How to Get the values from the pandas series between a specific time?

PandasServer Side ProgrammingProgramming

The Pandas Series.between_time() method is used to select values between particular times of the day. The between_time() method takes two-time parameters and returns a series object with selected values.

The between_time method is similar to the at_time method of pandas series object, the at_time method selects the values at a particular time whereas The between_time method will select the values between times.

It will raise the TypeError if the index of the input series object is not a DatetimeIndex.

By default, both input time (start_time, end_time) parameters are inclusive, if you want to change that we can use include_start and include_end parameters.

Example 1

import pandas as pd

# create the index
index = pd.date_range('2021-01-1', periods=10, freq='20T')

#creating pandas Series with date time index
series = pd.Series([1,2,3,4,5,6,7,8,9,10], index=index)

print(series)

# selecting values by between_time()
print("Selecting values:", series.between_time("00:10","1:40"))

Explanation

Here, we have created a pandas.Series object by using the pandas DateTime index with some list of integer values. After that, we applied the between_time() method to get the values between times “00:10” to “1:40”.

If the specified times are present in the index of the given series object then it will return a new series object with collected values with those DateTime indexes.

Output

2021-01-01 00:00:00  1
2021-01-01 00:20:00  2
2021-01-01 00:40:00  3
2021-01-01 01:00:00  4
2021-01-01 01:20:00  5
2021-01-01 01:40:00  6
2021-01-01 02:00:00  7
2021-01-01 02:20:00  8
2021-01-01 02:40:00  9
2021-01-01 03:00:00 10
Freq: 20T, dtype: int64

Selecting values:
2021-01-01 00:20:00 2
2021-01-01 00:40:00 3
2021-01-01 01:00:00 4
2021-01-01 01:20:00 5
2021-01-01 01:40:00 6
Freq: 20T, dtype: int64

We have collected the values between the “00:10” to “1:40” times. In this example, start_time (“00:10”) and end_time (“1:40”) both are inclusive.

Example 2

import pandas as pd

# create the index
index = pd.date_range('2021-01-1', periods=10, freq='20T')

#creating pandas Series with date time index
series = pd.Series([1,2,3,4,5,6,7,8,9,10], index=index)

print(series)

# selecting values by between_time()
print("Selecting values:", series.between_time("00:40","1:40", include_start=False,include_end=False))

Explanation

In the following example, we have applied the between_time() method by not including the start and end times, which is done by providing the False value to the include_start and include_end parameters.

Output

2021-01-01 00:00:00  1
2021-01-01 00:20:00  2
2021-01-01 00:40:00  3
2021-01-01 01:00:00  4
2021-01-01 01:20:00  5
2021-01-01 01:40:00  6
2021-01-01 02:00:00  7
2021-01-01 02:20:00  8
2021-01-01 02:40:00  9
2021-01-01 03:00:00 10
Freq: 20T, dtype: int64

Selecting values:
2021-01-01 01:00:00 4
2021-01-01 01:20:00 5
Freq: 20T, dtype: int64

In this example, we have successfully selected the 2 rows from the given series object, these 3 rows are having the DateTime index time between "00:40", "1:40" both times are not inclusive.

raja
Updated on 09-Mar-2022 07:32:07

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