Exploratory Data Analysis Using SweetViz!

SweetViz is an open-source Python library that produces beautiful, highly detailed visualizations to start the EDA. It also covers all the result of a normal Pandas df.describe() method and much more. The output is a simple html file that you can download and open/use at your own convenience

Features of SweetViz:

Target analysis(optional) :

• Shows how a target variable associates with other variables.

Compare?:

• Can compare distinct dataset(training and testing)

Automatically detects numerical and categorical features

Association :

• Shows associations for numerical as well as categorical data

Statistical summary :

• Shows missing values, unique values, most frequent values,largest values,smallest values
• numerical summary: min,max,range, mean,median,mode,std deviation, skewness,IQR and much more

Getting Started:

Firstly we will install the SweetViz library:

!pip install sweetviz        

Setting up Dependencies:

import?pandas?as?pd
import?seaborn?as?sns
import?sweetviz?as?sv        

Loading the dataset, we will use planets dataset from the seaborn library:

#Loading?the?dataset
planets?=?sns.load_dataset('planets')
planets.head()        

Lets analyze our dataset:

#?Analyzing?the?dataset
report?=?sv.analyze(planets)


#?Display?the?report
report.show_html('planets.html')        

We can also explore the relation by clicking the Associations tab.

And its done. The EDA report is ready and it contains a lot of information for all the features. It is easy to understand and the report requires only a few lines of code.