Data frame with unique values from other data frame(pandas, python)

Question

I have data frame in which I have duplicates values (in each column not duplicated rows). Data look like that:

|Col1|Col2|Cold3|Col4|
|   1|   A| John| -10|
|   2|   A|Scoot| 234|
|   2|   B|Kerry| 346|
|   6|   B| Adam| -10|

I would like to create another df from this one which would look like that:

|Col1|Col2|Cold3|Col4|
|   1|   A| John| -10|
|   2|   B|Scoot| 234|
|   6|null|Kerry| 346|
|null|null| Adam|null|

Those null could be NaN of course.

I can go by each column and print unique values for each:

for col in df:
    print (df[col].unique())

which returns numpy arrays. But I'm not sure how to write it to new data frame to look like one that I showed erlier.

Answer 1

I think you need:

df = df.apply(lambda x: pd.Series(x.unique()))
print (df)
   Col1 Col2  Cold3   Col4
0   1.0    A   John  -10.0
1   2.0    B  Scoot  234.0
2   6.0  NaN  Kerry  346.0
3   NaN  NaN   Adam    NaN

Or:

df = df.apply(lambda x: pd.Series(x.drop_duplicates().values))
print (df)
   Col1 Col2  Cold3   Col4
0   1.0    A   John  -10.0
1   2.0    B  Scoot  234.0
2   6.0  NaN  Kerry  346.0
3   NaN  NaN   Adam    NaN