The purpose of this vignette is to display all high-level plots available in GGally to be used in particular with ggduo() and ggpairs(). The name of all the corresponding functions are of the form ggally_*(). Most of them accept a discrete variables to be passed to the colour aesthetic.

We can distinct bivariate plots requiring two variables for x and y axis respectively and diagonal plots when the same variable is plotted on x and y axis.

library(GGally, quietly = TRUE)
#> Registered S3 method overwritten by 'GGally':
#>   method from   
#>   +.gg   ggplot2
data(tips, package = "reshape")

Bivariate plots

with 2x continuous variables

ggally_autopoint()

ggally_autopoint(tips, aes(x = total_bill, y = tip))

ggally_autopoint(tips, aes(x = total_bill, y = tip, colour = time))

ggally_cor()

ggally_cor(tips, aes(x = total_bill, y = tip))

ggally_cor(tips, aes(x = total_bill, y = tip, colour = time))

See also ggally_statistic().

ggally_density()

ggally_density(tips, aes(x = total_bill, y = tip))

ggally_density(tips, aes(x = total_bill, y = tip, colour = time))

ggally_points()

ggally_points(tips, aes(x = total_bill, y = tip))

ggally_points(tips, aes(x = total_bill, y = tip, colour = time))

ggally_smooth(), ggally_smooth_lm() & ggally_smooth_loess()

ggally_smooth_lm(tips, aes(x = total_bill, y = tip))

ggally_smooth_lm(tips, aes(x = total_bill, y = tip, colour = time))


ggally_smooth_loess(tips, aes(x = total_bill, y = tip))

ggally_smooth_loess(tips, aes(x = total_bill, y = tip, colour = time))

See also ggally_smooth() for more options.

with 2x discrete variables

ggally_colbar()

ggally_colbar(tips, aes(x = day, y = smoker))

Note: the colour aesthetic is not taken into account.

ggally_autopoint()

ggally_autopoint(tips, aes(x = day, y = smoker))

ggally_autopoint(tips, aes(x = day, y = smoker, colour = time))

ggally_count()

ggally_count(tips, aes(x = day, y = smoker))

ggally_count(tips, aes(x = day, y = smoker, colour = time))

ggally_cross()

ggally_cross(tips, aes(x = day, y = smoker))

ggally_cross(tips, aes(x = day, y = smoker, colour = time))

ggally_cross(tips, aes(x = day, y = smoker, colour = smoker))

Note: colour aesthetic is taken into account only if it corresponds to x or to y.

ggally_crosstable()

ggally_crosstable(tips, aes(x = day, y = smoker))

ggally_crosstable(tips, aes(x = day, y = smoker), cells = "col.prop", fill = "stdres")

Note: colour aesthetic is not taken into account.

ggally_facetbar()

ggally_facetbar(tips, aes(x = day, y = smoker))

ggally_facetbar(tips, aes(x = day, y = smoker, colour = time))

ggally_ratio()

ggally_ratio(tips, aes(x = day, y = smoker))

ggally_ratio(tips, aes(x = day, y = smoker, colour = time))

ggally_rowbar()

ggally_rowbar(tips, aes(x = day, y = smoker))

Note: the colour aesthetic is not taken into account.

ggally_table()

ggally_table(tips, aes(x = day, y = smoker))

ggally_table(tips, aes(x = day, y = smoker, colour = time))

ggally_table(tips, aes(x = day, y = smoker, colour = smoker))

Note: colour aesthetic is taken into account only if it corresponds to x or to y.

with 1x continuous and 1x discrete variables

ggally_autopoint()

ggally_autopoint(tips, aes(x = total_bill, y = day))

ggally_autopoint(tips, aes(x = total_bill, y = day, colour = time))

ggally_box() & ggally_box_no_facet()

ggally_box(tips, aes(x = total_bill, y = day))

ggally_box(tips, aes(x = total_bill, y = day, colour = time))

ggally_box_no_facet(tips, aes(x = total_bill, y = day))

ggally_box_no_facet(tips, aes(x = total_bill, y = day, colour = time))

ggally_denstrip()

ggally_denstrip(tips, aes(x = total_bill, y = day))
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> Warning: Removed 45 rows containing missing values (geom_bar).

ggally_denstrip(tips, aes(x = total_bill, y = day, colour = time))
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> Warning: Removed 45 rows containing missing values (geom_bar).

ggally_dot() & ggally_dot_no_facet()

ggally_dot(tips, aes(x = total_bill, y = day))

ggally_dot(tips, aes(x = total_bill, y = day, colour = time))

ggally_dot_no_facet(tips, aes(x = total_bill, y = day))

ggally_dot_no_facet(tips, aes(x = total_bill, y = day, colour = time))

ggally_facetdensitystrip()

ggally_facetdensitystrip(tips, aes(x = total_bill, y = day))

ggally_facetdensitystrip(tips, aes(x = total_bill, y = day, colour = time))
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning: Removed 1 row(s) containing missing values (geom_path).

ggally_facethist()

ggally_facethist(tips, aes(x = total_bill, y = day))
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggally_facethist(tips, aes(x = total_bill, y = day, colour = time))
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggally_summarise_by()

ggally_summarise_by(tips, aes(x = total_bill, y = day))

ggally_summarise_by(tips, aes(x = total_bill, y = day, colour = day))

Note: colour aesthetic is kept only if corresponding to the discrete axis.

Diagonal plots

with 1x continuous variable

ggally_autopointDiag()

ggally_autopointDiag(tips, aes(x = total_bill))

ggally_autopointDiag(tips, aes(x = total_bill, colour = time))

ggally_barDiag()

ggally_barDiag(tips, aes(x = total_bill))
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggally_barDiag(tips, aes(x = total_bill, colour = time))
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggally_densityDiag()

ggally_densityDiag(tips, aes(x = total_bill))

ggally_densityDiag(tips, aes(x = total_bill, colour = time))

with 1x discrete variable

ggally_autopointDiag()

ggally_autopointDiag(tips, aes(x = day))

ggally_autopointDiag(tips, aes(x = day, colour = time))

ggally_barDiag()

ggally_barDiag(tips, aes(x = day))

ggally_barDiag(tips, aes(x = day, colour = time))

ggally_countDiag()

ggally_countDiag(tips, aes(x = day))

ggally_countDiag(tips, aes(x = day, colour = time))

ggally_densityDiag()

ggally_densityDiag(tips, aes(x = day))

ggally_densityDiag(tips, aes(x = day, colour = time))
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -
#> Inf

Additional plots