Transforming Scikit’s Bunch to DataFrame | Data Science Tutorial

In this tutorial, we will learn how to transform a Scikit-learn Bunch object into a Pandas DataFrame. This can be useful when working with machine learning models in Python and needing to convert output data into a more familiar format for further analysis and visualization.

Step 1: Import necessary libraries

        
import pandas as pd
from sklearn.datasets import load_boston

    

Step 2: Load the dataset using Scikit’s load_boston method

        
boston = load_boston()

    

Step 3: Transform the Bunch object into a Pandas DataFrame

        
data = pd.DataFrame(data=boston.data, columns=boston.feature_names)
target = pd.DataFrame(data=boston.target, columns=['target'])
df = pd.concat([data, target], axis=1)

    

And voila! Now you have transformed the Scikit-learn Bunch object into a Pandas DataFrame. You can now easily manipulate, analyze, and visualize the data using the powerful tools provided by Pandas.

This tutorial provides a simple and efficient way to convert your machine learning data into a more user-friendly format for further data science tasks. Happy coding!