Joe's answer shows how to get rows based on column values, it seems like you want to get columns based on row values. Here's a simple way to achieve this using list comprehension.
In [45]: df = pd.DataFrame({'one': [2, 3, 4], 'two': [5, 6, 7], 'three': [8, 6, 1]})
In [46]: df
Out[46]:
one two three
0 2 5 8
1 3 6 6
2 4 7 1
Now we'll assign variables to say which row we're looking at, and the value which needs to be there in order to keep the column. Then we do the list comprehension and give the filtered df a new name
In [50]: row = 1
In [51]: value = 6
In [53]: list_comp = [c for c in df.columns if df[c][row] == value]
In [54]: filtered_df = df[list_comp]
In [55]: filtered_df
Out[55]:
two three
0 5 8
1 6 6
2 7 1