Getting started with EDA for Python
As explained earlier, EDA is the process of visually and statistically exploring datasets to uncover patterns, relationships, and insights. It’s a critical step before diving into more complex data analysis tasks. In this section, we’ll introduce you to the fundamentals of EDA and show you how to prepare your Python environment for EDA.
EDA is the initial phase of data analysis where you examine and summarize your dataset. The primary objectives of EDA are as follows:
- Understand the data: Gain insights into the structure, content, and quality of your data
- Identify patterns: Discover patterns, trends, and relationships within the data
- Detect anomalies: Find outliers and anomalies that may require special attention
- Generate hypotheses: Formulate initial hypotheses about your data
- Prepare for modeling: Preprocess data for advanced modeling and analysis
Before you can perform EDA, you’ll need to...
