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An interface to USDA Quick Stats data with mapping capabilities.
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README.md

tidyUSDA

Travis build statusCRAN statusmetacran downloadsminimal R version Codecov test coverage

tidyUSDA, an interface to USDA Quick Stats data with mapping capabilities.

Overview

tidyUSDA provides the R user with a consistent API to pull USDA census and survey data from QuickStats. You can:

  • getQuickstat() lets you pass values to the fields you see on the QuickStats website, as well as include a simple features (SF) geometry field for the county or state level.
  • View({parameter name}) lets you view QuickStats all available values for a given field (which you would input into getQuickstats(), preferably with copy paste)
  • plotUSDA() provides a quick way to plot your data if you set geometry = TRUE

Installation

# Install directly from CRAN:
install.packages("tidyUSDA")

Windows

Depending on which version of R you have installed, you may need to install Rtools.

Mac

You may need to install gdal before install.packages("tidyUSDA"). Use these commands:

brew install pkg-config     
brew install gdal

Linux

You will need to install GDAL (>= 2.0.1), GEOS (>= 3.4.0) and Proj.4 (>= 4.8.0) for most Unix-based systems.

Ubuntu

To install the dependencies on Ubuntu, either add ubuntugis-unstable to the package repositories:

sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable
sudo apt-get update
sudo apt-get install libudunits2-dev libgdal-dev libgeos-dev libproj-dev 

or install dependencies from source; see e.g. an older travis config file for hints.

Fedora

The following command installs all required dependencies:

sudo dnf install gdal-devel proj-devel proj-epsg proj-nad geos-devel udunits2-devel

Arch

Get gdal, proj and geos from the main repos and udunits from the AUR:

pacman -S gdal proj geos
pacaur/yaourt/whatever -S udunits

Thanks to the SF package README for these OS helpers.

Usage

Check out the vignette with:

vignette("using_tidyusda")

You first need to grab a free API token from the USDA at their website.

library(tidyUSDA)

# Save your API token to a variable, or better yet, use the keyring package to store it securely
key <- '1234-abcd'



# View all parameter names for the 'program' field
View(tidyUSDA::allProgram)



# Get count of operations with sales in 2017
ops.with.sales <- tidyUSDA::getQuickstat(
  sector=NULL,
  group=NULL,
  commodity=NULL,
  category=NULL,
  domain=NULL,
  county=NULL,
  key = key,
  program = 'CENSUS',
  data_item = 'CROP TOTALS - OPERATIONS WITH SALES',
  geographic_level = 'COUNTY',
  year = '2017',
  state = NULL,
  geometry = T,
  lower48 = T)



# Plot this data for each state
tidyUSDA::plotUSDA(df = ops.with.sales)

The last function returns this ggplot choropleth:

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