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#!/usr/bin/env bash

# With apologies to:
# ~/.osx — https://mths.be/osx

# Ask for the administrator password upfront
sudo -v

# Keep-alive: update existing `sudo` time stamp until `.osx` has finished
while true; do sudo -n true; sleep 60; kill -0 "$$" || exit; done 2>/dev/null &

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#!/usr/bin/env bash

# With apologies to:
# ~/.osx — https://mths.be/osx

# Ask for the administrator password upfront
sudo -v

# Keep-alive: update existing `sudo` time stamp until `.osx` has finished
while true; do sudo -n true; sleep 60; kill -0 "$$" || exit; done 2>/dev/null &

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# You may need to install a couple libraries before loading them:
# install.packages(c("ggmap", "plyr", "rgdal"))
library(ggmap)
library(plyr)
library(rgdal)

# Here we read in a shapefile containing the centroids of our TAZs
zonecentroids <- readOGR(dsn="/path/containing/shapefile/no/final/slash",
                        layer="shapefile-containing-points")

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# install.packages(c("rgdal", "rgeos", "ggmap", "maptools"))
library(rgdal)
library(rgeos)
library(ggmap)
library(maptools)

# Read the shapefile with OGR. Punctuation matters: No trailing slash
# on the dsn, and no .shp on the layer
udist <- readOGR(dsn="/Users/peter/Downloads/clip",
                 layer="unidstuc")

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require 'formula'

# ESRI FileGDB support. This recipe can download the file from ESRI,
# however, you must sign into the ESRI support site and agree to their
# licensing terms from a webbrowser.

class Filegdb < Formula
  homepage 'http://www.esri.com/software/arcgis/geodatabase/interoperability'
  url 'http://downloads2.esri.com/Software/FileGDB_API_1_3-64.zip'
  sha1 '95ba7e3da555508c8be10b8dbb6ad88a71b03f49'

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# Statewide obesity data 
# from http://massey.limfinity.com/data/

library(gdata)
library(ggplot2)

# stringsAsFactors=FALSE is important more often than not.
obesity <- read.xls("http://massey.limfinity.com/data/obesity.xls",
                    sheet=1, stringsAsFactors=FALSE)

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% I use the memoir class for everything. `texdoc memoir` from your command
% prompt (on Mac & Linux anyway) has all the details. It's better.
\documentclass[11pt,letterpaper,article]{memoir} % for a short document
\usepackage{lipsum}
\usepackage{amsmath}
\usepackage{latexsym}
% Useful for Knitr. Otherwise, I use memoir class's 'ctabular' env.
\usepackage{longtable}

\newsubfloat{figure}% Allow subfloats in figure environment

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Publishing a dataset using DSMP API from R

These are some notes I made to reason through / illustrate usage of the new DSMP API. Usage here is presented as a linear set of steps for pedagogical purposes rather than attempting to create a reusable set of functions or a library.

Creating a new R client library based around the DSMP API is a task for the hopefully-not-too-distant future.