Automating Exploratory Data Analysis and Modelling Data

Exploratory Data Analysis is the most crucial part, to begin with whenever we are working with a dataset. It allows us to analyze the data and works on initial findings from the data. EDA is an approach where we summarize the main characteristics of the data using different methods and mainly visualization. Before modeling the data should be analyzed, cleaned, and clearly understood in order to make modeling suceessful.

EDA takes us most of the time as we have to clearly analyze the data so that we can clean it and visualize the data to preprocess it before modelling. This is whuy EDA is most important but we can save this time by automating all the time taking EDA jobs and can use the time saved in modelling.

Dora is an open-source python library used to automate the painful parts of the Exploratory Data Analysis. It simply cleans your data, allows you to visualize, and not only this it also allows you to prepare your data for the modelling purpose.

In this article, we will explore dora and see what all different functionalities it provides us with.

#machine-learning #data-visualization #data-analysis #data-science #python