View source: R/geom-miss-point.R
geom_miss_point | R Documentation |
geom_miss_point
provides a way to transform and plot missing
values in ggplot2. To do so it uses methods from ggobi to display missing
data points 10\
the same axis.
geom_miss_point(
mapping = NULL,
data = NULL,
prop_below = 0.1,
jitter = 0.05,
stat = "miss_point",
position = "identity",
colour = ..missing..,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
mapping |
Set of aesthetic mappings created by |
data |
A data frame. If specified, overrides the default data frame defined at the top level of the plot. |
prop_below |
the degree to shift the values. The default is 0.1 |
jitter |
the amount of jitter to add. The default is 0.05 |
stat |
The statistical transformation to use on the data for this layer, as a string. |
position |
Position adjustment, either as a string, or the result of a call to a position adjustment function. |
colour |
the colour chosen for the aesthetic |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
... |
other arguments passed on to
|
Warning message if na.rm = T
is supplied.
gg_miss_case()
gg_miss_case_cumsum()
gg_miss_fct()
gg_miss_span()
gg_miss_var()
gg_miss_var_cumsum()
gg_miss_which()
## Not run:
library(ggplot2)
# using regular geom_point()
ggplot(airquality,
aes(x = Ozone,
y = Solar.R)) +
geom_point()
# using geom_miss_point()
ggplot(airquality,
aes(x = Ozone,
y = Solar.R)) +
geom_miss_point()
# using facets
ggplot(airquality,
aes(x = Ozone,
y = Solar.R)) +
geom_miss_point() +
facet_wrap(~Month)
## End(Not run)
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