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What is Exploratory Data Analysis with Seaborn about?

This document provides an overview of key techniques for exploratory data analysis (EDA) and data preprocessing, including: 1. Visualizing data distributions and relationships using Matplotlib and Seaborn libraries in Python. 2. Detecting and handling missing values and encoding categorical data. Common encoding techniques include one-hot encoding, label encoding, and ordinal encoding. 3. Standardizing data using min-max scaling and z-score normalization to center and normalize features.

Author

rhittum1802

Language

EN