Plot of the cloud of individuals

Plots a Multiple Correspondence Analysis cloud of individuals.

ggcloud_indiv(resmca, type = "i", points = "all", axes = c(1,2), 
col = "dodgerblue4", point.size = 0.5, alpha = 0.6,
repel = FALSE, text.size = 2,
density = NULL, col.contour = "darkred", hex.bins = 50, hex.pal = "viridis")

Arguments

resmca: object of class MCA, speMCA, csMCA, stMCA or multiMCA
type: If 'i', points are plotted. If 'inames', labels of individuals are plotted.
points: character string. If 'all' all points are plotted (default). If 'besth' only those who contribute most to horizontal axis are plotted. If 'bestv' only those who contribute most to vertical axis are plotted. If 'besthv' only those who contribute most to horizontal or vertical axis are plotted. If 'best' only those who contribute most to the plane are plotted.
axes: numeric vector of length 2, specifying the components (axes) to plot. Default is c(1,2).
col: If a factor, points or labels are colored according to their category regarding this factor. If a string with color name, every points or labels have the same color. Default is "dodgerblue4".
point.size: Size of the points of individuals. Default is 0.5.
alpha: Transparency of the points or labels of individuals. Default is 0.6.
repel: Logical. When type="inames"", should labels of individuals be repeled ? Default is FALSE.
text.size: Size of the labels of individuals. Default is 2.
density: If NULL (default), no density layer is added. If "contour", density is plotted with contours. If "hex", density is plotted with hexagon bins.
col.contour: character string. The color of the contours. Only used if density="contour".
hex.bins: integer. The number of bins in both vertical and horizontal directions. Only used if density="hex".
hex.pal: character string. The name of a viridis palette for hexagon bins. Only used if density="hex".

Value

a ggplot2 object

Details

Sometimes the dots are too many and overlap. It is then difficult to get an accurate idea of the distribution of the cloud of individuals. The density argument allows you to add an additional layer to represent the density of points in the plane, in the form of contours or hexagonal areas.

Note

If col argument is a factor, points or labels are colored according to the categories of the factor, using the default ggplot2 palette. The palette can be customized using any scale_color_* function, such as scale_color_brewer(), scale_color_grey() or scale_color_manual().

References

Le Roux B. and Rouanet H., Multiple Correspondence Analysis, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis, Kluwer Academic Publishers, Dordrecht (June 2004).

Author

Anton Perdoncin, Nicolas Robette

Examples

# specific MCA of Taste example data set
data(Taste)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA",
          "Comedy.NA", "Crime.NA", "Animation.NA", "SciFi.NA", "Love.NA", 
          "Musical.NA")
mca <- speMCA(Taste[,1:11], excl = junk)
# cloud of individuals
ggcloud_indiv(mca)

# points are colored according to gender
ggcloud_indiv(mca, col=Taste$Gender)

# a density layer of contours is added
ggcloud_indiv(mca, density = "contour")

# a density layer of hexagon bins is added
ggcloud_indiv(mca, density = "hex", hex.bin = 10)
#> Warning: Computation failed in `stat_binhex()`.
#> Caused by error in `compute_group()`:
#> ! The package "hexbin" is required for `stat_bin_hex()`.