The R Graph Gallery boasts the most extensive compilation of R-generated graphs on the web. Featuring over 400 examples, our collection is meticulously organized into nearly 50 chart types, following the data-to-viz classification. Each example comes with reproducible code and a detailed explanation of its functionality.

From Data to Viz leads you to the most appropriate graph for your data. It links to the code to build it and lists common caveats you should avoid. What kind of data do you have? Pick the main type using the buttons below. Then let the decision tree guide you toward your graphic possibilities. Alternatively, check the complete decision tree.

The R package metaviz is a collection of functions to create visually appealing and information-rich plots of meta-analytic data using ggplot2. Currently functions to create several variants of forest plots (viz_forest) and funnel plots (viz_funnel, viz_sunset) are provided. See the function documentations for more details and relevant references.

2018年7月13日 · From Data to Viz is a classification of chart types based on input data format. It comes in the form of a decision tree leading to a set of potentially appropriate visualizations to represent the dataset.

Generic function to create a scatter plot of multivariate analyse outputs, including PCA, CA, MCA and MFA. X, element, axes = c(1, 2), geom = "auto", label = "all", invisible = "none", labelsize …

This function can be used to visualize the contribution of rows/columns from the results of Principal Component Analysis (PCA), Correspondence Analysis (CA), Multiple Correspondence Analysis (MCA), Factor Analysis of Mixed Data (FAMD), and …

Draw the graph of individuals/variables from the output of Principal Component Analysis (PCA). The following functions, from factoextra package are use: The package devtools is required for the installation as factoextra is hosted on github. Load factoextra : label = "all", invisible = "none", labelsize = 4, pointsize = 2, habillage = "none",

Visualizing data in R is great because… All the steps are in one place: data processing, analysis, and visualization. You can easily switch graph types to test out different presentations. It’s perfect for creating customized graphs.

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