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and Nutrition"],"readme":"---\ntitle: \"\"\noutput: github_document\n---\n\n# {extractOz}: A Unified Approach to Extracting Data About Australian Locations Using GPS Points \u003cimg src='man/figures/logo.png' align='right' /\u003e\n\n\u003c!-- badges: start --\u003e\n[![codecov](https://codecov.io/gh/DPIRD-FSI/extractOz/branch/main/graph/badge.svg?token=PBtL3rNIYb)](https://codecov.io/gh/DPIRD-FSI/extractOz)\n[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![R-CMD-check](https://github.com/DPIRD-FSI/extractOz/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/DPIRD-FSI/extractOz/actions/workflows/R-CMD-check.yaml)\n\u003c!-- badges: end --\u003e\n\nExtract the GRDC agroecological zone, major soil order and weather data from your GPS sampling points.\nDatasets for the GRDC agroecological zones and functions that automatically download modified data from the Digital Atlas of Australian Soils are included in this package for ease of use.\nYou may also use your own geospatial vector format file to extract similar information using the generic function, `extract_area()`.\n\n## Quick Start\n\nYou can install {extractOz} like so.\n\n```{r setup, eval=FALSE}\nif (!require(\"remotes\")) {\n  install.packages(\"remotes\")\n}\n\nremotes::install_github(\"DPIRD-FSI/extractOz\", build_vignettes = TRUE)\n```\n\nLoad the packages necessary to execute the examples that follow.\n\n```{r load-libs}\nlibrary(extractOz)\nlibrary(dplyr)\n```\n\n## Create Locations in WA and NSW\n\n```{r create-locs}\nlocs \u003c- list(\n  \"Merredin\" = c(x = 118.28, y = -31.48),\n  \"Corrigin\" = c(x = 117.87, y = -32.33),\n  \"Tamworth\" = c(x = 150.84, y = -31.07)\n)\n```\n\n## Extract the GRDC AgroEcological Zones\n\nSee `?extract_ae_zone()` for more help on how to use this function.\n\n```{r az-zone}\nz \u003c- extract_ae_zone(x = locs)\n```\n\n## Extract the Soil Order\n\nSee `?extract_soil_order()` for more help on how to use this function.\n\n```{r soil-order}\ns \u003c- extract_daas_soil_order(x = locs)\n```\n\n## Get Weather Data for These Locations in 2020\n\nUsing the previously used list of GPS points, fetch weather data from SILO for 2020.\nThis is just a non-working example, replace `your_api_key` with your email address below.\nSee `?extract_patched_point()` for more help on how to use this function.\n\n### A Note on API Keys\n\nThe examples in this README assume that you have stored your API key in your .Renviron file.\nSee [Chapter 8](https://rstats.wtf/r-startup.html#renviron) in \"What They Forgot to Teach You About R\" by Bryan _et al._ for more on storing details in your .Renviron if you are unfamiliar.\n\n```{r ppd}\nthree_sites \u003c-\n  extract_patched_point(\n    x = locs,\n    start_date = \"20200101\",\n    end_date = \"20201231\",\n    api_key = Sys.getenv(\"SILO_API_KEY\")\n  )\n```\n\n## Join the Weather Data with AE Zone, Soil Order and Site Information\n\nNow using `dplyr::left_join()`, create a single `data.frame()` of the location, GPS coordinates, agroecological zone and weather data.\n\n```{r join-all}\nleft_join(z, three_sites, by = c(\n  \"location\" = \"location\",\n  \"x\" = \"x\",\n  \"y\" = \"y\"\n)) %\u003e%\n  left_join(s)\n```\n\n## Code of Conduct\n\nPlease note that the {extractOz} project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).\nBy contributing to this project, you agree to abide by its terms.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDPIRD-FSI%2FextractOz","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FDPIRD-FSI%2FextractOz","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDPIRD-FSI%2FextractOz/lists"}