Visual Map

e_visual_map(e, serie, calculable = TRUE, type = c("continuous",
  "piecewise"), scale = NULL, ...)

e_visual_map_(e, serie = NULL, calculable = TRUE,
  type = c("continuous", "piecewise"), scale = NULL, ...)

Arguments

e

An echarts4r object as returned by e_charts.

serie

Column name of serie to scale against.

calculable

Whether show handles, which can be dragged to adjust "selected range".

type

One of continuous or piecewise.

scale

A function that takes a vector of numeric and returns a vector of numeric of the same length.

...

Any other option to pass, check See Also section.

Scaling function

defaults to e_scale which is a basic function that rescales size between 1 and 20 for that makes for decent sized points on the chart.

See also

Examples

# scaled data mtcars %>% e_charts(mpg) %>% e_scatter(wt, qsec, scale = e_scale) %>% e_visual_map(qsec, scale = e_scale) # dimension # color according to y axis mtcars %>% e_charts(mpg) %>% e_scatter(wt) %>% e_visual_map(wt, dimension = 1) # color according to x axis mtcars %>% e_charts(mpg) %>% e_scatter(wt) %>% e_visual_map(mpg, dimension = 0) v <- LETTERS[1:10] matrix <- data.frame( x = sample(v, 300, replace = TRUE), y = sample(v, 300, replace = TRUE), z = rnorm(300, 10, 1), color = rnorm(300, 10, 1), size = rnorm(300, 10, 1), stringsAsFactors = FALSE ) %>% dplyr::group_by(x, y) %>% dplyr::summarise( z = sum(z), color = sum(color), size = sum(size) ) %>% dplyr::ungroup() matrix %>% e_charts(x) %>% e_scatter_3d(y, z, color, size) %>% e_visual_map( z, # scale to z inRange = list(symbolSize = c(1, 30)), # scale size dimension = 3 # third dimension 0 = x, y = 1, z = 2, size = 3 ) %>% e_visual_map( z, # scale to z inRange = list(color = c('#bf444c', '#d88273', '#f6efa6')), # scale colors dimension = 4, # third dimension 0 = x, y = 1, z = 2, size = 3, color = 4 bottom = 300 # padding to avoid visual maps overlap )