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Best way to Explore Data using Interactive EDA Reports in Python – 2023

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Hey folks I hope you all are doing good, In today’s blog, we will see how we can Explore Data using Interactive EDA Report using the Pandas Profiling library. This library is a very useful library that can create amazing interactive EDA Reports n seconds and can save you much time and effort.

This is going to be a very interesting blog, so without any further due, let’s do it…

Snapshot of our final report…

Step 1 – Importing Required Libraries

import pandas as pd
from pandas_profiling import ProfileReport 

Step 2 – Importing Data.

df = pd.read_csv('UCI_Credit_Card.csv')
df.head()

Step 3 – Let’s Explore Data using Interactive EDA Report

print('Creating Profile Report...')

profile = ProfileReport(df)
profile.to_file("EDA.html")

print('Profile Report Created Successfully...')

Let’s visualize the generated EDA Report

https://machinelearningprojects.net/wp-content/uploads/2022/07/pandas-profiling-report.mkv
Explore Data using Interactive EDA Report

Now let’s interpret the EDA Report…

First of all, let’s see the DataSet Statistics

Let’s observe any one numerical column

NOTE – Observe the HIGH_CORRELATION written in Red under the column name. When you will take your cursor on that banner it will show some column names with which LIMIT_BAL is having high correlation.

Let’s observe any one categorical column

How to see more information about any column?

Let’s Visualize the Interactions

Let’s Visualize the Correlations

Let’s Visualize the Missing Values

Do let me know if there’s any query when you Explore Data using Interactive EDA Reports in Python.

So this is all for this blog folks, try to explore this EDA Report as much as possible. Thanks for reading it and I hope you are taking something with you after reading this and till the next time …

Read my previous post: How to train your first XGBoost model in Python

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