James Black epijim
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| getPckg <- function(pckg) install.packages(pckg, repos = "http://cran.r-project.org") | |
| pckg = try(require(wordcloud)) | |
| if(!pckg) { | |
| cat("Installing 'wordcloud' from CRAN\n") | |
| getPckg("wordcloud") | |
| require("wordcloud") | |
| } | |
| pckg = try(require(tm)) | |
| if(!pckg) { |
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| library("beanplot") | |
| #To make it do the split (male/female in my plot), I set a variable up as "MainGrouping" then | |
| # a space followed by BinaryGrouping encoded as a numeric value (i.e. 1 or 2). | |
| beanplot(ContinuousVariable ~ MainGrouping_BinaryGrouping, data = DATA, what=c(1,1,1,0), log="", | |
| ylab = "Continous variable label", side = "both", | |
| border = NA, beanlinewd = 0.5, overallline = "median", | |
| col = list( "brown2", "cadetblue3")) | |
| legend("topright", fill = c("brown2", "cadetblue3"), c("Binary 1", "Binary 2")) |
epijim
/ collegewealth.coffee
Created
November 5, 2013 12:50
D3.js bubble plot see vlandham/vlandham.github.com for source.
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| class BubbleChart | |
| constructor: (data) -> | |
| @data = data | |
| @width = 940 | |
| @height = 600 | |
| # locations the nodes will move towards | |
| # depending on which view is currently being | |
| # used |
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| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| svg { | |
| font: 10px sans-serif; | |
| } | |
| .axis path { | |
| display: none; |
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| parallelset <- function(..., freq, col="gray", border=0, layer, | |
| alpha=0.5, gap.width=0.05) { | |
| p <- data.frame(..., freq, col, border, alpha, stringsAsFactors=FALSE) | |
| n <- nrow(p) | |
| if(missing(layer)) { layer <- 1:n } | |
| p$layer <- layer | |
| np <- ncol(p) - 5 | |
| d <- p[ , 1:np, drop=FALSE] | |
| p <- p[ , -c(1:np), drop=FALSE] | |
| p$freq <- with(p, freq/sum(freq)) |
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| # ggplot2 base layer | |
| g <- ggplot(table) | |
| # Bubble plots - edit limits and seq based on your data | |
| (g + geom_point(aes(x = XAxis, y = YAxis, size = Percent, colour = total),shape=16, alpha=0.80) + | |
| scale_colour_gradient(limits = c(0, 1400), low="blue", high="red", breaks= seq(0, 1400, by = 200)) + | |
| scale_x_continuous(breaks = 1:4, labels=c("Category1", "Category2", "Category3","Category4")) + | |
| scale_y_continuous(trans = "reverse") + coord_fixed(ratio=0.2) | |
| ) |
epijim
/ sparklines.tex
Last active
December 29, 2015 15:19
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| \documentclass[12pt]{article} | |
| \usepackage{sparklines} % makes inline curves | |
| \begin{document} | |
| Ten-year modelled CVD risk was 27.3 (SD 13.9, histogram | |
| \begin{sparkline}{4} % start first sparkline | |
| \sparkspike .083 .69 % first is x spacing, second is height | |
| \sparkspike .25 .97 |
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| library(ggmap) | |
| getLineColor <- function(val) { | |
| #pal <- colorRampPalette(c("#333333", "#ffffff", "#b5310c")) | |
| pal <- colorRampPalette(c("#ffffff", "red")) | |
| colors <- pal(80) | |
| val.log <- log(val) | |
| if (val > 50) { | |
| col <- colors[80] |
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| setwd("Directoy where the data is saved") | |
| library(plyr) # used to read in csvs | |
| library(psych) # has the describe function | |
| ################ | |
| # import data # | |
| ################ | |
| # Data is in monthly CSV's, so loop over them pulling in data |
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| theme_bare <- theme(axis.line = element_blank(), | |
| axis.text.x = element_blank(), | |
| axis.text.y = element_blank(), | |
| axis.ticks = element_blank(), | |
| axis.title.x = element_blank(), | |
| axis.title.y = element_blank(), | |
| legend.position = "none") | |
| cambridge <- get_map(location="Cambridge, UK", zoom=13, color="bw", source="osm") |