Hi Developer Community!
I have filtered my minute time series data frame by specific hours and minutes. The first Loop filters for 11:30 the second for 9:30. Lastly, I concatenated them next to each other.
Is there a way to do the same procedure without using an extra (second) loop? I would like to add more time and hour filters.
Thank you 
Yes, it is feasible to do it in one loop.
The code looks like this:
for i in range(len(majors_list)): temp = df_fixing[i][(df_fixing[i].index.hour==11) & (df_fixing[i].index.minute==30)] temp.index = temp.index.date df_fixing[i] = df_fixing[i][(df_fixing[i].index.hour==9) & (df_fixing[i].index.minute==30)] df_fixing[i].index = df_fixing[i].index.date df_fixing[i] = pd.concat([df_fixing[i], temp], axis=1)
thank you very much for your answer! This way of solution worked completely! Cheers!
Hi @levente.letenyei ,
One quick solution could simply be adding an OR component (df_fixing[i].index.hour == 9) in your first loop so the final code will look like this:
for i in range(len(majors_list)):
empty_list.append(df_fixing[i][((df_fixing[i].index.hour==11) | (df_fixing[i].index.hour == 9)) & (df_fixing[i].index.minute == 30)])
If you have noticed I have got rid of empty_list[i].index = empty_list[i].index.date to have the full datetime in the final list. And here is the final output:
empty_list[0]
Hope this helps.
Best regards,
Haykaz
Thank you ver much for your answer @h.aramyan ,
however I need the filtered minutes/hours data next to each other in new columns just like on the screenshot. Do you think it is feasible with one loop?
