So we’ll start off with four basic chart types, one for each of these value-encoding means. In his book Show Me the Numbers, Stephen Few suggests four major encodings for numeric values, indicating positional value via bars, lines, points, and boxes. Guidance on when to select each one based on use case is covered in a follow-up article. With these charts, you will have a broad toolkit to be able to handle your data visualization needs.

In this article, we’ll provide an overview of essential chart types that you’ll see most frequently offered by visualization tools. What are the types of metrics, features, or other variables that you plan on plotting? Who is the audience that you plan on presenting to – is it just an initial exploration for yourself, or are you presenting to a broader audience? What is the kind of conclusion that you want the reader to draw? Your choice of chart type will depend on multiple factors. Often, the most difficult part of creating a data visualization is figuring out which chart type is best for the task at hand. There are countless chart types out there, each with different use cases. Visualizations of data can bring out insights to someone looking at the data for the first time, as well as convey findings to others who won’t see the raw data. Charts are an essential part of working with data, as they are a way to condense large amounts of data into an easy to understand format.

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