In lhenneman/disperseR: Run HYSPLIT many times in parallel, aggregate to zip code level, plot the results, save the plots.

knitr::opts_chunk$set(echo = TRUE)

library(tidyverse)
library(disperseR)

In this vignette we show you how we prepared the zip code coordinate data that we have attached to the disperseR package.

In case you have not yet created your project folder use the following command.

disperseR::create_dirs()

We first download the data from Open Data Soft

filename <- file.path(main_dir, 'zipcodecoordinate.csv')
url <- 'https://public.opendatasoft.com/explore/dataset/us-zip-code-latitude-and-longitude/download/?format=csv&timezone=Europe/Berlin&use_labels_for_header=true'

if(!file.exists(filename)){
    download.file(url = url, destfile = filename)
}

Read in the file.

zipcodecoordinate <- read.csv(filename, skip = 0, header = T, sep=";")

Select columns and rename them.

zipcodecoordinate <- zipcodecoordinate %>% 
  dplyr::select(Zip, City, Latitude, Longitude) %>% 
  dplyr::rename(ZIP=Zip)

Now the data set is ready to use in your plots! We added it to this package.

lhenneman/disperseR documentation built on Nov. 14, 2021, 6:24 p.m.