qbin_lineplot
creates quantile binned boxplots from data
using x
as the binning
variable and connects the medians: it focuses on the change of median between qbins.
qbin_lineplot(
data,
x = NULL,
n = 100,
min_bin_size = NULL,
ncols = NULL,
connect = TRUE,
color = "#002f2f",
fill = "#2f4f4f",
auto_fill = FALSE,
qmarker = NULL,
xmarker = NULL,
...
)
a data.frame
to be binned
character
variable name used for the quantile binning
integer
number of quantile bins.
integer
minimum number of rows/data points that should be
in a quantile bin. If NULL it is initially sqrt(nrow(data))
The number of column to be used in the layout
if TRUE
subsequent boxplots are connected
The color to use for the lines
The color to use for the bars
If TRUE
, use a different color for each category
numeric
, the quantile marker to use.
numeric
the x marker, i.e. the value for x that is translated into a q value.
Additional arguments to pass to the plot functions
A list
of ggplot objects.
The data is binned by the x
and a boxplot is created for each bin.
The median of the subsequent boxplots are connected to highlight jumps in the
data. It hints at the dependecy of the variable on the binning variable.
Other qbin plotting functions:
qbin_barplot()
,
qbin_boxplot()
,
qbin_heatmap()
qbin_lineplot(
iris,
x = "Sepal.Length",
)
#> `overlap` not specified, using `overlap=FALSE`
#> `min_bin_size`=12, using `n=12`
# \donttest{
qbin_lineplot(
iris,
x = "Sepal.Length",
xmarker = 5.5,
auto_fill = TRUE
)
#> `overlap` not specified, using `overlap=FALSE`
#> `min_bin_size`=12, using `n=12`
qbin_lineplot(
iris,
x = "Sepal.Length",
overlap=TRUE,
xmarker = 5.5,
auto_fill = TRUE
)
data("diamonds", package="ggplot2")
qbin_lineplot(
diamonds[1:7],
"carat",
auto_fill = TRUE
)
qbin_lineplot(
diamonds[1:7],
"price",
auto_fill = TRUE,
)
# }