Pandas Dataframe - Select Columns With A Specific Value In A Specific Row

I want to select columns with a specific value (say 1) in a specific row (say first row) for Pandas Dataframe

Solution 1:

Use iloc with boolean indexing, for performance is better filtering index not DataFrame and then select index (see performance):

df = pd.DataFrame({
        'A':list('abcdef'),
         'B':[4,5,4,5,5,4],
         'C':[7,8,9,4,2,3],
         'D':[1,3,5,7,1,0],
         'E':[5,3,6,9,2,4],
         'F':list('aaabbb')
})

print (df)
   A  B  C  D  E  F
0  a  4  7  1  5  a
1  b  5  8  3  3  a
2  c  4  9  5  6  a
3  d  5  4  7  9  b
4  e  5  2  1  2  b
5  f  4  3  0  4  b

s = df.iloc[0]        
a = s.index[s == 1]
print (a)
Index(['D'], dtype='object')

a = s.index.values[(s == 1)]
print (a)
['D']

Solution 2:

You can use iloc to extract a row as a series, then apply your condition:

row = df.iloc[0]           # extract first row as seriesres = row[res == 1].index  # filter for values equal to 1 and get columns via index

Solution 3:

you can use this

df['a'][df['a']==0]