plot_bars() Creates a bar plot based on one categorical variable and
one numeric variable. It can be used to show the results of a one-way trial
with qualitative treatments.
plot_factbars() Creates a bar plot based on two categorical
variables and one numeric variable. It can be used to show the results of a
two-way trial with qualitative-qualitative treatment structure.
plot_bars(
.data,
x,
y,
order = NULL,
y.lim = NULL,
y.breaks = waiver(),
y.expand = 0.05,
y.contract = 0,
xlab = NULL,
ylab = NULL,
n.dodge = 1,
check.overlap = FALSE,
color.bar = "black",
fill.bar = "gray",
lab.bar = NULL,
lab.bar.hjust = 0.5,
lab.bar.vjust = -0.5,
lab.bar.angle = 0,
size.text.bar = 5,
values = FALSE,
values.hjust = 0.5,
values.vjust = 1.5,
values.angle = 0,
values.digits = 2,
values.size = 4,
lab.x.hjust = 0.5,
lab.x.vjust = 1,
lab.x.angle = 0,
errorbar = TRUE,
stat.erbar = "se",
width.erbar = NULL,
level = 0.95,
invert = FALSE,
width.bar = 0.9,
size.line = 0.5,
size.text = 12,
fontfam = "sans",
na.rm = TRUE,
verbose = FALSE,
plot_theme = theme_metan()
)plot_factbars(
.data,
...,
resp,
y.lim = NULL,
y.breaks = waiver(),
y.expand = 0.05,
y.contract = 0,
xlab = NULL,
ylab = NULL,
n.dodge = 1,
check.overlap = FALSE,
lab.bar = NULL,
lab.bar.hjust = 0.5,
lab.bar.vjust = -0.5,
lab.bar.angle = 0,
size.text.bar = 5,
values = FALSE,
values.hjust = 0.5,
values.vjust = 1.5,
values.angle = 0,
values.digits = 2,
values.size = 4,
lab.x.hjust = 0.5,
lab.x.vjust = 1,
lab.x.angle = 0,
errorbar = TRUE,
stat.erbar = "se",
width.erbar = NULL,
level = 0.95,
invert = FALSE,
col = TRUE,
palette = "Spectral",
width.bar = 0.9,
legend.position = "bottom",
size.line = 0.5,
size.text = 12,
fontfam = "sans",
na.rm = TRUE,
verbose = FALSE,
plot_theme = theme_metan()
)
The data set.
Argument valid for plot_bars() The variables to be mapped
to the x and y axes, respectively.
Argument valid for plot_bars(). Controls the order of the
factor in the x axis. Defaults to the order of the factors in
.data. Use order = "asce" or order = "desc" to reorder
the labels to ascending or descending order, respectively, based on the
values of the variable y.
The range of y axis. Defaults to NULL (maximum and
minimum values of the data set). New values can be inserted as y.lim
= c(y.min, y.max).
The breaks to be plotted in the y-axis. Defaults to waiver().
authomatic breaks. The same arguments than x.breaks can be
used.
A multiplication range expansion/contraction
factor. y.expand expands the upper limit of the y escale, while
y.contract contracts the lower limit of the y scale. By default
y.expand = 0.05 and y.contract = 0 produces a plot without
spacing in the lower y limit and an expansion in the upper y limit.
The labels of the axes x and y, respectively. Defaults to
NULL.
The number of rows that should be used to render the x labels. This is useful for displaying labels that would otherwise overlap.
Silently remove overlapping labels, (recursively) prioritizing the first, last, and middle labels.
Argument valid for plot_bars(). The color and
fill values of the bars.
A vector of characters to show in each bar. Defaults to NULL.
The horizontal and vertical adjust for the labels in the bar. Defaults to 0.5 and -0.5, respectively.
The angle for the labels in the plot. Defaults to 0. Use
in combination with lab.bar.hjust and lab.bar.vjust to best
fit the labels in the plot.
The size of the text in the bar labels.
Logical argument. Shows the values in the plot bar?
Defaults to FALSE
The horizontal and vertical adjust
for the values in the bar. Defaults to 0.5 and 1.5, respectively. If
values = TRUE the values are shown bellow the error bar.
The angle for the labels in the plot. Defaults to 0.
Use in combination with values.hjust and values.vjust
to best fit the values in the plot bar.
The significant digits to show if values
= TRUE. Defaults to 2.
The size of the text for values shown in the bars.
Defaults to 3.
The horizontal and vertical adjust for the labels in the bar. Defaults to 0.5 and 1, respectively.
The angle for the labels in x axis. Defaults to 0. Use
in combination with lab.x.hjust and lab.x.vjust to best
fit the labels in the axis.
Logical argument, set to TRUE. In this case, an error bar is shown.
The statistic to be shown in the errorbar. Must be one of
the stat.erbar = "se" (standard error, default), stat.erbar =
"sd" (standard deviation), or stat.erbar = "ci" (confidence
interval), based on the confidence level in the argument level.
The width of the error bar. Defaults to 25% of
width.bar.
The confidence level
Logical argument. If TRUE, rotate the plot in
plot_bars() and invert the order of the factors in
plot_factbars().
The width of the bars in the graph. Defaults to 0.9. Possible values are in the range 0-1.
The size of the line in the bars. Default to 0.5.
The size of the text. Default to 12.
The family of the font text. Defaults to "sans".
Should 'NA' values be removed to compute the statistics? Defaults to true
Logical argument. If TRUE a tibble containing the mean, N, standard deviation, standard error of mean and confidence interval is returned.
The graphical theme of the plot. Default is
plot_theme = theme_metan(). For more details, see
theme.
Argument valid for plot_factbars(). A comma-separated list
of unquoted variable names. Sets the two variables to be mapped to the
x axis.
Argument valid for plot_factbars(). The response variable
to be mapped to the y axis.
Logical argument valid for plot_factbars(). If
FALSE, a gray scale is used.
Argument valid for plot_factbars() The color palette to
be used. For more details, see ?scale_colour_brewer
The position of the legend in the plot.
An object of class gg, ggplot.
# NOT RUN {
library(metan)
# two categorical variables
plot_factbars(data_ge2,
GEN,
ENV,
resp = PH)
# one categorical variable
p1 <- plot_bars(data_g, GEN, PH)
p2 <- plot_bars(data_g, GEN, PH,
n.dodge = 2, # two rows for x labels
y.expand = 0.1, # expand y scale
y.contract = -0.75, # contract the lower limit
errorbar = FALSE, # remove errorbar
color.bar = "red", # color of bars
fill.bar = alpha_color("cyan", 75), # create a transparent color
lab.bar = letters[1:13]) # add labels
arrange_ggplot(p1, p2)
# }
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