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EDA.md

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Exploratory Data Analysis


It's an approach to analyzing datasets to summarize it's characteristics and patterns.
It refers to the process of :-

  • discovering patterns
  • spotting anomalies
  • testing hypothesis
  • checking assumptions

Reasons for EDA

  • get a first look at the data
  • display the data so that the most interesting features become apparent
  • detection of errors
  • checking assumptions
  • preliminary selection of appropriate models
  • determining the relationship among input variables
  • assessing the direction and rough size of relationships between input and target variables

EDA techniques

The techniques are divide into graphical and quantitative techniques. Examples include:-

  • Histograms
  • Scatter plots
  • Pair plots
  • Box plots
  • Violin plots
  • Distribution plots