Data visualization

Statistical tools for data analysis and visualization

Check out these 10 illustrative and powerful data visualizations in Python, R, Tableau and D3.js. All data visualization comes with open source code too.

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The ggdist package is a ggplot2 extension that is made for visualizing distributions and uncertainty. We'll show see how ggdist can be used to make a raincloud plot.

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Learn how to create a CORRELATION PLOT in R. Use the pairs and cpairs functions, the corrgram and corrplot packages and other alternatives

In my previous post, I showed how to use cdata package along with ggplot2‘s faceting facility to compactly plot two related graphs from the same data. This got me thinking: can I use cdata to produce a ggplot2 version of a scatterplot matrix, or pairs plot? A pairs plot compactly plots every (numeric) variable in … Continue reading Scatterplot matrices (pair plots) with cdata and ggplot2

This MATLAB function plots Pearson's correlation coefficients between all pairs of variables in the input matrix of time series data.

Scatter plots are used to display the relationship between two variables x and y. In this article, we’ll start by showing how to create beautiful scatter plots in R. We’ll use helper functions

To arrange multiple ggplot2 graphs on the same page, the standard R functions - par() and layout() - cannot be used. The basic solution is to use the gridExtra R package, which comes with the

To arrange multiple ggplot2 graphs on the same page, the standard R functions - par() and layout() - cannot be used. The basic solution is to use the gridExtra R package, which comes with the

I was wondering if there is a statistical model "cheat sheet(s)" that lists any or more information: when to use the model when not to use the model required and optional inputs expected outputs ha...