Plot standard Schola likert-like barplot with groupwise comparison per items
Source:R/barplot.R
schola_barplot.RdUsage
schola_barplot(
.data,
vars,
group,
dict = dict_from_data(.data),
escape_level = "nevím",
n_breaks = 11,
desc = TRUE,
labels = TRUE,
min_label_width = 0.09,
absolute_counts = TRUE,
fill_cols = NULL,
fill_labels = waiver(),
facet_label_wrap = 115,
reverse = FALSE,
order_by = "chi-square differences",
drop = FALSE,
drop_na = TRUE,
show.legend = TRUE,
...
)Arguments
- .data
data with items and group variable
- vars
vector of items, supports
{tidyselect}syntax (i.e, non-standard evaluation)- group
group variable used to split the results, have to be logical, where
TRUEis gonna be considered as "focal" group and displayed as upper group Supports{tidyselect}syntax.- dict
item code-label dictionary, if none provided, those are derived from the data.
- escape_level
character, level of item response considered as NA
- n_breaks
number of breaks displayed at x-axis, outer labels are automatically aligned to face inward. Defaults to 11, which results in 10% wide breaks.
- desc
sor items in descending order?
- labels
draw labels?
- min_label_width
smallest percentage (0-1) to display in the plot, proportions larger than this value are shown, smaller are not.
- absolute_counts
draw labels and absolute counts in parentheses?
- fill_cols
colors to be used for item categories, defaults to NULL, meaning standard RdYlBu palette will be used
- fill_labels
character vector or function taking breaks and returning labels for fill aesthetic
- facet_label_wrap
width of facet label to wrap
- reverse
if TRUE, reverse colors
- order_by
how to order the items. chi-square differences (default) computes chi-square test for every item and sort them by largest X2 statistic to smallest (if desc = TRUE)
- drop
Drop unobserved levels form the legend? Defaults to
FALSE. See ggplot2::discrete_scale for more details. To always show the legend key, make sure you haveshow.legendset toTRUEas well (as done by default).- drop_na
Drop
NAs from every item (a.k.a. "pairwise")? Defaults toTRUE. Note that the number of observations per item may differ, becauseNAin one item does not mean the respondent row is discarded completely (listwise).- show.legend
logical. Should this layer be included in the legends?
NA, the default, includes if any aesthetics are mapped.FALSEnever includes, andTRUEalways includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, useTRUE. IfNA, all levels are shown in legend, but unobserved levels are omitted.- ...
Arguments passed on to
fct_nanifynegatelogical, whether to return non-matching elements. Defaults to
FALSE.ignore_caselogical, ignore case when matching? Defaults to
TRUE.
See also
Other Making charts:
flush_axis,
plot_lollipop(),
prepare_lollipop_data(),
theme_schola()