plotly (version 4.7.1)

plot_ly: Initiate a plotly visualization

Description

Transform data into a plotly visualization.

Usage

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

Arguments

data

A data frame (optional) or crosstalk::SharedData object.

...

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.

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 grDevices::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. Either valid pch or plotly symbol codes may be supplied.

size

A formula containing a name or expression yielding a numeric vector. Values are scaled according to the range specified in sizes.

sizes

A numeric vector of length 2 used to scale sizes to pixels.

linetype

A formula containing a name or expression. Values are scaled and mapped to linetypes based on the value of linetypes. To avoid scaling, wrap with I().

linetypes

A character vector of line types. Either valid par (lty) or plotly dash codes may be supplied.

split

A formula containing a name or expression. Similar to group_by(), but ensures at least one trace for each unique value. This replaces the functionality of the (now deprecated) group argument.

frame

A formula containing a name or expression. The resulting value is used to split data into frames, and then animated.

width

Width in pixels (optional, defaults to automatic sizing).

height

Height in pixels (optional, defaults to automatic sizing).

source

a character string of length 1. Match the value of this string with the source argument in event_data() to retrieve the event data corresponding to a specific plot (shiny apps can have multiple plots).

Details

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

See Also

• For initializing a plotly-geo object: plot_geo().

• For initializing a plotly-mapbox object: plot_mapbox().

• For translating a ggplot2 object to a plotly object: ggplotly().

• For modifying any plotly object: layout(), add_trace(), style()

Examples

# 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, but those may be over-written
plot_ly(economics, x = ~date, color = I("black")) %>%
 add_lines(y = ~uempmed) %>%
 add_lines(y = ~psavert, color = I("red"))

# Attributes are documented in the figure reference -> https://plot.ly/r/reference
# You might notice plot_ly() has named arguments that aren't in this 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)

# }
# NOT RUN {
# }