BUG: Groupby mean differs depending on where `np.inf` value was introduced

[ncclementi]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

EDIT: editing RE as initial one had some issues, the posts that say they couldn't reproduce is based on the initial post with some errors.

Reproducible Example (latest)

#When `inf` is in at the end of the columns

d ={"x": [1, 2, 3, 4, 5, np.inf], #notice inf at the end
    "y": [1, 1 ,1, 1, 1, 1],
    "z": ["alice", "bob", "alice", "bob", 
          "alice", "bob",]}
          
pdf = pd.DataFrame(d).astype({"x": "float32", "y": "float32","z": "string"})

pdf.groupby("z").x.mean()
"""returns
z
alice    3.0
bob      inf
Name: x, dtype: float32
""" 
#When `inf` is in at the beginning of the columns

d2 ={"x": [ np.inf, 1, 2, 3, 4, 5], #inf at the beginning
    "y": [1, 1 ,1, 1, 1, 1],
    "z": ["alice", "bob", "alice", "bob", 
          "alice", "bob",]}
          
pdf2 = pd.DataFrame(d2).astype({"x": "float32", "y": "float32","z": "string"})

pdf2.groupby("z").x.mean()
"""returns
z
alice    NaN
bob      3.0
Name: x, dtype: float32
"""   

Issue Description

Regardless of how inf values are inserted in the dataframe the groupby aggregation should be consistent.

Expected Behavior

It is not clear to me whether it should return NaN or Inf but it should be consistent

Installed Versions

pandas=1.5.2
numpy=1.23.5 / tried 1.24.0 too

[rhshadrach]

Thanks for the report; I'm not able to reproduce on main - I get NaN in both cases. What version of NumPy are you using?

[ncclementi]

@rhshadrach I have numpy=1.23.5

[MarcoGorelli]

I can't reproduce either, neither on pandas 1.5.2 nor on main:

In [6]: pdf
Out[6]:
     x    y      z
0  inf  1.0  alice
1  1.0  1.0    bob
2  2.0  1.0  alice
3  3.0  1.0    bob
4  4.0  1.0  alice
5  5.0  1.0    bob

In [7]: pdf.groupby("z").x.mean()
Out[7]:
z
alice    NaN
bob      3.0
Name: x, dtype: float32

[ncclementi]

Ok, I had a typo on my initial example, the problem comes on whether the inf is at idx 0 or last one. Here is the new reproducer

d ={"x": [1, 2, 3, 4, 5, np.inf], #notice inf at the end
    "y": [1, 1 ,1, 1, 1, 1],
    "z": ["alice", "bob", "alice", "bob", 
          "alice", "bob",]}
          
pdf = pd.DataFrame(d).astype({"x": "float32", "y": "float32","z": "string"})

pdf.groupby("z").x.mean()
"""returns
z
alice    3.0
bob      inf
Name: x, dtype: float32
""" 

d2 ={"x": [ np.inf, 1, 2, 3, 4, 5], #inf at the beginning
    "y": [1, 1 ,1, 1, 1, 1],
    "z": ["alice", "bob", "alice", "bob", 
          "alice", "bob",]}
          
pdf2 = pd.DataFrame(d2).astype({"x": "float32", "y": "float32","z": "string"})

pdf2.groupby("z").x.mean()
"""returns
z
alice    NaN
bob      3.0
Name: x, dtype: float32
"""
   

I can reproduce with both numpy 1.23.5 and 1.24.0

[MarcoGorelli]

ok this reproduces, thanks

[ncclementi]

Should I update the main comment, or leave it as is?