drop_duplicates() stopped working in Python pandas

Question

This code had previously worked in python 3 to remove the duplicate values but keep first occurrence across an entire dataframe. After coming back to my script this no longer removes duplicates in a pandas dataFrame.

df = df.apply(lambda x: x.drop_duplicates(), axis=1)

so if I have

a   b  c
0   1  2
3   4  0
0   8  9
10  0  11

I want to get as an output

a  b  c
0  1  2
3  4  
   8  9
10   11

I don't mind if the blanks return as 'nan'

I also tried the following

df.drop_duplicates(subset = None, keep='first')

and

df.drop_duplicates(subset = None, keep='first', inplace =True)

Any advice / alternatives would be welcome!

Answer 1

After your attached the data , I think you can using duplicated

newdf=df[~df.stack().duplicated().unstack()]
newdf
Out[131]: 
      a    b     c
0   0.0  1.0   2.0
1   3.0  4.0   NaN
2   NaN  8.0   9.0
3  10.0  NaN  11.0

Answer 2

You need inplace to be True:

df.drop_duplicates(subset=None, keep='first', inplace=True)