Preparing for visualization

Before visualizing our data, it is important to get a glimpse of what the data looks like. This step basically involves inspecting our data to get a sense of the shape, data types, and type of information. Without this critical step, we may end up using the wrong visuals for analyzing our data. Visualizing data is never one size fits all because different charts and visuals require different data types and numbers of variables. This must always be factored in when visualizing data. Also, we may be required to transform our data before EDA; inspecting our data helps us identify whether transformation is required before proceeding to EDA. Lastly, this step helps us to identify whether there are additional variables that can be created from transforming or combining existing variables, such as in feature engineering.

In pandas, the head, dtypes, and shape methods are good ways to get a glimpse of our data.

Getting ready

We will work with one dataset...