Pandas DataFrame Between_time Method

Introduction

In this lab, we will learn how to use the between_time() method in Pandas DataFrame. This method allows us to select values between particular times of the day. It can be used to filter and extract specific time-based data from a DataFrame.

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Import the necessary libraries

Before we can use the between_time() method, we need to import the necessary libraries. In this lab, we will be using the Pandas library.

import pandas as pd

Create a DataFrame

Next, let's create a DataFrame that contains time-based data. We can use the date_range() function from Pandas to generate a sequence of dates, and then set it as the index of the DataFrame.

values = pd.date_range('2021-01-01', periods=4, freq='20T')
df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [1, 2, 3, 4]}, index=values)

Select values between a specific time

Now that we have our DataFrame, let's use the between_time() method to select values between a specific start and end time. We can simply pass the start and end time as arguments to the method. The method will return a new DataFrame containing only the rows that fall between the specified times.

df_selected = df.between_time('00:00', '01:00')

Customize include_start and include_end parameters

The between_time() method also allows us to customize the include_start and include_end parameters. By default, these parameters are set to True, which means that the start and end times are included in the result.

df_selected = df.between_time('00:00', '01:00', include_start=False, include_end=False)

Handle non-DatetimeIndex error

If the index of the DataFrame is not a DatetimeIndex, the between_time() method will raise a TypeError. To avoid this error, make sure that the index of your DataFrame is a DatetimeIndex.

df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [1, 2, 3, 4]}, index=[1, 2, 3, 4])
## This will raise a TypeError
df_selected = df.between_time('00:00', '01:00')

Summary

In this lab, we learned how to use the between_time() method in Pandas DataFrame. This method allows us to select values between particular times of the day. We can customize the start and end times, as well as the inclusion of the start and end times, to filter and extract specific time-based data from a DataFrame. It is important to ensure that the index of the DataFrame is a DatetimeIndex to avoid TypeError errors. This method can be useful in various applications, such as analyzing time series data and extracting specific time periods from a dataset.