When you want to get to know and love your data

Visualizing the Iris Data

I’ve been working on additional scatter plot matrix plotting capabilities for the imCorrelations module.

Here is a little preview of a modified gpairs function from the YaleToolkit R package which is used to visualize the Iris data set. This scatterplot matrix allows for many interesting combinations of plots, which can be annotated with colors based on categorical variable(s).

The upper and lower matrix triangles can be modified with a variety of inputs:

  • scatterplots: points, best-fit-line, loess, qqplot for linear model residuals, best-fit-line confidence interval, correlation statistics
  • conditional plots: boxplot, stripplot, barcode

    Scatterplot matrix for overview of correlations and regressions, displaying box plots for Iris data species, variable histograms, correlation statistics, stripcharts and best fit lines.

This can be easily modified to rapidly visualize and overview variable dependencies.

Displaying Iris data, confidence intervals for best fit lines, residual quantile-quantile plots and variable barcode plots.

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