add_trace: Add trace(s) to a plotly visualization

Description Usage Arguments Author(s) References See Also Examples

View source: R/add.R

Description

Add trace(s) to a plotly visualization

Usage

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add_trace(p, ..., data = NULL, inherit = TRUE)

add_markers(p, x = NULL, y = NULL, z = NULL, ..., data = NULL,
  inherit = TRUE)

add_text(p, x = NULL, y = NULL, z = NULL, text = NULL, ...,
  data = NULL, inherit = TRUE)

add_paths(p, x = NULL, y = NULL, z = NULL, ..., data = NULL,
  inherit = TRUE)

add_lines(p, x = NULL, y = NULL, z = NULL, ..., data = NULL,
  inherit = TRUE)

add_segments(p, x = NULL, y = NULL, xend = NULL, yend = NULL, ...,
  data = NULL, inherit = TRUE)

add_polygons(p, x = NULL, y = NULL, ..., data = NULL,
  inherit = TRUE)

add_sf(p, ..., x = ~x, y = ~y, data = NULL, inherit = TRUE)

add_table(p, ..., rownames = TRUE, data = NULL, inherit = TRUE)

add_ribbons(p, x = NULL, ymin = NULL, ymax = NULL, ...,
  data = NULL, inherit = TRUE)

add_area(p, r = NULL, t = NULL, ..., data = NULL, inherit = TRUE)

add_pie(p, values = NULL, labels = NULL, ..., data = NULL,
  inherit = TRUE)

add_bars(p, x = NULL, y = NULL, ..., data = NULL, inherit = TRUE)

add_histogram(p, x = NULL, y = NULL, ..., data = NULL,
  inherit = TRUE)

add_histogram2d(p, x = NULL, y = NULL, z = NULL, ..., data = NULL,
  inherit = TRUE)

add_histogram2dcontour(p, x = NULL, y = NULL, z = NULL, ...,
  data = NULL, inherit = TRUE)

add_heatmap(p, x = NULL, y = NULL, z = NULL, ..., data = NULL,
  inherit = TRUE)

add_contour(p, z = NULL, ..., data = NULL, inherit = TRUE)

add_boxplot(p, x = NULL, y = NULL, ..., data = NULL,
  inherit = TRUE)

add_surface(p, z = NULL, ..., data = NULL, inherit = TRUE)

add_mesh(p, x = NULL, y = NULL, z = NULL, ..., data = NULL,
  inherit = TRUE)

add_scattergeo(p, ...)

add_choropleth(p, z = NULL, ..., data = NULL, inherit = TRUE)

Arguments

p

a plotly object

...

Arguments (i.e., attributes) passed along to the trace type. See schema() for a list of acceptable attributes for a given trace type (by going to traces -> type -> attributes). Note that attributes provided at this level may override other arguments (e.g. plot_ly(x = 1:10, y = 1:10, color = I("red"), marker = list(color = "blue"))).

data

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

inherit

inherit attributes from plot_ly()?

x

the x variable.

y

the y variable.

z

a numeric matrix

text

textual labels.

xend

"final" x position (in this context, x represents "start")

yend

"final" y position (in this context, y represents "start")

rownames

whether or not to display the rownames of data.

ymin

a variable used to define the lower boundary of a polygon.

ymax

a variable used to define the upper boundary of a polygon.

r

For polar chart only. Sets the radial coordinates.

t

For polar chart only. Sets the radial coordinates.

values

the value to associated with each slice of the pie.

labels

the labels (categories) corresponding to values.

Author(s)

Carson Sievert

References

https://plotly-r.com/overview.html

https://plot.ly/r

https://plot.ly/r/reference/

See Also

plot_ly()

Examples

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# the `plot_ly()` function initiates an object, and if no trace type
# is specified, it sets a sensible default
p <- plot_ly(economics, x = ~date, y = ~uempmed)
p

# some `add_*()` functions are a specific case of a trace type
# for example, `add_markers()` is a scatter trace with mode of markers
add_markers(p)

# scatter trace with mode of text
add_text(p, text = "%")

# scatter trace with mode of lines 
add_paths(p)

# like `add_paths()`, but ensures points are connected according to `x`
add_lines(p)

# if you prefer to work with plotly.js more directly, can always
# use `add_trace()` and specify the type yourself
add_trace(p, type = "scatter", mode = "markers+lines")

# mappings provided to `plot_ly()` are "global", but can be overwritten
plot_ly(economics, x = ~date, y = ~uempmed, color = I("red"), showlegend = FALSE) %>% 
  add_lines() %>%
  add_markers(color = ~pop)

# a number of `add_*()` functions are special cases of the scatter trace
plot_ly(economics, x = ~date) %>% 
  add_ribbons(ymin = ~pce - 1e3, ymax = ~pce + 1e3)

# use `group_by()` (or `group2NA()`) to apply visual mapping
# once per group (e.g. one line per group)
txhousing %>% 
  group_by(city) %>% 
  plot_ly(x = ~date, y = ~median) %>%
  add_lines(color = I("black"))

## Not run: 
# use `add_sf()` or `add_polygons()` to create geo-spatial maps
# http://blog.cpsievert.me/2018/03/30/visualizing-geo-spatial-data-with-sf-and-plotly/
if (requireNamespace("sf", quietly = TRUE)) {
  nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
  plot_ly() %>% add_sf(data = nc)
}

# univariate summary statistics
plot_ly(mtcars, x = ~factor(vs), y = ~mpg) %>% 
  add_boxplot()
plot_ly(mtcars, x = ~factor(vs), y = ~mpg) %>% 
  add_trace(type = "violin")
  
# `add_histogram()` does binning for you...
mtcars %>%
  plot_ly(x = ~factor(vs)) %>%
  add_histogram()
  
# ...but you can 'pre-compute' bar heights in R
mtcars %>%
  dplyr::count(vs) %>%
  plot_ly(x = ~vs, y = ~n) %>%
  add_bars()

# the 2d analogy of add_histogram() is add_histogram2d()/add_histogram2dcontour()
library(MASS)
(p <- plot_ly(geyser, x = ~waiting, y = ~duration))
add_histogram2d(p)
add_histogram2dcontour(p)

# the 2d analogy of add_bars() is add_heatmap()/add_contour()
# (i.e., bin counts must be pre-specified)
den <- kde2d(geyser$waiting, geyser$duration)
p <- plot_ly(x = den$x, y = den$y, z = den$z)
add_heatmap(p)
add_contour(p)

# `add_table()` makes it easy to map a data frame to the table trace type
plot_ly(economics) %>% 
  add_table()

# pie charts!
ds <- data.frame(labels = c("A", "B", "C"), values = c(10, 40, 60))
plot_ly(ds, labels = ~labels, values = ~values) %>%
  add_pie() %>%
  layout(title = "Basic Pie Chart using Plotly")
  
data(wind)
plot_ly(wind, r = ~r, t = ~t) %>% 
  add_area(color = ~nms) %>%
  layout(radialaxis = list(ticksuffix = "%"), orientation = 270)

# ------------------------------------------------------------
# 3D chart types
# ------------------------------------------------------------
plot_ly(z = ~volcano) %>% 
  add_surface()
plot_ly(x = c(0, 0, 1), y = c(0, 1, 0), z = c(0, 0, 0)) %>% 
  add_mesh()

## End(Not run)

plotly documentation built on May 2, 2019, 1:49 a.m.