From f8b88da27f692374b6b3c1b3219a030d5e6ee067 Mon Sep 17 00:00:00 2001 From: Alessandro Berti Date: Fri, 20 Oct 2023 12:00:54 +0200 Subject: [PATCH] fix(pm4py): removing unneeded workaround in managing datetimes inside Pandas --- pm4py/objects/conversion/log/variants/to_data_frame.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/pm4py/objects/conversion/log/variants/to_data_frame.py b/pm4py/objects/conversion/log/variants/to_data_frame.py index f2cb531b0..2aaeff9ba 100644 --- a/pm4py/objects/conversion/log/variants/to_data_frame.py +++ b/pm4py/objects/conversion/log/variants/to_data_frame.py @@ -50,20 +50,20 @@ def apply(log, parameters=None): # Pandas 1.5.x has problems in managing datetime.datetime types # ensure the dates are provided as np.datetime64 which is supported correctly # until a proper fix on the Pandas side is provided - wka_dt_columns = set() + """wka_dt_columns = set() for ev in transf_log: for attr in ev: if isinstance(ev[attr], datetime): ev[attr] = np.datetime64(ev[attr]) - wka_dt_columns.add(attr) + wka_dt_columns.add(attr)""" df = pd.DataFrame.from_dict(transf_log) # additional requirement for the workaround: transform back np.datetime64 to datetime after the dataframe # is created :))) - for attr in wka_dt_columns: + """for attr in wka_dt_columns: df[attr] = df[attr].apply(lambda x: x.to_datetime64()) - df[attr] = pd.to_datetime(df[attr], utc=True) + df[attr] = pd.to_datetime(df[attr], utc=True)""" df.attrs = copy(log.properties) if pm4_constants.PARAMETER_CONSTANT_CASEID_KEY in df.attrs: