Exploratory Data Analysis (EDA) has six main practices. The six main practices of EDA are discovering, structuring, cleaning, joining, validating and presenting. This post discusses the sixth practice, presenting. EDA is not a step-by-step process you follow like a recipe. It’s iterative and non-sequential.

Visualizing and presenting don’t necessarily come at the end of your data exploration. You may create visuals of your own data throughout the data analysis process. In fact, it is recommended that you create visuals at the beginning of your data analysis.

For example, you might want to create a histogram of a column of categorical data. Here’s an example from the post Histogram of Categorical Data that uses the Titanic dataset.