| ⌘T | go to file |
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| library("foreign") | |
| library("rgdal") | |
| library("sp") | |
| library("spdep") | |
| library("maptools") | |
| library("SpatialEpi") | |
| library("plyr") | |
| data <- read.dbf("counts.dbf") | |
| shapes <- readShapePoly("counts.shp") |
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| require("lattice") | |
| require("makeR") | |
| #################################################################### | |
| #################################################################### | |
| #################################################################### | |
| #################################################################### | |
| levelplot.forumula <- function (x, data = NULL, allow.multiple = is.null(groups) || | |
| outer, outer = TRUE, aspect = "fill", panel = if (useRaster) lattice.getOption("panel.levelplot.raster") else lattice.getOption("panel.levelplot"), |
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| data$date <- as.POSIXlt(data$unix_time, origin="1970-01-01", tz="America/New_York") | |
| data$date <- as.Date(data$date, format="%Y-%m-%d") |
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| #_______________________________________________________________________________# | |
| #| |# | |
| #| !! keep in mind that each data frame must have only one common field name!! |# | |
| #|_____________________________________________________________________________|# | |
| #create the function for csvs | |
| merge.csv = function(mypath){ | |
| filenames=list.files(path=mypath, full.names=TRUE) | |
| datalist = lapply(filenames, function(x){read.csv(file=x,header=T, stringsAsFactors=F)}) |
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| #// Say you were building a dataset and wanted to automatically | |
| #// generate variable names by some pattern. | |
| #// For instance, you might want to do this with population counts | |
| #// within 100 census tracts by race | |
| #// IE: | |
| # | |
| # tracts <- paste("c", rep(1:100), sep="") | |
| # race - c("black", "white", "hispanic") | |
| # | |
| #// In this case you would want to generate 300 unique variable names |
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| #see below for query specifications | |
| getInsights <- function( | |
| username = "[email protected]", | |
| password = "googleinsights4r", | |
| text_query = "'hello world'", | |
| date_query = "1/2004 108m", | |
| geo_query = "US", | |
| search_type= "all", | |
| filter_category="none"){ |
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| path_to_file = "~/Desktop/Vizzuality-cartodb-r-05eb537/CartoDB_1.4.tar.gz" | |
| install.packages(path_to_file, repos=NULL, type="source") | |
| require("CartoDB") | |
| account_name = "parks-datadive" | |
| api_key = "[ON THE BOARD IN 517-F]" | |
| cartodb(account_name, api_key) | |
| cartodb.test() |
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| # Get a lat/lon value for each address | |
| geocode.addr <- function(city, country) { | |
| geo.url <- "http://maps.googleapis.com/maps/api/geocode/json?address=" | |
| geo.text <- getURL(paste(geo.url, URLencode(paste(city, country, collapse="+")), "&sensor=false", sep="")) | |
| geo.json <- fromJSON(geo.text) | |
| if(geo.json$status == "OK"){ | |
| return(geo.json$results[[1]]$geometry$location) | |
| } | |
| else{ |
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