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Tuesday, 30 April 2019

Data Exploration and Visualization Techniques in Python

Data Exploration and Visualization is the first step in the process of creating a robust Machine Learning model. We need to understand and explore the data using various graphs and plots present in matplotlib and seaborn libraries. This step takes a lot of time and patience. 

Plots and graphs help us to analyze relationships among various variables present in the dataset. We can visualize and analyze missing values, outliers, skewed data, correlation among variables etc. 

Main Python libraries used in data exploration and visualization are pandasmatplotlib and seaborn.

There are mainly three types of plots: Univariate, Bivariate and Multivariate Analysis

Some commonly used plots and graphs are: Joint PlotDistribution PlotBox PlotBar PlotRegression PlotStrip PlotHeatmapViolin PlotPair Plot and GridFacet Grid.

Visualize missing values

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