For an exhaustive, multi-faceted overview of all possible types of data visualization, visit the [DataViz Project (DVP)](https://datavizproject.com/#) or the [Data Visualization Catalogue (DVC)](https://datavizcatalogue.com/). And Nathan Yau (Flowing Data) has a [collection of chart types](https://flowingdata.com/chart-types). **Last but not least,** you have Cole Nussbaumer Knaflic's [Chart Guide](https://www.storytellingwithdata.com/chart-guide) on the [Storytelling with Data](https://www.storytellingwithdata.com) website. ## Types of plots, diagrams, and graphs Depending on the kind of data you whish to show, pick one: ### [Depict a single value](Depict%20a%20single%20value.md) ### [Capture distributions](Capture%20distributions.md) ### [Compare variables](Compare%20variables.md) ### [Display a trend](Display%20a%20trend.md) ### [Part-to-whole charts](Part-to-whole%20charts.md) ### [Visualize flow](Visualize%20flow.md) Source/Ref: [Datacamp's Data Visualization Cheat Sheet](https://www.datacamp.com/cheat-sheet/data-viz-cheat-sheet) ## What is the right graph for my situation? Now, create your visual and show it to a friend or colleague. Have them articulate the following as they process the information: 1. Where they focus, 1. what they see, 1. what observations they make, and 1. what questions they have. This will help you assess whether your visual is hitting the mark, or in the case where it isn’t, help you know where to concentrate your changes. Source/Ref: [Storytelling with Data](https://www.storytellingwithdata.com/books) by Cole Nussbaumer Knafilc