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Exploratory Data Analysis In Python Beginners Guide For 2021

Avi Arora
Machine Learning | Computer Vision | Python | React.js | Data Science Writer
・1 min read

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As a common saying goes, it's often not the drawing that's the hard part; instead, it’s deciding what to draw that gets the best of most. Fortunately, once you've chosen, the rest isn't as hard as it might seem. The same is the case in data science, and the phase where you're deciding is what we refer to as EDA or Exploratory Data Analysis.

EDA plays the most pivotal role from acquiring the dataset to figuring out how to proceed with it and get your desired results.

So, in this article, we will be going through a beginner's guide to EDA. Don't worry if you're a complete newbie and just discovered EDA; by the end of the article, you will have a firm grasp on all the major concepts involved in EDA, along with a step-by-step, hands-on coding example. Let’s dig in!

Article Overview

  1. What is Exploratory Data Analysis?
  2. What is Univariate Analysis
  3. What is Bivariate Analysis
  4. A Hands-on Coding Example
  5. Wrap-Up

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