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` or
a proxy as returned by `echarts4rProxy` . |

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
)