I have a datframe with 4 columns of strings and others as integers. Now I need to find out those rows of data where at least one of the column is a non-zero value (or > 0).

manwra,sahAyaH,T7,0,0,0,0,T
manwra, akriti,T5,0,0,1,0,K 
awma, prabrtih,B6, 0,1,1,0,S

My output should be

manwra, akriti,T5,0,0,1,0,K 
awma, prabrtih,B6, 0,1,1,0,S

I have tried the following to obtain the answer. The string values are in colums 0,1,2 and -1 (last column).

KT[KT.ix[:,3:-2] != 0]

What I am receiving as output is

NaN,NaNNaN,NaN,NaN,NaN,NaN,NaN
NaN,NaN,NaN,NaN,NaN,1,NaN,NaN
NaN,NaN,NaN,NaN,1,1,NaN,NaN

How to obtain the desired output

Here is an alternative solution which uses select_dtypes() method:

In [41]: df[(df.select_dtypes(include=['number']) != 0).any(1)]
Out[41]:
        0          1   2  3  4  5  6  7
1  manwra     akriti  T5  0  0  1  0  K
2    awma   prabrtih  B6  0  1  1  0  S

Explanation:

In [42]: df.select_dtypes(include=['number']) != 0
Out[42]:
       3      4      5      6
0  False  False  False  False
1  False  False   True  False
2  False   True   True  False

In [43]: (df.select_dtypes(include=['number']) != 0).any(1)
Out[43]:
0    False
1     True
2     True
dtype: bool