Filtering for Dataframe - columns and rows

Question

I want to perform filtering for Pandas Dataframe. The sample table is like below. For example, I want to filter(remove) all columns which contains the value 2.

C1 C2 C3 C4 C5
1  1  1  1  4
1  2  1  2  5
1  1  3  1  4

I want result table like this. (C2 and C4 removed)

C1 C3 C5
1  1  4
1  1  5
1  3  4

Also, I want to do this job on rows, using value 5.

C1 C3 C5
1  1  4
1  3  4

I can do it very easily for single column or row, like df = df[df.C2 !=2], but I don't have good idea for multiple or whole columns and rows. Is there some simple way for this?

Answer 1

You can select by loc with any and specify axis:

print df
   C1  C2  C3  C4  C5
0   1   1   1   1   4
1   1   2   1   2   5
2   1   1   3   1   4

print ~(df == 2)
     C1     C2    C3     C4    C5
0  True   True  True   True  True
1  True  False  True  False  True
2  True   True  True   True  True

df = df.loc[:, ~(df == 2).any(axis=0)]
print df
   C1  C3  C5
0   1   1   4
1   1   1   5
2   1   3   4

df = df.loc[~(df == 5).any(axis=1)]
print df
   C1  C3  C5
0   1   1   4
2   1   3   4