Prabhas Pokharel prabhasp

[ Launch: pnc-schedules ] 5795197 by prabhasp

[ Launch: pnc-schedules ] 5797583 by prabhasp[ Launch: pnc-schedules ] 5795197 by prabhasp

Nr	NAME OF THE PROJECT	AREA	IMPLEMENTATION START	IMPLEMENTATION END	ADDENDUMS
1	Find your polling Station (finished)	Social/Technology	22/11/2010	02/03/2011
2	OSM Handbook (finished)	Technology	12/03/2010	31/03/2011
3	Follow The Stars (finished)	Social/Arts/Culture	02/01/2011	15/06/2011
4	Our Virtual City on 3D (finished)	Technology	02/02/2011	18/04/2011
5	Our Eye (finished)	Education/Social	03/03/2011	05/10/2011	15/12/2011
6	Say NO to plastic bags (finished)	Environment	03/03/2011	30/05/2011
7	Art Gallery for blind Artists (finished)	Social/Arts	15/03/2011	15/04/2011
8	E-career Guidelines	Education/Social	28/03/2011	26/04/2012
9	Recycle smART (finished)	Environment/Arts	20/04/2011	07/04/2011

	<!DOCTYPE html>
	<!-- saved from url=(0014)about:internet -->
	<html>
	<head>
	<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>

	<title>How to make choropleth maps with R</title>

	<style type="text/css">
	body, td {

	We'll be checking whether the top 100 users of formhub follow a power law distribution, or a log-normal distribution, using guidance from [a blog post by CMU stats prof. Cosma Rohilla Shaliz](http://vserver1.cscs.lsa.umich.edu/~crshalizi/weblog/857.html).

	First, load up the dataset; I have included it here in case you want to re-produce it. Each value is a number of submissions on formhub for top 100 users.

	```{r}
	source("~/Downloads/pli-R-v0.0.3-2007-07-25/pareto.R")
	source("~/Downloads/pli-R-v0.0.3-2007-07-25/lnorm.R")
	source("~/Downloads/pli-R-v0.0.3-2007-07-25/power-law-test.R")

	users <- c(220346L, 31099L, 28568L, 16573L, 14862L, 7531L, 6510L, 6138L,

	setwd("~/Dropbox/FINAL CONPEDIUM OF LOCALITIES/")
	require(gdata)

	l <- list.files()
	l <- l[which(str_detect(l, "\\.xls"))]

	listofdfs <- llply(l, function(fname) {
	print(paste("Reading file:", fname))
	tryCatch({
	d <- read.xls(fname)

	<p><link href="http://kevinburke.bitbucket.org/markdowncss/markdown.css" rel="stylesheet"></link></p>
	Analyzing bamboo bechmarks--2013/3/13
	=====================================
	Please refer to the generating index.Rmd file if you want to look at the code that generated this file. It should be in the same folder as index.html (which you are seeing now); most R code will be hidden for prettiness.
	```{r warning=FALSE, message=FALSE, echo=FALSE}
	library(lubridate)
	library(reshape2)
	library(ggplot2)
	library(plyr)
	# Read in data

	[
	{
	"source": "Education_113_ALL_FACILITY_INDICATORS.csv",
	"target": "nmis_indicators_education_lga_level_113.R"
	},
	{
	"source": "lgas.csv",
	"target": "nmis_indicators_education_lga_level_113.R"
	},
	{

	---
	title : Two tools for reproducible data work
	subtitle :
	author : Prabhas Pokharel, Modi Research Group
	job :
	framework : io2012 # {io2012, html5slides, shower, dzslides, ...}
	highlighter : highlight.js # {highlight.js, prettify, highlight}
	hitheme : tomorrow #
	widgets : [] # {mathjax, quiz, bootstrap}
	mode : selfcontained # {standalone, draft}