Mastering Exploratory Data Analysis (EDA) with Pandas 🐼

@genaiexp Exploratory Data Analysis (EDA) is a critical step in understanding your dataset. Pandas offers numerous tools for data exploration, including summary statistics using `df.describe()` and data visualization with libraries like Matplotlib and Seaborn. EDA allows you to uncover patterns, correlations, and anomalies in your data, guiding further analysis. Use Pandas to compute correlations with `df.corr()` or visualize data distributions with histograms. EDA not only provides insights into your dataset but also highlights areas that require further cleaning or adjustment. This foundational step is essential for effective data-driven decision making.