andybega

egy.points <-
structure(list(Latitude = c(30.0626, 30.0626, 30.0626, 25, 30.5, 
30.1219, 29.0744, 31.4044, 29.9737, 30.0626, 31.4, 31.2, 29, 
30.6, 28.1, 26.1642, 24.0934, 25.6989, 27, 30.0453, 30.6043, 
30.6803, 30.4658, 31.2565, 30.1219, 27.7667, 31.0364, 30.0273, 
31.4044, 29.7, 27.2, 26.5, 29.5, 26, 28.501, 27.9333, 30.5, 27.2574, 
27, 30.2986, 30.5333, 29.7, 27.2167, 30.7885, 25.0757, 30.9, 
30.7, 30.9, 24.0934, 29.9978, 31.1, 30.15, 22.3457, 25.9141, 
30.6, 31.35, 26.1642, 28.3121, 26.55, 30.9251, 31.0392, 30.5, 
27, 29.3, 26.0495, 31, 26.0549, 26.1247, 30.3, 26.7292, 30.0626, 

andybega

#
#
#     Original code from Mike:
#
#

# mdw attempts at modeling Protests & Demonstrations
# August 13, 2013

library(wicews)

andybega

library(geonames)

# list of city names (in Afghanistan)
cities <- c("Gereshk", "Lashkar Gah", "Marjah", "Nad-e Ali")
                                                                                                                                                                          -5L), class = "data.frame")
# conveninence function to look up and format results
GNsearchAF <- function(x) {
  res <- GNsearch(name=x, country="AF")
  return(res[1, ])
}

andybega

CREATE TABLE afg_greg AS
SELECT * 
  FROM greg 
  WHERE ( ST_contains((SELECT the_geom FROM afg_adm0), geom) OR
          ST_overlaps((SELECT the_geom FROM afg_adm0), geom) );

andybega

plotMissing <- function(data, dim1=NULL, dim2=NULL, na.id=NULL) {
  require(ggplot2)
  require(grid)
  # Function to plot missing values in a data frame, or to plot missing values
  # in a data frame representing panel data (i.e. against 2 dimensions)
  # Leave dim1 and dim2 NULL to plot missing values in data frame.
  if (xor(is.null(dim1), is.null(dim2))) stop("Specify either both or no dims.")
  
  # Set colors for possible data values
  myCol <- c("#DCDCDC", "#32CD32", "#CD4F39")

andybega

library(XML)
library(plyr)

# Get and format html file
duke.html <- readLines("http://www.gradeinflation.com/Duke.html")
duke.doc <- htmlParse(duke.html)

# Get table as data frame
duke <- readHTMLTable(duke.doc, header=F, as.data.frame=F)
duke <- data.frame(duke, stringsAsFactors=F)