David Curran cavedave

## New google Logo
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUA
AAAFCAYAAACNbyblAAAAHElEQVQI12P4//8/w38GIAXDIBKE0DHxgljNBAAO
9TXL0Y4OHwAAAABJRU5ErkJggg=="/>

## StackedAreac3.html
<!doctype html>
<html lang="en">
 <head>

  <meta charset="UTF-8">
  <meta name="Generator" content="EditPlus®">
  <meta name="Author" content="">
  <meta name="Keywords" content="">
  <meta name="Description" content="">
  <title>Document</title>

## README.md

      
              5 files
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                cavedave
                / README.md
            
            
              Last active
              January 30, 2016 12:33
            
              
                Gist to make a Voronoi map of Irish Breweries
              
          
    Voronoi Maps

This project can be used to generate Voronoi maps using D3 and Leaflet.
This code was made by Chris Zeeter and the data comes from Beoir.org.
See an explanation of the code.
The code is released under the The MIT License.

  
## SFCrimeclock

#read in SF crime data is at https://www.kaggle.com/c/sf-crime/data
mydata = read.csv("train.csv")
library(dplyr)

#break up times

mydata$Year <- year(mydata$Dates)
mydata$Month <- month(mydata$Dates)
mydata$Hour <- hour(mydata$Dates)

## State Population
library(statebins)
library(dplyr)

#get population data from https://www.census.gov/popest/data/national/totals/2015/files/NST-EST2015-popchg2010_2015.csv

pop<-read.csv("NST.csv", header = TRUE, sep = ",", quote = "\"",dec = ".", fill = TRUE, comment.char = "")
#data wangling to get only states and cast as characters
pop15 <- select(pop, NAME, POPESTIMATE2015)
pop15s<-slice(pop15, 6:56)
pops<-rename(pop15s, c(NAME=state,POPESTIMATE2015=pop))

## Cartogram 50 States
library(statebins)
library(dplyr)
size<-read.csv("size.csv", header = TRUE, sep = ",", quote = "\"",dec = ".", fill = TRUE, comment.char = "")
i <- sapply(size, is.factor)
size[i] <- lapply(size[i], as.character)
sizeT <- mutate(size,areaT = round(area/1000))
statebins_continuous(sizeT,value_col="areaT",  text_color="black", font_size=3,legend_title = "50 States colored By Area", plot_title="US States Colored by 1000km squared",brewer_pal="PuRd",
                     legend_position="bottom",title_position="top")

csv is

## README.md

      
              5 files
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                cavedave
                / README.md
            
            
              Last active
              February 26, 2016 15:18
            
              
                Sankey graph for ge16
              
          
    This is a Sankey graph made using d3.js to show how votes transfer in the Irish General Election February 2016

  
## Wind Direction GGPlot2
#Download data from http://www.met.ie/climate-request/
# select the ddhm and the date columns.
data =read.csv("Dub2014.csv", header=TRUE)
newdata <- na.omit(data)

  ggplot(aes(ddhm)) +
    geom_histogram(binwidth = 10, colour = "blue")+
    theme_minimal() +
   coord_polar(start = 0) +
    scale_fill_brewer()  +  ylab("Wind Direction")+  xlab("ddhm: -   Mean Wind Direction")+

## slope.html
<!DOCTYPE html>

<!-- paulirish.com/2008/conditional-stylesheets-vs-css-hacks-answer-neither/ -->
<!--[if lt IE 7 ]> <html lang="en" class="no-js ie6"> <![endif]-->
<!--[if IE 7 ]>    <html lang="en" class="no-js ie7"> <![endif]-->
<!--[if IE 8 ]>    <html lang="en" class="no-js ie8"> <![endif]-->
<!--[if IE 9 ]>    <html lang="en" class="no-js ie9"> <![endif]-->
<!--[if (gt IE 9)|!(IE)]><!--> <html lang="en" class="no-js"> <!--<![endif]-->
<head>
  <meta charset="utf-8">

