The best way to explore data is visually, using graphic representations. This process is called exploratory data analysis. Sometimes, this can be very difficult; for example, vizualizing Big Data can be tricky. Fortunately, we now have the processing power to work with very large, varied datasets. Still, it's up to us to choose a meaningful method of visualization. Some visualization types are more suited to certain datasets than others. So, let's take a look at the most common types of data visualizations.
We already know one way to visualize datasets: histograms. We'll now discuss when they should be used. Histograms are ideal for presenting large sets of quantitative elements, and they allow us to compare the sizes of specific value groupings. However, histograms observations must be presented as numbers, which limits their usage to displaying the underlying frequency distribution of a continuous dataset.
In the next exercises, you'll get a glimpse of other data visualizations.