View source: R/transition-filter.R
transition_filter | R Documentation |
This transition allows you to transition between a range of filtering
conditions. The conditions are expressed as logical statements and rows in
the data will be retained if the statement evaluates to TRUE
. It is
possible to keep filtered data on display by setting keep = TRUE
which will
let data be retained as the result of the exit function. Note that if data is
kept the enter function will have no effect.
transition_filter(
transition_length = 1,
filter_length = 1,
...,
wrap = TRUE,
keep = FALSE
)
transition_length |
The relative length of the transition. Will be recycled to match the number of states in the data |
filter_length |
The relative length of the pause at the states. Will be recycled to match the number of states in the data |
... |
A number of expressions to be evaluated in the context of the layer data, returning a logical vector. If the expressions are named, the name will be available as a frame variable. |
wrap |
Should the animation wrap-around? If |
keep |
Should rows that evaluates to |
transition_filter
makes the following variables available for string
literal interpretation, in addition to the general ones provided by
animate()
:
transitioning is a boolean indicating whether the frame is part of the transitioning phase
previous_filter The name of the last filter the animation was at
closest_filter The name of the filter closest to this frame
next_filter The name of the next filter the animation will be part of
previous_expression The expression of the last filter the animation was at
closest_expression The expression of the filter closest to this frame
next_expression The expression of the next filter the animation will be part of
transition_filter
does not link rows across data to the same graphic
element, so elements will be defined uniquely by each row. If keep = TRUE
the rows not matching the conditions of a filter is not removed from the plot
after the exit animation, and a possible subsequent enter will begin from
the state they were left in, rather than enter anew from the state defined by
the enter function.
It is possible to use variables calculated by the statistic to define the
transition. Simply inclose the variable in stat()
in the same way as when
using computed variables in aesthetics.
Other transitions:
transition_components()
,
transition_events()
,
transition_layers()
,
transition_manual()
,
transition_null()
,
transition_reveal()
,
transition_states()
,
transition_time()
anim <- ggplot(iris, aes(Petal.Width, Petal.Length, colour = Species)) +
geom_point() +
transition_filter(
transition_length = 2,
filter_length = 1,
Setosa = Species == 'setosa',
Long = Petal.Length > 4,
Wide = Petal.Width > 2
) +
ggtitle(
'Filter: {closest_filter}',
subtitle = '{closest_expression}'
) +
enter_fade() +
exit_fly(y_loc = 0)
# Setting `keep = TRUE` allows you to keep the culled data on display. Only
# exit functions will be used in that case (as elements enters from the
# result of the exit function)
anim2 <- ggplot(iris, aes(Petal.Width, Petal.Length, colour = Species)) +
geom_point() +
transition_filter(
transition_length = 2,
filter_length = 1,
Setosa = Species == 'setosa',
Long = Petal.Length > 4,
Wide = Petal.Width > 2,
keep = TRUE
) +
ggtitle(
'Filter: {closest_filter}',
subtitle = '{closest_expression}'
) +
exit_recolour(colour = 'grey') +
exit_shrink(size = 0.5)
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