7 Best Python Visualization Techniques for EDA: Enhance Insights
Discover the 7 best ways to visualize data distributions using Python. Learn about histograms, KDE plots, ridge plots, and more to enhance your EDA skills.
EDA usually involves examining the distribution of a dataset. Checking the dataset’s distribution helps identify the data range, outliers, central tendency, and skewness. This article introduces seven ways to present data distributions using Python:
Histograms
Kernel Density Estimation Plots (KDE Plots)
Joy Plots or Ridge Plots
Box Plots
Violin Plots
Strip and Swarm Plots
ECDF Plots