Performing EDA in Python

With your data loaded and cleaned, you can embark on your initial data exploration journey. This phase is crucial for gaining a deep understanding of your dataset, revealing its underlying patterns, and identifying potential areas of interest or concern.

These preliminary steps not only provide a solid foundation for your EDA but also help you uncover hidden patterns and relationships within your data. Armed with this initial understanding, you can proceed to more advanced data exploration techniques and dive deeper into the Excel dataset.

In the subsequent sections, we’ll delve into specific data exploration and visualization techniques to further enhance your insights into the dataset. With this knowledge, let’s move on to the next section, where we’ll explore techniques for understanding data distributions and relationships in greater detail.

Summary statistics

Begin by generating summary statistics for your dataset. This...