Exploratory Data Analysis Using Python
In this tutorial, you’ll use Python and Pandas to explore a dataset and create visual distributions, identify and eliminate outliers, and uncover correlations between two datasets.
One of the most important parts of any Machine Learning (ML) project is performing Exploratory Data Analysis (EDA) to make sure the data is valid and that there are no obvious problems. EDA also helps you provide data-driven insights to business stakeholders before the project starts to ensure you’re asking the right questions.
In this tutorial, you’ll use Python and Pandas to:
- Explore a dataset and create visual distributions
- Identify and eliminate outliers
- Uncover correlations between two datasets
Creating an EDA is one of the first steps to building cleaner, more efficient machine learning and AI models. Read the tutorial and try it for yourself!