Data Frame EDA Packages Comparison: Pandas Profiling, Sweetviz, and PandasGUI

Which pandas data frame EDA packages suit you?

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As a data scientist, our work would always involve exploring data or often called Exploratory Data Analysis (EDA). The purposes of exploring data are to know our data better and grasp what we are dealing with.

Previously, exploring data using the pandas data frame is a big hassle because we need to code every single analysis from scratch. Not only it takes a lot of time, but it takes our mind focus as well.

Take an example of the mpg dataset below.

import pandas as pd
import seaborn as sns
mpg = sns.load_dataset('mpg')
mpg.head()

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While the data looks simple but to exploring this dataset would still take a lot of time.

Luckily, many great people already develop great packages to simplify the EDA process in our modern time. Examples of these packages are Pandas Profiling, Sweetviz, and PandasGUI.

Knowing many of the EDA packages out there, I am intrigued to see how they are compared to each other and which packages are…