Pandas drop rows by time duration

Question

I would like to drop dataframe rows by time condition (ignoring date). My data contains around 100 million rows. I have around 100 columns and each column has different samp

Answer 1

by df=df.loc['2018-01-01 00:00:00.000000 ':'2018-01-01 00:00:00.000500 '] you will have new df witch data are between 2018-01-01 00:00:00.000000 and 2018-01-01 00:00:00.000500 now you can apply you filter for desire dates

import pandas as pd

# leave_duration=0.01 seconds
# drop_duration=0.1 seconds

i = pd.date_range('2018-01-01', periods=1000, freq='2ms')
i=i.append(pd.date_range('2018-01-01', periods=1000, freq='3ms'))
i=i.append(pd.date_range('2018-01-01', periods=1000, freq='0.5ms'))
df = pd.DataFrame({'A': range(len(i))}, index=i)
df=df.sort_index()
print(df)

#filter data between 2018-01-01 00:00:00.000000 ':'2018-01-01 00:00:00.000500
df=df.loc['2018-01-01 00:00:00.000000 ':'2018-01-01 00:00:00.000500 ']
print(df)

Output: Before data filter applied

                               A
2018-01-01 00:00:00.000000     0
2018-01-01 00:00:00.000000  2000
2018-01-01 00:00:00.000000  1000
2018-01-01 00:00:00.000500  2001
2018-01-01 00:00:00.001000  2002
...                          ...
2018-01-01 00:00:02.985000  1995
2018-01-01 00:00:02.988000  1996
2018-01-01 00:00:02.991000  1997
2018-01-01 00:00:02.994000  1998
2018-01-01 00:00:02.997000  1999

[3000 rows x 1 columns]

After date filter applied:

                               A
2018-01-01 00:00:00.000000     0
2018-01-01 00:00:00.000000  2000
2018-01-01 00:00:00.000000  1000
2018-01-01 00:00:00.000500  2001