Python | Pandas Series.between_time()
Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.between_time()
function select values between particular times of the day (e.g., 9:00-9:30 AM). By setting start_time to be later than end_time, you can get the times that are not between the two times.
Syntax: Series.between_time(start_time, end_time, include_start=True, include_end=True, axis=None)
Parameter :
start_time : datetime.time or string
end_time : datetime.time or string
include_start : boolean, default True
include_end : boolean, default True
axis : {0 or ‘index’, 1 or ‘columns’}, default 0Returns : values_between_time : same type as caller
Example #1: Use Series.between_time()
function to return the values lying in the given time duration.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 11 , 21 , 8 , 18 , 65 , 18 , 32 , 10 , 5 , 32 , None ]) # Create the Index index_ = pd.date_range( '2010-10-09 08:45' , periods = 11 , freq = 'H' ) # set the index sr.index = index_ # Print the series print (sr) |
Output :
Now we will use Series.between_time()
function to return the values lying in the given time duration.
# return values between the passed time duration result = sr.between_time(start_time = '10:45' , end_time = '15:45' ) # Print the result print (result) |
Output :
As we can see in the output, the Series.between_time()
function has successfully returned the values lying in the given time duration.
Example #2 : Use Series.between_time()
function to return the values lying in the given time duration. Skip the values corresponding to the start and end time.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 11 , 21 , 8 , 18 , 65 , 18 , 32 , 10 , 5 , 32 , None ]) # Create the Index index_ = pd.date_range( '2010-10-09 08:45' , periods = 11 , freq = 'H' ) # set the index sr.index = index_ # Print the series print (sr) |
Output :
Now we will use Series.between_time()
function to return the values lying in the given time duration. Skip the values corresponding to the start and end time.
# return values between the passed time duration # skip the start and end time result = sr.between_time(start_time = '10:45' , end_time = '15:45' , include_start = False , include_end = False ) # Print the result print (result) |
Output :
As we can see in the output, the Series.between_time()
function has successfully returned the values lying in the given time duration. Notice the values corresponding to the start and end time has not been included.
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