compute_tabulate: Count data at each location of a categorical variable

In rpruim/ggvis2: Interactive grammar of graphics

Description

Count data at each location of a categorical variable

Usage

compute_tabulate(x, x_var, w_var = NULL)

Arguments

x	Dataset-like object to count. Built-in methods for data frames, grouped data frames and ggvis visualisations.
x_var,w_var	Names of x and weight variables.

Value

A data frame with columns:

count_	the number of points
x_	value of bin

See Also

compute_bin For counting cases within ranges of a continuous variable.

compute_count For counting cases at specific locations of a continuous variable. This is useful when the variable is continuous but the data is granular.

Examples

library(dplyr)
# The tabulated column must be countable (not numeric)
## Not run: mtcars %>% compute_tabulate(~cyl)
mtcars %>% mutate(cyl = factor(cyl)) %>% compute_tabulate(~cyl)

# Or equivalently:
mtcars %>% compute_tabulate(~factor(cyl))

# If there's one weight value at each x, it effectively just renames columns.
pressure %>% compute_tabulate(~factor(temperature), ~pressure)

# It doesn't matter whether you transform inside or outside of a vis
mtcars %>% compute_tabulate(~factor(cyl)) %>%
  ggvis(x = ~x_, y = ~count_, y2 = 0) %>%
  layer_rects(width = band())

mtcars %>%
  ggvis(x = ~x_, y = ~count_, y2 = 0) %>%
  compute_tabulate(~factor(cyl)) %>%
  layer_rects(width = band())

# compute_tabulate is used automatically in layer_bars when no y prop
# is supplied.
mtcars %>% ggvis(x = ~factor(cyl)) %>% layer_bars()

rpruim/ggvis2 documentation built on May 28, 2019, 2:34 a.m.