cpsievert

library(plotly)
library(crosstalk)
library(htmlwidgets)

mtcars %>% 
  SharedData$new() %>% 
  plot_ly(x = ~wt, y = ~mpg) %>% 
  highlight("plotly_selected", dynamic = TRUE) %>%
  onRender(
"function(el, x) {

cpsievert

accumulate_by <- function(dat, var, showLastFirst = FALSE) {
  var <- lazyeval::f_eval(var, dat)
  lvls <- plotly:::getLevels(var)
  dats <- lapply(seq_along(lvls), function(x) {
    cbind(dat[var %in% lvls[seq(1, x)], ], frame = lvls[[x]])
  })
  if (showLastFirst) {
    lastFrame <- dats[[length(dats)]]
    # you will likely have to fiddle with this value
    lastFrame$frame <- 0

cpsievert

cpsievert

# install.packages("plotly")

library(plotly)
library(htmlwidgets)

# grab some fake data from manhattanly
# note this is a data.frame!
# you can convert a matrix to a data frame with as.data.frame()
download.file("https://github.com/sahirbhatnagar/manhattanly/raw/master/data/HapMap.rda", "HapMap.rda")
load("HapMap.rda")

cpsievert

library(jsonlite)

txt <- '{
  "points": [{
  "curveNumber": 0, 
  "text": "a", 
  "pointNumber": 0, 
  "customdata": "c.a", 
  "y": 4, 
  "x": 1

cpsievert

library(dplyr)
library(tidyr)
library(readr)

# For other measures, see http://ghdx.healthdata.org/us-data
# TODO: do this on the county level for more interesting data, like this post - https://fivethirtyeight.com/features/mortality-black-belt/
obesity <- read_csv("http://ghdx.healthdata.org/sites/default/files/record-attached-files/IHME_USA_OBESITY_PHYSICAL_ACTIVITY_2001_2011.csv")

# reshape data so value tracks 
ob <- obesity %>%

cpsievert

library(shiny)
library(plotly)

# I keep a collection of my (plotly and non-plotly) apps here 
# https://github.com/cpsievert/apps
runGitHub("apps", "cpsievert", subdir = "shiny/apps/plotlyAg")
browseURL("https://github.com/cpsievert/apps/blob/master/shiny/apps/plotlyAg/app.R")

# The plotly package ships with some rmarkdown/shiny examples
browseURL("https://github.com/ropensci/plotly/tree/master/inst/examples")

cpsievert

{"x":{"data":[{"orientation":"v","width":[0.310344827586207,0.310344827586207,0.310344827586207,0.310344827586207,0.310344827586206,0.310344827586207,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586207,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206,0.310344827586206],"base":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"x":[0.931034482758621,1.24137931034483,1.55172413793103,1.86206896551724,2.17241379310345,2.48275862068966,2.79310344827586,3.10344827586207,3.41379310344828,3.72413793103448,4.03448275862069,4.3448275862069,4.6551724137931,4.96551724137931,5.27586206896552,5.58620689655172,5.89655172413793,6.20689655172414,6.51724137931035,6.82758620689655,7.13793103448276,7.448275862

cpsievert

library(plotly)

plot_ly(
  type = 'sankey',
  node = list(
    label =  c("a","b", "c", "d", "e", "f", "g", "h"),
    color =  c("black","black","black","black","black","black",
               "black","black"),
    pad = 15,
    thickness = 15,

cpsievert

library(grid)
(a <- arrow())
#> $angle
#> [1] 30
#> 
#> $length
#> [1] 0.25inches
#> 
#> $ends
#> [1] 2