Automated Exploratory Data Analysis using Python

When working on different projects it used to become difficult for me to do Exploratory Data Analysis as it used to involve so many steps.So, I started using automatic EDAs which used to save a lot of time for me.

Please find below the EDAs that I generally use in my daily work.I hope it will help you in saving your time.

1. PANDAS PROFILING

We can install it using the command given below.

pip install pandas-profiling

We can import it using the command given below

from pandas_profiling import ProfileReport

We can execute it using the command given below

profile = ProfileReport(df)
profile

After execution , the report we look like

It has three main sections:

1.Overview-As the name suggest we get all the overview of the dataset in it like number of variables, variable types etc.

2.Warnings-It shows all the warning such like high cardinality ,missing, uniform and unique.

3.Variables:It shows us all the information related to each column in our dataset.

We can also get other informations like correlations.missing values count etc.

2. DATA PREP

We can install it using the command given below.

pip install dataprep

We can import it using the command given below

from dataprep.eda import plot

We can execute it using the command given below

plot(df)

After execution , the report we look like

Each graph is intractive which means we can get count, percntage of each data in the column

Thank you for your time and do let me know if you know any other automatic EDA libraries for python.