ggvis (version 0.4.4)

dplyr-ggvis: Dplyr verbs for ggvis.

Description

Applying a dplyr verb to a ggvis object creates a reactive transformation: whenever the underlying data changes the transformation will be recomputed.

Usage

# S3 method for ggvis
groups(x)
# S3 method for ggvis
group_by_(.data, ..., .dots, add = FALSE)
# S3 method for ggvis
ungroup(x)
# S3 method for ggvis
summarise_(.data, ..., .dots)
# S3 method for ggvis
mutate_(.data, ..., .dots)
# S3 method for ggvis
arrange_(.data, ..., .dots)
# S3 method for ggvis
select_(.data, ..., .dots)
# S3 method for ggvis
filter_(.data, ..., .dots)
# S3 method for ggvis
distinct_(.data, ..., .dots)
# S3 method for ggvis
slice_(.data, ..., .dots)
# S3 method for ggvis
rename_(.data, ..., .dots)
# S3 method for ggvis
transmute_(.data, ..., .dots)
# S3 method for reactive
groups(x)
# S3 method for reactive
ungroup(x)
# S3 method for reactive
group_by_(.data, ..., .dots, add = FALSE)
# S3 method for reactive
summarise_(.data, ..., .dots)
# S3 method for reactive
mutate_(.data, ..., .dots)
# S3 method for reactive
arrange_(.data, ..., .dots)
# S3 method for reactive
select_(.data, ..., .dots)
# S3 method for reactive
filter_(.data, ..., .dots)
# S3 method for reactive
distinct_(.data, ..., .dots)
# S3 method for reactive
slice_(.data, ..., .dots)
# S3 method for reactive
rename_(.data, ..., .dots)
# S3 method for reactive
transmute_(.data, ..., .dots)

Non-standard evaluation

Both dplyr and shiny do non-standard evaluation, so to help each package figure out when it should evaluate its code, reactive components in these functions must be wrapped in eval().

Examples

# NOT RUN {
library(dplyr)
base <- mtcars %>% ggvis(~mpg, ~cyl) %>% layer_points()
base %>% group_by(cyl) %>% summarise(mpg = mean(mpg)) %>%
  layer_points(fill := "red", size := 100)

base %>% filter(mpg > 25) %>% layer_points(fill := "red")

base %>% mutate(cyl = jitter(cyl)) %>% layer_points(fill := "red")

# }
# NOT RUN {
# Dynamically restrict range using filter
mtcars %>% ggvis(~disp, ~mpg) %>%
   filter(cyl > eval(input_slider(0, 10))) %>%
   layer_points()

# Dynamically compute box-cox transformation with mutate
bc <- function(x, lambda) {
  if (abs(lambda) < 1e-6) log(x) else (x ^ lambda - 1) / lambda
}
bc_slider <- input_slider(-2, 2, 1, step = 0.1)
mtcars %>%
 ggvis(~disp, ~mpg) %>%
 mutate(disp = bc(disp, eval(bc_slider))) %>%
 layer_points()
# }

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