andybega

# Log in to event database first, e.g. 
# mysql -u xxx -p -h IPaddress -D event_data

SET @countryid = (SELECT id FROM countries WHERE countryname='CYPRUS');

# Pull events and related information, takes 1.5m for Cyprus, and save 
# to a csv file
CREATE TABLE temp_results AS
SELECT e.event_ID,
       e.event_date,

andybega

worldMap <- function(x, id, data, date='2008-01-01', legend.title=NULL,
                     maxy=1) {
  # Input 2-column matrix with unique identifier and data to be mapped for 
  # state slice in "date", output thematic map.
  
  require(cshapes)
  require(maptools)
  require(RColorBrewer) # for color palettes
  require(plyr)
  

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# Change to your data
data <- data.frame(resp=1:5,
                   w11=sample(1:5, 5, replace=TRUE), 
                   w12=sample(1:5, 5, replace=TRUE), 
                   w13=sample(1:5, 5, replace=TRUE))
data$LoySum <- apply(data[, c("w11", "w12", "w13")], 1, mean)                   
                   

# Names of the variables we want to look at
q.names <- c("w11", "w12", "w13")

andybega

setwd("/Volumes/political-science/shared/ICEWS Project/C-IED/Data/Global_WITS")

# Read as txt chunk
# The first 16 lines are meta data
wits.text <- readLines("WITS.csv")
head(wits.text, n=16)

# Get actual data
wits <- read.csv(text=wits.text, header=TRUE, skip=16)

andybega

## Correlations for blog post

library(plyr)

# from GT
# source directories and first few lines of pull-data.R

sql <- 
  "SELECT dateoccured AS date, count(*) AS sigacts
FROM sigacts

andybega

# Libraries
library(RMySQL)

# Connect to server
conn <- dbConnect(MySQL(), user="ab428", password="", 
                  dbname="event_data", host="")

country <- "Turkey"
start.date <- "2013-05-15"
end.date <- "2013-06-15"

andybega

# Dot density map
# Eventually should be like http://www.radicalcartography.net/index.html?frenchkisses

library(maptools)

nc_SP <- readShapePoly(system.file("shapes/sids.shp", package="maptools")[1],
 proj4string=CRS("+proj=longlat  +ellps=clrk66"))
 
## Not run:
pls <- slot(nc_SP, "polygons")

andybega

# from here http://blog.55minutes.com/2013/09/postgresql-93-brew-upgrade/

# Create backup of database
/usr/local/cellar/postgresql/9.2.4/bin/pg_dump -h localhost -p 5432 -U ab428 -Fc -b -v -f "/usr/local/var/pg_backup/afghanistan.backup" afghanistan

# Upgrade PostGIS
brew doctor  # fix errors
brew update
brew upgrade postgres
brew upgrade gdal --with-postgres

andybega

library("ggplot2")

df <- structure(list(date = structure(c(17532, 17897, 18262, 18993, 
19358, 19723, 20089), class = "Date"), id = c("9991", "9991", 
"9991", "9992", "9992", "9992", "9992"), cowcode = c(999, 999, 
999, 999, 999, 999, 999), y = c(1, 1, 1, 2, 2, 2, 2)), row.names = c(NA, 
-7L), class = "data.frame")

ggplot(df, aes(x = date, y = y, group = cowcode)) + geom_line()

andybega

library("tidyverse")

arima_qs <- readr::read_csv("/path/to/forecast_rct_a_subset.csv", 
  col_types = cols(user_id = col_integer())) %>%
  mutate(Forecaster = factor(Forecaster))

# Add # of questions to each Data source label
arima_qs <- arima_qs %>%
  group_by(Data_source) %>%
  mutate(by_Data_source_n_ifps = length(unique(ifp_id))) %>%