CODEWITHSUNDEEP
pythonpandasdataframenull
Lovkush
Lovkush

Reputation: 31

how to use pandas groupby with None and NaN treated as separate values

Is it possible for pandas groupby to treat Nones and NaNs as separate entities?

Here is an example:

df = pd.DataFrame([
    [np.nan, 5],
    [None, 10],
    ['a', 7],
    [np.nan, 5],
    [None, 10]
])

Out:
      0   1
0   NaN   5
1  None  10
2     a   7
3   NaN   5
4  None  10

df.groupby(0, dropna=False).mean()

Out:
       1
0       
a    7.0
NaN  7.5

However, I want to achieve the following result:

       1
0       
a    7.0
NaN  5.0
None 10.0

EDIT: an 'ideal' solution to this problem should:

Alternatively, explaining why the task cannot be done 'tidily' would also appreciated, so one can instead think about 'hacky' solutions.

Upvotes: 3

Views: 930

Answers (1)

jezrael
jezrael

Reputation: 862511

Not very nice, but possible converting to strings:

print (df.groupby(df[0].astype(str)).mean())
       1
0       
None  10
a      7
nan    5

Upvotes: 3

Related Questions