How to convert a Scikit-learn dataset to a Pandas dataset

If you have a dataset that you have loaded using Scikit-learn and you want to convert it to a Pandas dataframe, there are a few steps you can follow to accomplish this task.

1. First, import the necessary libraries:

<pre>
import pandas as pd
from sklearn import datasets
</pre>

2. Load the dataset using Scikit-learn:

<pre>
iris = datasets.load_iris()
</pre>

3. Create a Pandas dataframe from the dataset:

<pre>
df = pd.DataFrame(data=iris.data, columns=iris.feature_names)
</pre>

4. Add the target variable to the dataframe, if applicable:

<pre>
df['target'] = iris.target
</pre>

By following these steps, you can easily convert a Scikit-learn dataset to a Pandas dataframe and perform further analysis using Pandas’ powerful data manipulation capabilities.