I have tick data that I would like to refine by removing the first and last rows of each day. The original dataframe has a datetime64[ns] index with a format of '%Y-%m-%d %H:%M:%S'
To do so I used
pd.resample('D').first()
pd.resample('D').last()
and successfully sampled out the first and last rows of each day The problem is when resampling in days the original datetime index transforms into a '%Y-%m-%d' format
How do I use resample so that it retains the original datetime index format? or is there a way I can reformat datetime index in the new dataframe to display until seconds?
Your problem is that you are resampling daily and getting the first value per day. But that you want to include the associated date for that first value.
You want to aggregate the date in your index as well.
df.assign(NewDate=df.index).resample('D').first().set_index('NewDate')
Or you can resample the index and grab min values
df.loc[df.index.to_series().resample('D').min()]