When working on any data science project, one of the essential steps to explore and interpret your results is to visualize your data. At the beginning of the project, visualizing your data helps you understand it better, find patterns and trends.
At the end of the project, after you’ve done your analysis and applied different machine learning models, data visualization will help you communicate your results more efficiently.
Humans are visual creatures by nature; things make sense to us when it’s represented in an easy to understand visualization. It’s way easier to interpret a bar chart than it is to look at massive amounts of numbers in a spreadsheet.
Efficient data visualization can make or break your project. If you put tons of effort into analyzing and modeling your data, but you ended up using the wrong chart type to present your results, your audience will not grasp the effort you put in or how to use these results.
There are many chart types, so many, the process of choosing the correct one can be overwhelming and confusing. This article will — hopefully — give you a simple and straightforward approach to selecting the best chart type that represents your…
