Day 2 is all about understanding your data. Before we can build any model, we need to know what we're working with.
Loading Data with Pandas
Pandas is the go-to library for data manipulation in Python. We'll use it to load CSV files, inspect data types, and handle missing values.
Key EDA Techniques
Learn to use describe(), info(), and value_counts() to understand your data distribution. Visualize with histograms and scatter plots.
Today's Challenge
Download the Iris dataset and perform a complete EDA. Identify the features, target variable, and any patterns you notice.
