Pandas DataFrame First Method

Introduction

In this lab, we will learn how to use the DataFrame.first() method in Pandas. The DataFrame.first() method selects the initial periods of time series data based on a date offset. This can be useful when working with a DataFrame that has dates as the index and you want to select the first few rows based on a specific date offset.

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Skills Graph

Import the necessary libraries

First, we need to import the pandas library, which we will use to work with the DataFrame.

import pandas as pd

Create a DataFrame with dates as the index

Next, let's create a DataFrame with dates as the index. We will use the pd.date_range() function to generate a range of dates and the pd.DataFrame() function to create the DataFrame.

i = pd.date_range('2021-01-01', periods=5, freq='D')
df = pd.DataFrame({'A': [1, 2, 3, 4, 5]}, index=i)

Use the DataFrame.first() method to select the first few rows

Now, we can use the DataFrame.first() method to select the first few rows based on a specific date offset. For example, if we want to select the first 3 days, we can use the following code:

df_first = df.first('3D')

Print the selected rows

Finally, let's print the selected rows from the DataFrame.

print(df_first)

Summary

In this lab, we learned how to use the DataFrame.first() method in Pandas to select the initial periods of time series data based on a date offset. This can be useful when working with a DataFrame that has dates as the index and you want to select the first few rows based on a specific date offset. By following the steps in this lab, you should now be able to use the DataFrame.first() method in your own data analysis tasks.