## Dragon.r
# library documentation at https://cran.r-project.org/web/packages/LindenmayeR/LindenmayeR.pdf
# L systems described here at https://en.wikipedia.org/wiki/L-system
#variables : X Y
#start  : FX
#rules  : (X → X+YF+), (Y → −FX−Y)
#constants : F + −
#angle  : 90°
# This doesnt work
library(LindenmayeR)
rSierp <- data.frame(inp = c("X", "Y"), out = c("X+YF+", "-FX−Y"), stringsAsFactors = FALSE)
	<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUA
	AAAFCAYAAACNbyblAAAAHElEQVQI12P4//8/w38GIAXDIBKE0DHxgljNBAAO
	9TXL0Y4OHwAAAABJRU5ErkJggg=="/>
	<!doctype html>
	<html lang="en">
	<head>

	<meta charset="UTF-8">
	<meta name="Generator" content="EditPlus®">
	<meta name="Author" content="">
	<meta name="Keywords" content="">
	<meta name="Description" content="">
	<title>Document</title>

	#read in SF crime data is at https://www.kaggle.com/c/sf-crime/data
	mydata = read.csv("train.csv")
	library(dplyr)

	#break up times

	mydata$Year <- year(mydata$Dates)
	mydata$Month <- month(mydata$Dates)
	mydata$Hour <- hour(mydata$Dates)
	library(statebins)
	library(dplyr)

	#get population data from https://www.census.gov/popest/data/national/totals/2015/files/NST-EST2015-popchg2010_2015.csv

	pop<-read.csv("NST.csv", header = TRUE, sep = ",", quote = "\"",dec = ".", fill = TRUE, comment.char = "")
	#data wangling to get only states and cast as characters
	pop15 <- select(pop, NAME, POPESTIMATE2015)
	pop15s<-slice(pop15, 6:56)
	pops<-rename(pop15s, c(NAME=state,POPESTIMATE2015=pop))
	library(statebins)
	library(dplyr)
	size<-read.csv("size.csv", header = TRUE, sep = ",", quote = "\"",dec = ".", fill = TRUE, comment.char = "")
	i <- sapply(size, is.factor)
	size[i] <- lapply(size[i], as.character)
	sizeT <- mutate(size,areaT = round(area/1000))
	statebins_continuous(sizeT,value_col="areaT", text_color="black", font_size=3,legend_title = "50 States colored By Area", plot_title="US States Colored by 1000km squared",brewer_pal="PuRd",
	legend_position="bottom",title_position="top")

	csv is
	#Download data from http://www.met.ie/climate-request/
	# select the ddhm and the date columns.
	data =read.csv("Dub2014.csv", header=TRUE)
	newdata <- na.omit(data)

	ggplot(aes(ddhm)) +
	geom_histogram(binwidth = 10, colour = "blue")+
	theme_minimal() +
	coord_polar(start = 0) +
	scale_fill_brewer() + ylab("Wind Direction")+ xlab("ddhm: - Mean Wind Direction")+
	<!DOCTYPE html>

	<!-- paulirish.com/2008/conditional-stylesheets-vs-css-hacks-answer-neither/ -->
	<!--[if lt IE 7 ]> <html lang="en" class="no-js ie6"> <![endif]-->
	<!--[if IE 7 ]> <html lang="en" class="no-js ie7"> <![endif]-->
	<!--[if IE 8 ]> <html lang="en" class="no-js ie8"> <![endif]-->
	<!--[if IE 9 ]> <html lang="en" class="no-js ie9"> <![endif]-->
	<!--[if (gt IE 9)\|!(IE)]><!--> <html lang="en" class="no-js"> <!--<![endif]-->
	<head>
	<meta charset="utf-8">
	# library documentation at https://cran.r-project.org/web/packages/LindenmayeR/LindenmayeR.pdf
	# L systems described here at https://en.wikipedia.org/wiki/L-system
	#variables : X Y
	#start : FX
	#rules : (X → X+YF+), (Y → −FX−Y)
	#constants : F + −
	#angle : 90°
	# This doesnt work
	library(LindenmayeR)
	rSierp <- data.frame(inp = c("X", "Y"), out = c("X+YF+", "-FX−Y"), stringsAsFactors = FALSE)