I think you are looking for the likert function in the HH package.
>From ?likert
Diverging stacked barcharts for Likert, semantic differential, rating
scale data, and population pyramids.
This will get you started. Much more fine control is available. See
the examples and demo.
## install.packages("HH") ## if not yet on your system.
library(HH)
AA <- dfr[,-9]
labels <- sort(unique(as.vector(data.matrix(AA))))
result.template <- integer(length(labels))
names(result.template) <- labels
BB <- apply(AA, 2, function(x, result=result.template) {
tx <- table(x)
result[names(tx)] <- tx
result
}
)
BB
likert(t(BB), ReferenceZero=0, horizontal=FALSE)
On Tue, Mar 28, 2017 at 6:05 AM, <g.maub...@weinwolf.de> wrote:
> Hi All,
>
> in my current project I have to plot a whole bunch of related variables
> (item batteries, e.g. How do you rate ... a) Accelaration, b) Horse Power,
> c) Color Palette, etc.) which are all rated on a scale from 1 .. 4.
>
> I need to present the results as stacked bar charts where the variables
> are columns and the percentages of the scales values (1 .. 4) are the
> chunks of the stacked bar for each variable. To do this I have transformed
> my data from wide to long and calculated the percentage for each variable
> and value. The code for this is as follows:
>
> -- cut --
>
> dfr <- structure(
> list(
> v07_01 = c(3, 1, 1, 4, 3, 4, 4, 1, 3, 2, 2, 3,
> 4, 4, 4, 1, 1, 3, 3, 4),
> v07_02 = c(1, 2, 1, 1, 2, 1, 4, 1, 1,
> 4, 4, 1, 4, 4, 1, 3, 2, 3, 3, 1),
> v07_03 = c(3, 2, 2, 1, 4, 1,
> 2, 3, 3, 1, 4, 2, 3, 1, 4, 1, 4, 2, 2, 3),
> v07_04 = c(3, 1, 1,
> 4, 2, 4, 4, 2, 2, 2, 4, 1, 2, 1, 3, 1, 2, 4, 1, 4),
> v07_05 = c(1,
> 2, 2, 2, 4, 4, 1, 1, 4, 4, 2, 1, 2, 1, 4, 1, 2, 4, 1, 4),
> v07_06 = c(1,
> 2, 1, 2, 1, 1, 3, 4, 3, 2, 2, 3, 3, 2, 4, 2, 3, 1, 4, 3),
> v07_07 = c(3,
> 2, 3, 3, 1, 1, 3, 3, 4, 4, 1, 3, 1, 3, 2, 4, 1, 2, 3, 4),
> v07_08 = c(3,
> 2, 1, 2, 2, 2, 3, 3, 4, 4, 1, 1, 1, 2, 3, 1, 4, 2, 2, 4),
> cased_id = structure(
> 1:20,
> .Label = c(
> "1",
> "2",
> "3",
> "4",
> "5",
> "6",
> "7",
> "8",
> "9",
> "10",
> "11",
> "12",
> "13",
> "14",
> "15",
> "16",
> "17",
> "18",
> "19",
> "20"
> ),
> class = "factor"
> )
> ),
> .Names = c(
> "v07_01",
> "v07_02",
> "v07_03",
> "v07_04",
> "v07_05",
> "v07_06",
> "v07_07",
> "v07_08",
> "cased_id"
> ),
> row.names = c(NA, -20L),
> class = c("tbl_df", "tbl",
> "data.frame")
> )
>
> mdf <- melt(df)
> d_result <- mdf %>%
> dplyr::group_by(variable) %>%
> count(value)
>
> ggplot(
> d_result,
> aes(variable, y = n, fill = value)) +
> geom_bar(stat = "identity") +
> coord_cartesian(ylim = c(0,100))
>
> -- cut --
>
> Is there an easier way of doing this, i. e. a way without need to
> transform the data?
>
> How can I change the colors for the data points 1 .. 4?
>
> I tried
>
> -- cut --
>
> d_result,
> aes(variable, y = n, fill = value)) +
> geom_bar(stat = "identity") +
> coord_cartesian(ylim = c(0,100)) +
> scale_fill_manual(values = RColorBrewer::brewer.pal(4, "Blues"))
>
> -- cut -
>
> but this does not work cause I am mixing continuous and descrete values.
>
> How can I change the colors for the bars?
>
> Kind regards
>
> Georg
>
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
