plot_ly: Initiate a plotly visualization
In gvarunkumar/plotly: Create Interactive Web Graphics via 'plotly.js'

Description Usage Arguments Details Author(s) See Also Examples

Transform data into a plotly visualization.

plot_ly(data = data.frame(), ..., type = NULL, group, color,
  colors = NULL, alpha = 1, symbol, symbols = NULL, size, sizes = c(10,
  100), linetype, linetypes = NULL, width = NULL, height = NULL,
  source = "A")

`data`	A data frame (optional).
`...`	These arguments are documented at https://plot.ly/r/reference/ Note that acceptable arguments depend on the value of `type`.
`type`	A character string describing the type of trace. If `NULL` (the default), the initial trace type is determined by `add_trace`
`color`	A formula containing a name or expression. Values are scaled and mapped to color codes based on the value of `colors` and `alpha`. To avoid scaling, wrap with `I()`, and provide value(s) that can be converted to rgb color codes by `col2rgb()`.
`colors`	Either a colorbrewer2.org palette name (e.g. "YlOrRd" or "Blues"), or a vector of colors to interpolate in hexadecimal "#RRGGBB" format, or a color interpolation function like `colorRamp()`.
`alpha`	A number between 0 and 1 specifying the alpha channel applied to color.
`symbol`	A formula containing a name or expression. Values are scaled and mapped to symbols based on the value of `symbols`. To avoid scaling, wrap with `I()`, and provide valid `pch()` values and/or valid plotly symbol(s) as a string
`symbols`	A character vector of symbol types. For possible values, see schema.
`size`	A variable name or numeric vector to encode the size of markers.
`sizes`	A numeric vector of length 2 used to scale sizes to pixels.
`linetype`	Either a variable name or a (discrete) vector to use for linetype encoding.
`linetypes`	A character vector of line types. For possible values, see schema.
`width`	Width in pixels (optional, defaults to automatic sizing).
`height`	Height in pixels (optional, defaults to automatic sizing).
`source`	Only relevant for event_data.

There are a number of "visual properties" that aren't included in the officical Reference section (see below).

Carson Sievert

layout(), add_trace(), style()

## Not run: 

# plot_ly() tries to create a sensible plot based on the information you 
# give it. If you don't provide a trace type, plot_ly() will infer one.
plot_ly(economics, x = ~pop)
plot_ly(economics, x = ~date, y = ~pop)
# plot_ly() doesn't require data frame(s), which allows one to take 
# advantage of trace type(s) designed specifically for numeric matrices
plot_ly(z = ~volcano)
plot_ly(z = ~volcano, type = "surface")

# plotly has a functional interface: every plotly function takes a plotly
# object as it's first input argument and returns a modified plotly object
add_lines(plot_ly(economics, x = ~date, y = ~unemploy/pop))

# To make code more readable, plotly imports the pipe operator from magrittr
economics %>% plot_ly(x = ~date, y = ~unemploy/pop) %>% add_lines()

# Attributes defined via plot_ly() set 'global' attributes that 
# are carried onto subsequent traces
plot_ly(economics, x = ~date, line = list(color = "black")) %>%
 add_trace(y = ~uempmed, mode = "markers+lines") %>%
 add_lines(y = ~psavert) %>%
 layout(title = "Setting global trace attributes")

# Attributes are documented in the figure reference -> https://plot.ly/r/reference
# You might notice plot_ly() has named arguments that aren't in the figure
# reference. These arguments make it easier to map abstract data values to
# visual attributes.
p <- plot_ly(iris, x = ~Sepal.Width, y = ~Sepal.Length) 
add_markers(p, color = ~Petal.Length, size = ~Petal.Length)
add_markers(p, color = ~Species)
add_markers(p, color = ~Species, colors = "Set1")
add_markers(p, symbol = ~Species)
add_paths(p, linetype = ~Species)


## End(Not run)