Scatter-plot matrix — explore

A matrix of pairwise plots for a set of numeric variables: scatter plots below the diagonal, densities on the diagonal and correlation coefficients above the diagonal. Optionally colour everything by a grouping variable. Built with 'patchwork', so it shares the package theme and palette.

Usage

explore_pairs(
  data,
  cols = NULL,
  group = NULL,
  max_cols = 8,
  point_alpha = 0.5,
  method = c("pearson", "spearman", "kendall"),
  palette = NULL,
  title = NULL
)

Arguments

data: A data frame.
cols: Numeric columns to include, which cannot include group. If NULL, every numeric column other than group is used, so a frame with more than max_cols of them needs cols to choose among them.
group: Optional grouping variable mapped to colour, with each level in the same colour in every panel. A numeric code counts as a group, but a numeric column with more than 20 distinct values is refused as continuous. Rows with a missing group are dropped with a message, and levels without rows are left out of the plot and its palette.
max_cols: The largest number of variables accepted, since a k-by-k matrix grows quickly. More columns than this is an error, so the matrix never leaves a variable out without saying so.
point_alpha: Point transparency in the scatter panels.
method: Correlation method for the upper-triangle coefficients, passed to stats::cor(): "pearson", "spearman" or "kendall". A pair whose correlation is undefined (a constant column, or too few complete cases) is labelled n/a, as in correlation_heatmap().
palette: Colours for the groups; defaults to depictr_palette().
title: Overall title for the matrix.

Value

A 'patchwork' object (printable like a ggplot2::ggplot).

Examples

explore_pairs(crop_yield, cols = c("rainfall", "fertiliser", "yield"))

# \donttest{
explore_pairs(crop_yield, cols = c("rainfall", "fertiliser", "yield"),
              group = treatment, method = "spearman")

# }