ScatterPlot Visualization

ScatterPlot Visualization

n_scatter(
  data,
  x,
  y,
  entry_info = NULL,
  group = NULL,
  group_info = NULL,
  render = c("svg", "canvas"),
  ...,
  width = NULL,
  height = NULL,
  element_id = NULL
)

Arguments

data	data set in data.frame.
x, y	column names of x, y and z (if any, for size) value.
entry_info	column names of additional information for entries (point). Used to set the label or the size of the point, etc.
group	column name of group.
group_info	column names of additional information for groups (serie).
render	"svg" (responsive) or "canvas". "canvas" is well suited for large data sets as it does not impact DOM tree depth, however you'll lose the isomorphic rendering ability.
...	additional arguments.
width, height	Must be a valid CSS unit (like '100%', '400px', 'auto') or a number, which will be coerced to a string and have 'px' appended.
element_id	element id of widgets.

Value

a nivo ScatterPlot component

See also

Additional arguments

Examples

library(nivor)

# the simplest use
n_scatter(
  data = iris,
  x = "Sepal.Width",
  y = "Sepal.Length",
  group = "Species"
)

# an example of a slightly more complex setup
n_scatter(
  data = iris,
  x = "Sepal.Width",
  y = "Sepal.Length",
  group = "Species",
  margin = list(top = 60, right = 140, bottom = 70, left = 90),
  xFormat = htmlwidgets::JS('function(e){return e+" cm"}'),
  yFormat = htmlwidgets::JS('function(e){return e+" cm"}'),
  axisBottom = list(
    orient = "bottom",
    tickSize = 5,
    tickPadding = 5,
    tickRotation = 0,
    legend = "Sepal.Width",
    legendPosition = "middle",
    legendOffset = 46
  ),
  blendMode = "multiply",
  legends = list(
    list(
      anchor = "bottom-right",
      direction = "column",
      justify = FALSE,
      translateX = 130,
      translateY = 0,
      itemWidth = 100,
      itemHeight = 12,
      itemsSpacing = 5,
      itemDirection = "left-to-right",
      symbolSize = 12,
      symbolShape = "circle",
      effects = list(
        list(
          on = "hover",
          style = list(
            itemBackground = "rgba(0, 0, 0, .03)",
            itemOpacity = 1
          )
        )
      )
    )
  )
)

# Set additional information as size for each point
n_scatter(
  data = iris,
  y = "Sepal.Width",
  x = "Sepal.Length",
  entry_info = "Petal.Length",
  group = "Species",
  nodeSize = list(
    key = "Petal.Length",
    values = list(0, 4),
    sizes = list(9, 32)
  )
)