Python Pandas: drop rows of a timeserie based on time range

Question

I have the following timeserie:

start = pd.to_datetime(\'2016-1-1\')
end = pd.to_datetime(\'2016-1-15\')
rng = pd.date_range(start, end, freq=\'2h\')
df = pd.Dat         


        

Answer 1

using query

df.query('index < @start_remove or index > @end_remove')

using loc

df.loc[(df.index < start_remove) | (df.index > end_remove)]

using date slicing

This includes the end points

pd.concat([df[:start_remove], df[end_remove:]])

And without the end points

pd.concat([df[:start_remove], df[end_remove:]]).drop([start_remove, end_remove])