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/ Data_Science-EDA Public

A collection of useful implementations to perform EDA on a new dataset in order to understand preliminary patterns in the dataset and gain a high-level grasp of the dataset using plots and visualizations.

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Exploratory Data Analysis on Python

A collection of useful implementations to perform EDA on a new dataset in order to understand preliminary patterns in the dataset and gain a high-level grasp of the dataset using plots and visualizations

Python Version : 3.6.8 Virtual Environment : Anaconda 4.8.2

Topics for Reference

  • Exploratory Data Analysis

    1. QQplot
    2. BoxCoxTransform

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A collection of useful implementations to perform EDA on a new dataset in order to understand preliminary patterns in the dataset and gain a high-level grasp of the dataset using plots and visualizations.

Topics

distribution plots histogram eda statistical-analysis iris-dataset boxplots qqplot seaborn-plots violin-plots contour-plots

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