delete columns based on fixed values

Question

I am trying to delete the columns where the non zeros is less than a said number.This is the code I got but it is giving the same answer.What am I doing wrong?

 df = pd.DataFrame([[1,0,0,0], [0,0,1,0]])



   0  1  2  3
0  1  0  0  0
1  0  0  1  0

df = df.loc[:, (df.astype(bool).sum(axis=0) <= max_number_of_zeros)]

   0  1  2  3
0  1  0  0  0
1  0  0  1  0

edit-- example-

   0  1  2  3
0  1  0  0  0
1  2  0  1  0
2  0  2  3  4
3  1  1  1  1

output would be for value=2 the columns 0 and column 2

 0  1  2  3
0  1  0  0  0
1  2  0  1  0
2  0  2  3  4
3  1  1  1  1

jezrael · Accepted Answer · 2018-07-01 18:24:08Z

1

I think you need to change the boolean mask to df.eq(0) which is the same as df == 0 with changed condition from <= to <:

max_number_of_zeros = 2
df  = df.loc[:,df.eq(0).sum(axis=0) < max_number_of_zeros]
print (df)
   0  2
0  1  0
1  2  1
2  0  3
3  1  1

Detail:

print (df.eq(0))
       0      1      2      3
0  False   True   True   True
1  False   True  False   True
2   True  False  False  False
3  False  False  False  False

print (df.eq(0).sum(axis=0))
0    1
1    2
2    1
3    2
dtype: int64

EDIT:

max_number_of_zeros = 2
df  = df.loc[:,len(df.columns) - df.astype(bool).sum(axis=0) < max_number_of_zeros]
print (df)
   0  2
0  1  0
1  2  1
2  0  3
3  1  1

edited Jul 1, 2018 at 18:24

answered Jul 1, 2018 at 16:25

jezrael

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10 Comments

ubuntu_noob Over a year ago

shouldnt the answer be col1 and co2 ?

jezrael Over a year ago

@ubuntu_noob - Sorry, solution was multiple times edited, now it should working nice.

ubuntu_noob Over a year ago

for no of zeros=2 the df doesnt change

jezrael Over a year ago

Yes, it is expected, because want remove columns with more as 2 values of zeros, so it means 3 and more

ubuntu_noob Over a year ago

I want to remove the columns whch have more than or equal to 2 zeros

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