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pandas drop duplicate keep last

df = df.sort_values('timestamp').drop_duplicates(['customer_id','var_name'], keep='last')
print (df)
   customer_id  value var_name                timestamp
0            1      1    apple  2018-03-22 00:00:00.000
3            1      1   orange  2018-03-22 08:00:00.000
2            2      4    apple  2018-03-24 08:00:00.000
4            2      3   orange  2018-03-24 08:00:00.000
Comment

pandas drop duplicates but keep most recent date

df.sort_values('DATE_CHANGED').drop_duplicates('STATION_ID',keep='last')
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