In the previous post, “Tidy Data in Python – First Step in Data Science and Machine Learning”, we discussed the importance of the tidy data and its principles. In a Machine Learning project, once we have a tidy dataset in place, it is always recommended to perform EDA (Exploratory Data Analysis) on the underlying data before fitting it into a Machine Learning model. Let’s start understanding the importance of EDA and some basic EDA techniques which are very useful.
What is Exploratory Data Analysis (EDA)
Exploratory Data Analysis or EDA, is the process of organizing, plotting and summarizing the data to find trends, patterns, and outliers using statistical and visual methods. It takes input data from a tabular format and represents it in a graphical format which makes it more human interpretable. It is an important step in a Machine Learning/Data Science project which should be performed before … More