BUG: DataFrame from ndarray[SeriesObjects] vs PandasArray[SeriesObjects] inconsistent (original) (raw)

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

Reproducible Example

import numpy as np import pandas as pd

ser = pd.Series([1, 2])

arr = np.array([None, None], dtype=object) arr[0] = ser arr[1] = ser * 2

parr = pd.array(arr) # <- PandasArray

pd.DataFrame(arr) 0 0 0 1 1 2 dtype: int64 1 0 2 1 4 dtype: int64

pd.DataFrame(parr) 0 1 0 1 2 1 2 4

Issue Description

We un-nest nested data when it is in a PandasArray but not when it is in a ndarray/Index/Series. Aligning this behavior would allow us to simplify the DataFrame constructor.

Only one test where we pass a PandasArray containing Series to DataFrame: test_apply_series_on_date_time_index_aware_series

Expected Behavior

ndarray vs PandasArray should not matter here.

Installed Versions

Details

Replace this line with the output of pd.show_versions()