From 88f47b80fe023d6a3406a1a76507c7a3fd172f24 Mon Sep 17 00:00:00 2001 From: Joris Van den Bossche Date: Thu, 13 Jun 2024 14:49:41 +0200 Subject: [PATCH] cleanup --- python/pyarrow/tests/test_pandas.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/python/pyarrow/tests/test_pandas.py b/python/pyarrow/tests/test_pandas.py index b7701f2926b34..7d74a60dcb921 100644 --- a/python/pyarrow/tests/test_pandas.py +++ b/python/pyarrow/tests/test_pandas.py @@ -4741,12 +4741,12 @@ def make_df_with_timestamps(): # Some of the milliseconds timestamps deliberately don't fit in the range # that is possible with nanosecond timestamps. df = pd.DataFrame({ - 'dateTimeMs': np.array([ + 'dateTimeMs': [ np.datetime64('0001-01-01 00:00', 'ms'), np.datetime64('2012-05-02 12:35', 'ms'), np.datetime64('2012-05-03 15:42', 'ms'), np.datetime64('3000-05-03 15:42', 'ms'), - ], dtype=object), + ], 'dateTimeNs': [ np.datetime64('1991-01-01 00:00', 'ns'), np.datetime64('2012-05-02 12:35', 'ns'), @@ -4757,7 +4757,6 @@ def make_df_with_timestamps(): df['dateTimeMs'] = df['dateTimeMs'].astype('object') # Not part of what we're testing, just ensuring that the inputs are what we # expect. - # if Version(pd.__version__) < Version("3.0.0.dev0"): assert (df.dateTimeMs.dtype, df.dateTimeNs.dtype) == ( # O == object, M8[ns] == timestamp64[ns] np.dtype("O"), np.dtype("M8[ns]")