When to use Plotly? , R bloggers

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When to use Post Plotly? First appeared on finstats.

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If you are interested in learning more about Data Science, you can find more articles here.

When to use Plotly? As you can see, it has many features that make it exciting and fun to use.

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There are many situations where ggplot or plotly can be used, but the following elements make plotly a better choice.

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Graphs displayed electronically or online. Users must engage with the graph. Requires more customization than ggplot offers. The higher resolution must be used to render the visuals. Working with others in different languages ​​(eg, Python, Bash, Node, etc.). Creation of novel chart types (TreeMaps, Sunburst, Sankey, etc.).

The biggest drawbacks of Plotly are its complexity and insufficient documentation. Although it is a very powerful library, it is intended for a very technical audience.

Although their documentation has improved significantly over the past year, it can still be challenging (as of the writing of this article) for novice users to understand and locate the information they need.

Plotly Features

Plotly offers a wide range of sophisticated functions. You’ve already come across a handful of them!

The most common symptoms are:

When you hover over a tooltip, that information appears. The graph can be zoomed in or out. Graphs can be exported by users as images.

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Some of the more difficult ones include:

Joining different graphs together. Description on template hover. Animated scenes and animations. Incorporation of commercial coding environment.

Plotly has tons more features than that!

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If you’re already familiar with ggplot, you’ll be happy to know about the ggplotly function, which takes an existing ggplot graph and renders it using the plotly library.

Here’s an example using the same data we graphed earlier.

The ggplot2 package must be installed before running the following R code, so keep that in mind:

df <- mtcars df$name <- row.names(mtcars) P1 <- ggplot2::ggplot(data = df, aes(x=cyl, y=disp)) + geom_point(aes(color = factor(cyl)) ggplotly (P1)

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If you are interested in learning more about Data Science, you can find more articles here.

When to use Post Plotly? First appeared on finstats.

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