Plot Initial Dimensions (Active Variables) on a Multiple Correspondence Analyses

This function mostly have an educational value : it shows the initial dimensions of the Multiple Correspondence Analysis (active variables) in the space built by the analysis (principal axes). To see initial dimensions in their initial reference frame, use ggmca_initial_dims.

Usage

ggmca_with_base_ref(res.mca, data, axes = c(1, 2), keep = NULL)

Arguments

res.mca

An object created with FactoMineR::MCA.

data

The data the analysis was made on. Optional: this graph draws only active variables, which are read from `res.mca`, so it changes nothing. It is accepted so that every `ggmca_*` function takes `(res.mca, data)`.

axes

The axes to print, as a numeric vector of length 2.

keep

A character vector of the name of active variables to keep.

Value

A ggplot object to be printed in the `RStudio` Plots pane. Possibility to add other gg objects with +. Sending the result through ggi will draw the interactive graph in the Viewer pane using girafe.

Examples

# \donttest{
data(tea, package = "FactoMineR")
res.mca <- multiple_correspondence_analysis(tea, 1:18)
ggmca_with_base_ref(res.mca)
#> Warning: Removed 18 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 18 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 13 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 31 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 31 rows containing missing values or values outside the scale range
#> (`geom_segment()`).


# It is more readable to select just a few active variables
lv2_vars <- dplyr::select(tea[1:18], where(~ nlevels(.) == 2)) |> names()
ggmca_with_base_ref(res.mca, keep = lv2_vars)
#> Warning: Removed 13 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 13 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 13 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 26 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 26 rows containing missing values or values outside the scale range
#> (`geom_segment()`).


lv3_vars <- dplyr::select(tea[1:18], where(~ nlevels(.) == 3)) |> names()
ggmca_with_base_ref(res.mca, keep = lv3_vars)
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_segment()`).


lv4_vars <- dplyr::select(tea[1:18], where(~ nlevels(.) == 4)) |> names()
ggmca_with_base_ref(res.mca, keep = lv4_vars)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).


lv6_vars <- dplyr::select(tea[1:18], where(~ nlevels(.) == 6)) |> names()
ggmca_with_base_ref(res.mca, keep = lv6_vars)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).

# }