R Biplot Example

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R Biplot Example Csv
R Biplot Example
R Biplot Examples
R Biplot Pca Example

Source: R/ggplot_pca.R

Produces a ggplot2 variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base Rbiplot() function.

R offers two functions for doing PCA: princomp and prcomp, while plots can be visualised using the biplot function. However, the plots produced by biplot are often hard to read and the function lacks many of the options commonly available for customising plots.
Biplots can be interpreted as graphs in which observations are represented as points while, simultaneously, variables are represented as calibrated biplot axes. Such representations make it easy to visualise multivariate data in two or three dimensions.

Arguments

The biplot capitalizes on correlations between variables in reducing the dimensionality—for example, variables x and y in the scatterplot of Exhibit 0.1 appear to have high positive correlation and would be represented. An implementation of the biplot using ggplot2. The package provides two functions: ggscreeplot and ggbiplot.ggbiplot aims to be a drop-in replacement for the built-in R function biplot.princomp with extended functionality for labeling groups, drawing a correlation circle, and adding Normal probability ellipsoids.

x	an object returned by `pca()`, `prcomp()` or `princomp()`
choices	length 2 vector specifying the components to plot. Only the default is a biplot in the strict sense.
scale	The variables are scaled by `lambda ^ scale` and the observations are scaled by `lambda ^ (1-scale)` where `lambda` are the singular values as computed by `princomp`. Normally `0 <= scale <= 1`, and a warning will be issued if the specified `scale` is outside this range.
pc.biplot	If true, use what Gabriel (1971) refers to as a 'principal component biplot', with `lambda = 1` and observations scaled up by sqrt(n) and variables scaled down by sqrt(n). Then inner products between variables approximate covariances and distances between observations approximate Mahalanobis distance.
labels	an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the `pca()` function as input for `x`, this will be determined automatically based on the attribute `non_numeric_cols`, see `pca()`.
labels_textsize	the size of the text used for the labels
labels_text_placement	adjustment factor the placement of the variable names (`>=1` means further away from the arrow head)
groups	an optional vector of groups for the labels, with the same length as `labels`. If set, the points and labels will be coloured according to these groups. When using the `pca()` function as input for `x`, this will be determined automatically based on the attribute `non_numeric_cols`, see `pca()`.
ellipse	a logical to indicate whether a normal data ellipse should be drawn for each group (set with `groups`)
ellipse_prob	statistical size of the ellipse in normal probability
ellipse_size	the size of the ellipse line
ellipse_alpha	the alpha (transparency) of the ellipse line
points_size	the size of the points
points_alpha	the alpha (transparency) of the points
arrows	a logical to indicate whether arrows should be drawn
arrows_colour	the colour of the arrow and their text
arrows_size	the size (thickness) of the arrow lines
arrows_textsize	the size of the text at the end of the arrows
arrows_textangled	a logical whether the text at the end of the arrows should be angled
arrows_alpha	the alpha (transparency) of the arrows and their text
base_textsize	the text size for all plot elements except the labels and arrows
...	Arguments passed on to functions

R Biplot Example Csv

Source

The ggplot_pca() function is based on the ggbiplot() function from the ggbiplot package by Vince Vu, as found on GitHub: https://github.com/vqv/ggbiplot (retrieved: 2 March 2020, their latest commit: 7325e88; 12 February 2015).

R Biplot Example

As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:

Rewritten code to remove the dependency on packages plyr, scales and grid
Parametrised more options, like arrow and ellipse settings
Hardened all input possibilities by defining the exact type of user input for every argument
Added total amount of explained variance as a caption in the plot
Cleaned all syntax based on the lintr package, fixed grammatical errors and added integrity checks
Updated documentation

Details

The colours for labels and points can be changed by adding another scale layer for colour, like scale_colour_viridis_d() or scale_colour_brewer().

R Biplot Examples

Maturing Lifecycle

R Biplot Pca Example

The lifecycle of this function is maturing. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome to suggest changes at our repository or write us an email (see section 'Contact Us').