What is Exploratory Data Analysis?
Exploratory Data Analysis is nothing but just like the name suggests, is the method of studying and analyzing the data thoroughly before the final decision-making process. In exploratory data analysis, the data is analyzed mostly visually to summarize various characteristics of the given data set.
In simple terms, It’s just like choosing which movie to go to. Before going in for a movie, we tend to check the ratings and reviews and basic storylines, etc.. doing the same thing for a particular data set is what data analysts call as Exploratory Data Analysis.
So is Exploratory Data Analysis same as Data Analysis?
Well, technically both of them are the same thing. The difference lies in the way it’s done or the purpose for which it’s done.
When it comes to normal data analysis, most of the work done here are using various testing methods and algorithms whereas when it comes to exploratory data analysis, mostly visual representations such as bar graphs, scatter plots, histograms, etc. are used by the data analyst to understand the dataset at an even deeper level.
What are the types of Exploratory Data Analysis ?
All types of visual representations such as histograms, bar plots, scatter plots, multi-vari chart, etc. are a part of EDA. Some of the more widely used types would include:
- Principal Component Analysis (PCR)
- Multilinear Scaling
- Nonlinear Dimensionality Reduction (NLDR)
Exploratory data analysis is a powerful tool for any data analyst as it helps them provide a structured solution to simple organizational queries with easy visualizations before rushing into building complicated models.