [20, 30, 40, 50, 60, 70],
          "Class" : [1, 2, 3, 4, 5, 6],
          "test_0_n" : [1, 2, 0, 0, 4, 5],
          "test_1_n" : [2, 2, 0, 0, 4, 5],
          "test_2_n" : [3, 2, 0, 1, 4, 5],
          "test_3_n" : [4, 3, 0, 0, 4, 5],
          "test_4_n" : [5, 4, 0, 1, 8, 5],
          "test_5_n" : [6, 4, 0, 0, 9, 5],
          "test_6_n" : [7, 2, 0, 1, 10, 5],
          "Output" : [21, 32, 999, 54, 65, 76]
         })
test = pd.DataFrame(a)
test.head(10)

I want to do a sum of all the column containing "test" as column name and then calculate the sum of all those columns and if sum(axis = 1) is 0 Output = 999 else Output = Age Class.

In my code as you can see for Index = 2 Output is showing 999 because sum(axis=1) for all the columns with "test" is 0?

CodePudding user response：

df['result']=np.where((df.filter(like='test').sum(axis=1)).eq(0),
         999,
         df['Age'] df['Class'] )
df

    Id  Age     Class   test_0_n    test_1_n    test_2_n    test_3_n    test_4_n    test_5_n    test_6_n    Output  result
0   1   20  1   1   2   3   4   5   6   7   21  21
1   2   30  2   2   2   2   3   4   4   2   32  32
2   3   40  3   0   0   0   0   0   0   0   999     999
3   4   50  4   0   0   1   0   1   0   1   54  54
4   5   60  5   4   4   4   4   8   9   10  65  65
5   6   70  6   5   5   5   5   5   5   5   76  76

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