Pandas DataFrame Filter Method

Introduction

In this lab, we will learn how to use the filter() method in the Pandas DataFrame. The filter() method allows us to subset the rows or columns of a DataFrame based on specified index labels. It is important to note that this method filters the DataFrame based on the labels of the index, not the content of the DataFrame.

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Skills Graph

Create a DataFrame

First, let's create a sample DataFrame to work with.

#import pandas as pd
import pandas as pd

#creating DataFrame
df=pd.DataFrame({
    "Name":["Navya","Vindya","Sinchana","Amrutha","Akshatha"],
    "Age":[25,24,25,25,26],
    "Education":["M.Tech","M.Tech","M.Tech","Ph.d","Ph.d"],
    "YOP":[2019,2020,2018,None,None]},
    index=["Group_1", "Group_1","Group_1","Group_2","Group_2"])

#printing DataFrame
print("-------DataFrame is----------")
print(df)

Filter by column names using the filter() method

We can use the items parameter of the filter() method to filter the DataFrame by certain columns.

#filter by column names
filtered_df = df.filter(items=["Name","Education"])

#printing filtered DataFrame
print("---------Filtered DataFrame---------")
print(filtered_df)

Filter by row names using the filter() method

We can use the like parameter of the filter() method to filter the DataFrame by certain rows.

#filter by row names
filtered_df = df.filter(like='Group_2', axis=0)

#printing filtered DataFrame
print("---------Filtered DataFrame---------")
print(filtered_df)

Filter by column names with the regex parameter

We can use the regex parameter of the filter() method to filter the DataFrame by certain columns based on a regular expression.

#filter by column names with regex
filtered_df = df.filter(regex ='[g]')

#printing filtered DataFrame
print("---------Filtered DataFrame---------")
print(filtered_df)

Summary

In this lab, we learned how to use the filter() method in the Pandas DataFrame. We covered how to filter the DataFrame by column names and row names, as well as how to filter based on a regular expression. This method is useful for subsetting the DataFrame based on specific index labels.