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plot_scatter.R
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plot_scatter.R
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#' @title Plot (grouped) scatter plots
#' @name plot_scatter
#'
#' @description Display scatter plot of two variables. Adding a grouping variable to
#' the scatter plot is possible. Furthermore, fitted lines can be added
#' for each group as well as for the overall plot.
#'
#' @param data A data frame, or a grouped data frame.
#' @param x Name of the variable for the x-axis.
#' @param y Name of the variable for the y-axis.
#' @param grp Optional, name of the grouping-variable. If not missing, the
#' scatter plot will be grouped. See 'Examples'.
#' @param dot.labels Character vector with names for each coordinate pair given
#' by \code{x} and \code{y}, so text labels are added to the plot.
#' Must be of same length as \code{x} and \code{y}.
#' If \code{dot.labels} has a different length, data points will be trimmed
#' to match \code{dot.labels}. If \code{dot.labels = NULL} (default),
#' no labels are printed.
#' @param label.size Size of text labels if argument \code{dot.labels} is used.
#' @param fit.line,fit.grps Specifies the method to add a fitted line accross
#' the data points. Possible values are for instance \code{"lm"}, \code{"glm"},
#' \code{"loess"} or \code{"auto"}. If \code{NULL}, no line is plotted.
#' \code{fit.line} adds a fitted line for the complete data, while \code{fit.grps}
#' adds a fitted line for each subgroup of \code{grp}.
#' @param emph.dots Logical, if \code{TRUE}, overlapping points at same coordinates
#' will be becomme larger, so point size indicates amount of overlapping.
#' @param show.rug Logical, if \code{TRUE}, a marginal rug plot is displayed
#' in the graph.
#'
#' @return A ggplot-object. For grouped data frames, a list of ggplot-objects for
#' each group in the data.
#'
#' @inheritParams plot_model
#' @inheritParams plot_grpfrq
#'
#' @examples
#' # load sample date
#' library(sjmisc)
#' library(sjlabelled)
#' data(efc)
#'
#' # simple scatter plot
#' plot_scatter(efc, e16sex, neg_c_7)
#'
#' # simple scatter plot, increased jittering
#' plot_scatter(efc, e16sex, neg_c_7, jitter = .4)
#'
#' # grouped scatter plot
#' plot_scatter(efc, c160age, e17age, e42dep)
#'
#' # grouped scatter plot with marginal rug plot
#' # and add fitted line for complete data
#' plot_scatter(
#' efc, c12hour, c160age, c172code,
#' show.rug = TRUE, fit.line = "lm"
#' )
#'
#' # grouped scatter plot with marginal rug plot
#' # and add fitted line for each group
#' plot_scatter(
#' efc, c12hour, c160age, c172code,
#' show.rug = TRUE, fit.grps = "loess",
#' grid = TRUE
#' )
#'
#' @import ggplot2
#' @export
plot_scatter <- function(
data,
x,
y,
grp,
title = "",
legend.title = NULL,
legend.labels = NULL,
dot.labels = NULL,
axis.titles = NULL,
dot.size = 1.5,
label.size = 3,
colors = "metro",
fit.line = NULL,
fit.grps = NULL,
show.rug = FALSE,
show.legend = TRUE,
show.ci = FALSE,
wrap.title = 50,
wrap.legend.title = 20,
wrap.legend.labels = 20,
jitter = .05,
emph.dots = FALSE,
grid = FALSE
) {
# check available packages
if (!is.null(dot.labels) && !requireNamespace("ggrepel", quietly = TRUE)) {
stop("Package `ggrepel` needed to plot labels. Please install it.", call. = FALSE)
}
# get data
name.x <- deparse(substitute(x))
name.y <- deparse(substitute(y))
if (!missing(grp))
name.grp <- deparse(substitute(grp))
else
name.grp <- NULL
# optionally hide legend if not needed
if (!is.null(name.grp) && grid && missing(show.legend)) show.legend <- FALSE
pl <- NULL
if (inherits(data, "grouped_df")) {
# get grouped data
grps <- get_grouped_data(data)
# now plot everything
for (i in seq_len(nrow(grps))) {
# copy back labels to grouped data frame
tmp <- sjlabelled::copy_labels(grps$data[[i]], data)
# prepare argument list, including title
tmp.title <- get_grouped_plottitle(data, grps, i, sep = "\n")
# copy data
x <- tmp[[name.x]]
y <- tmp[[name.y]]
if (!is.null(name.grp))
grp <- tmp[[name.grp]]
else
grp <- NULL
# prepare color palette
if (!is.null(grp))
collen <- dplyr::n_distinct(grp, na.rm = TRUE)
else
collen <- 1
colors <- col_check2(colors, collen)
# plot
plots <- scatter_helper(
x, y, grp, title = tmp.title, legend.title, legend.labels, dot.labels, axis.titles,
dot.size, label.size, colors, fit.line, fit.grps, show.rug,
show.legend, show.ci, wrap.title, wrap.legend.title, wrap.legend.labels,
jitter, emph.dots, grid, name.x, name.y, name.grp
)
# add plots, check for NULL results
pl <- c(pl, list(plots))
}
} else {
# copy data
x <- data[[name.x]]
y <- data[[name.y]]
if (!is.null(name.grp))
grp <- data[[name.grp]]
else
grp <- NULL
# prepare color palette
if (!is.null(grp))
collen <- dplyr::n_distinct(grp, na.rm = TRUE)
else
collen <- 1
colors <- col_check2(colors, collen)
# plot
pl <- scatter_helper(
x, y, grp, title, legend.title, legend.labels, dot.labels, axis.titles,
dot.size, label.size, colors, fit.line, fit.grps, show.rug,
show.legend, show.ci, wrap.title, wrap.legend.title, wrap.legend.labels,
jitter, emph.dots, grid, name.x, name.y, name.grp
)
