James Curley jalapic

This is an example of creating what could be a legend for a heat map, demonstrating the simple use of a data-driven linear gradient with D3.

@jalapic did these really nice set of touch heatmap charts. On Twitter, there was a discussion how to do this interactively with d3.js or some other JavaScript. I definitely have some ideas how to accomplish this, but for now let's see how we can kind of do it in rbokeh. There is just a small issue with palette selection in Bokeh that does not let us allow a no color that prevents us from getting really close.

## https://gist.github.com/jalapic/3616c0197ece24060e99
library(rbokeh)
library(dplyr)

gana <- read.csv("https://gist.githubusercontent.com/jalapic/3616c0197ece24060e99/raw/2bc2361c5fceb9be80dece9b7ffa14d129a3edfb/gana.csv")

figure() %>%

	## reproduce the figures from http://www.jstatsoft.org/v28/c01/paper using ggplot2

	library(ggplot2)

	## parameters
	set.seed(2710)

	## Figure 1
	d <- rnorm(50)

	# This second example runs Trueskill on a tennis tournament, the Australian Open.
	# Note that actual computation is commented out as it takes about ~40 seconds to
	# update skill ratings over 127 matches.

	library(trueskill)

	# Data format of ausopen2012 is: Player, Opponent, Margin, Round, WRank, LRank
	data("ausopen2012")

	# create match_id in order to reshape

	library(dplyr)
	library(tidyr)
	library(magrittr)
	library(ggplot2)
	"http://academic.udayton.edu/kissock/http/Weather/gsod95-current/NYNEWYOR.txt" %>%
	read.table() %>% data.frame %>% tbl_df -> data
	names(data) <- c("month", "day", "year", "temp")

	data %>%
	group_by(year, month) %>%

	library(rvest)
	library(htmltools)
	library(pipeR)
	library("DiagrammeR")
	html('
	<ul class="ze_imagelist" style="width:925px;height:400px;" id="slideshowpj_widget_54da647bbdf7e"><li class="ze_thumb ze_type_image ze_item_number_1"><a class="ze_box" rel="prettyPhoto[pj_widget_54da647bbdf7e]" href="http://ec12.cdn.cincopa.com/SaltedCaramel2.jpg?o=1&res=76&cdn=ec&p=y&pid=231720&ph3=b2d1timslim1sat2p2lxtiganpc1chim&d=AMWAjFwULOAANQJsAMnyJRB&as=mp3" title="Salted Caramel - Our Signature Cookie<br />Our Signature Cookie! Caramel-infused dough loaded with Chocolate Chips and drizzled with Salted Caramel Sauce" style="width:190px;height:190px;"> <div class="ze_overlay"></div> <div id="pj_widget_54da647bbdf7e_0_thumbsplash" class="ze_item" style="width:190px;height:190px;"> <img class="ze_postar" style="height:190px;" src="http://ec12.cdn.cincopa.com/SaltedCaramel2.jpg?o=1&res=76&cdn=ec&p=y&pid=231720&ph3=b2d1timslim1sat2p2lxtiganpc1chim&d=AMWAjFwULOAANQJsAMnyJRB" t

	<!DOCTYPE html>
	<meta charset="utf-8">

	<style>
	body{
	margin: 0px;
	font: 10px sans-serif;
	}

	path.player{

	viridis_pal <- function(alpha=1) {
	function(n) {
	viridis(n, alpha)
	}
	}


	scale_color_viridis <- function(..., alpha=1, discrete=TRUE) {
	if (discrete) {
	discrete_scale("colour", "viridis", viridis_pal(alpha), ...)

	#' NBA Player Shot Chart
	#'
	#' @param player name the player, must be exact
	#' @param author, year_end_season: numeric end of season
	#'
	#' @return
	#' @export
	#'
	#' @examples boggie_bog <- plot_player_shot_chart(player = "Bojan Bogdanovic",
	#year_season_end = 2015, exclude_backcourt = T

	library(ggplot2)
	library(FField)

	# You'll have to play with repulsion, cex.x, and cex.y to get satisfactory results.
	plot_text <- function(x, y, label, repulsion = 1, cex.x = 110, cex.y = 40) {
	dat <- data.frame(xpos = x, ypos = y, label = label)
	dat$label <- as.character(dat$label)

	# Use the FField package to repel the text labels away from each other.
	dat <- cbind(