BUG: Groupby mean differs depending on where np.inf value was introduced #50367
Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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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