Exploratory Data Analysis(EDA) from scratch in Python!

Introduction

Exploratory Data Analysis

Exploratory Data Analysis(EDA)

– Handle Missing value
– Removing duplicates
– Outlier Treatment
– Normalizing and Scaling( Numerical Variables)
– Encoding Categorical variables( Dummy Variables)
– Bivariate Analysis

Exploratory Data Analysis - Import Libraries
Box-plot after removing outliers

Box-plot after removing outliers

  1. Exploratory Data Analysis - Data Shape

  2. Exploratory Data Analysis - Data Information

    Exploratory Data Analysis - Data Type

  3. Exploratory Data Analysis - Describe

Exploratory Data Analysis - Sum

Image for postExploratory Data Analysis - Impute Missing values

Exploratory Data Analysis - Impute Missing Values

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Handling Duplicate records

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Handling Outlier

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Box-plot before removing outliers

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Box-plot after removing outliers

Bivariate Analysis

  1. Two Categorical Variables

    1. Bar chart
    2. Grouped bar chart
    3. Point plot

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Correlation between all the variables

Normalizing and Scaling

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ENCODING

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About the Author

Ritika Singh – Data Scientist

I am a Data scientist by profession and a Blogger by passion. I have been working on machine learning projects for more than 2 years. Here you will find articles on “Machine Learning, Statistics, Deep Learning, NLP and Artificial Intelligence”.

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