}
pl
}
#' @importFrom stats na.omit
#' @importFrom sjlabelled get_labels get_label
#' @importFrom sjmisc word_wrap
scatter_helper <- function(
x, y, grp, title, legend.title, legend.labels, dot.labels, axis.titles,
dot.size, label.size, colors, fit.line, fit.grps, show.rug,
show.legend, show.ci, wrap.title, wrap.legend.title, wrap.legend.labels,
jitter, emph.dots, grid, name.x, name.y, name.grp
) {
# any missing names?
if (is.null(name.x) || name.x == "NULL") name.x <- ""
if (is.null(name.y) || name.y == "NULL") name.y <- ""
# copy titles
if (is.null(axis.titles)) {
axisTitle.x <- NULL
axisTitle.y <- NULL
} else {
axisTitle.x <- axis.titles[1]
if (length(axis.titles) > 1)
axisTitle.y <- axis.titles[2]
else
axisTitle.y <- NULL
}
# try to automatically set labels is not passed as parameter
if (is.null(legend.labels) && !is.null(grp)) {
legend.labels <- sjlabelled::get_labels(
grp,
attr.only = F,
values = NULL,
non.labelled = T
)
}
if (is.null(legend.title) && !is.null(grp)) legend.title <- sjlabelled::get_label(grp, def.value = name.grp)
if (is.null(axisTitle.x)) axisTitle.x <- sjlabelled::get_label(x, def.value = name.x)
if (is.null(axisTitle.y)) axisTitle.y <- sjlabelled::get_label(y, def.value = name.y)
if (is.null(title)) {
t1 <- sjlabelled::get_label(x, def.value = name.x)
t2 <- sjlabelled::get_label(y, def.value = name.y)
if (!is.null(t1) && !is.null(t2)) {
title <- paste0(t1, " by ", t2)
if (!is.null(grp)) {
t3 <- sjlabelled::get_label(grp, def.value = name.grp)
if (!is.null(t3)) title <- paste0(title, " (grouped by ", t3, ")")
}
}
}
# remove titles if empty
if (!is.null(legend.title) && legend.title == "") legend.title <- NULL
if (!is.null(axisTitle.x) && axisTitle.x == "") axisTitle.x <- NULL
if (!is.null(axisTitle.y) && axisTitle.y == "") axisTitle.y <- NULL
if (!is.null(title) && title == "") title <- NULL
# create data frame
# check whether we have grouping variable
if (is.null(grp)) {
# if not, add a dummy grouping variable
grp <- rep(1, length(x))
# we don't need legend here
show.legend <- FALSE
}
# get value labels from attribute
grl <- sjlabelled::get_labels(grp, attr.only = T)
# simple data frame
dat <- stats::na.omit(data.frame(x = x, y = y, grp = grp))
# group as factor
dat$grp <- as.factor(dat$grp)
# set labelled levels, for facets
if (grid && !is.null(grl)) levels(dat$grp) <- grl
# do we have point labels?
if (!is.null(dot.labels)) {
# check length
if (length(dot.labels) > nrow(dat)) {
# Tell user that we have too many point labels
warning("More point labels than data points. Omitting remaining point labels", call. = F)
# shorten vector
dot.labels <- dot.labels[seq_len(nrow(dat))]
} else if (length(dot.labels) < nrow(dat)) {
# Tell user that we have too less point labels
warning("Less point labels than data points. Omitting remaining data point", call. = F)
# shorten data frame
dat <- dat[seq_len(length(dot.labels)), ]
}
# append labels
dat$dot.lab <- as.character(dot.labels)
}
# fix and wrap labels and titles
if (is.null(legend.labels)) legend.labels <- as.character(sort(unique(dat$grp)))
legend.labels <- sjmisc::word_wrap(legend.labels, wrap.legend.labels)
if (!is.null(legend.title)) legend.title <- sjmisc::word_wrap(legend.title, wrap.legend.title)
if (!is.null(title)) title <- sjmisc::word_wrap(title, wrap.title)
if (!is.null(axisTitle.x)) axisTitle.x <- sjmisc::word_wrap(axisTitle.x, wrap.title)
if (!is.null(axisTitle.y)) axisTitle.y <- sjmisc::word_wrap(axisTitle.y, wrap.title)
# Plot scatter plot
scp <- ggplot(dat, aes_string(x = "x", y = "y", colour = "grp"))
# add marginal rug
if (show.rug) {
scp <- scp + geom_rug(position = position_jitter(width = jitter))
}
# add data points
if (emph.dots) {
# indicate overlapping dots by point size
scp <- scp + geom_count(show.legend = F, position = position_jitter(width = jitter))
} else {
# else plot dots
scp <- scp + geom_jitter(size = dot.size, position = position_jitter(width = jitter))
}
# add labels
if (!is.null(dot.labels)) {
scp <- scp +
ggrepel::geom_text_repel(aes_string(label = "dot.lab"), size = label.size)
}
# Show fitted lines
if (!is.null(fit.grps)) {
scp <- scp +
stat_smooth(data = dat, aes_string(colour = "grp"), method = fit.grps, se = show.ci)
}
if (!is.null(fit.line)) {
scp <- scp +
stat_smooth(method = fit.line, se = show.ci, colour = "black")
}
# set font size for axes.
scp <- scp +
labs(title = title, x = axisTitle.x, y = axisTitle.y, colour = legend.title)
# facet plot
if (grid) scp <- scp + facet_wrap(~grp)
sj.setGeomColors(
scp,
colors,
length(legend.labels),
show.legend,
legend.labels
)
}