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Take A QuizGeneral Tech Bugs & Fixes 2 years ago
Posted on 16 Aug 2022, this text provides information on Bugs & Fixes related to General Tech. Please note that while accuracy is prioritized, the data presented might not be entirely correct or up-to-date. This information is offered for general knowledge and informational purposes only, and should not be considered as a substitute for professional advice.
Create 2 masks - first convert to_datetime
s with errors='coerce'
and test Series.notna
and also test this column:
mcom/tag/1">1 = pd.to_datetime(df['col2'], errors='coerce').notna()
m2 = df['col2'].notna()
Then pass it to numpy.select
- but is necessary convert NaN
to None
:
df['col2'] = np.select([mcom/tag/1">1, m2], [True, False], None)
print(df)
0 a False c
com/tag/1">1 b True b
2 c None b
3 b True b
Or use DataFrame.loc
:
df.loc[m2, 'col2'] = mcom/tag/1">1
print(df)
colcom/tag/1">1 col2 col3
0 a False c
com/tag/1">1 b True b
2 c NaN b
3 b True b
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manpreet
Best Answer
2 years ago
Output of above script is:
As to column
col2
,I want to convert allyyyy-mm-dd hh:mm
format string to boolTrue
,others toFalse
,keepNa
value as same.The expect result as below:
How to do it? Thanks in advance!