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README.Rmd
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README.Rmd
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---
title: ""
output: github_document
---
# {extractOz}: A Unified Approach to Extracting Data About Australian Locations Using GPS Points <img src='man/figures/logo.png' align='right' />
<!-- badges: start -->
[](https://codecov.io/gh/DPIRD-FSI/extractOz)
[](https://www.repostatus.org/#active)
[](https://github.com/DPIRD-FSI/extractOz/actions/workflows/R-CMD-check.yaml)
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Extract the GRDC agroecological zone, major soil order and weather data from your GPS sampling points.
Datasets 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.
You may also use your own geospatial vector format file to extract similar information using the generic function, `extract_area()`.
## Quick Start
You can install {extractOz} like so.
```{r setup, eval=FALSE}
if (!require("remotes")) {
install.packages("remotes")
}
remotes::install_github("DPIRD-FSI/extractOz", build_vignettes = TRUE)
```
Load the packages necessary to execute the examples that follow.
```{r load-libs}
library(extractOz)
library(dplyr)
```
## Create Locations in WA and NSW
```{r create-locs}
locs <- list(
"Merredin" = c(x = 118.28, y = -31.48),
"Corrigin" = c(x = 117.87, y = -32.33),
"Tamworth" = c(x = 150.84, y = -31.07)
)
```
## Extract the GRDC AgroEcological Zones
See `?extract_ae_zone()` for more help on how to use this function.
```{r az-zone}
z <- extract_ae_zone(x = locs)
```
## Extract the Soil Order
See `?extract_soil_order()` for more help on how to use this function.
```{r soil-order}
s <- extract_daas_soil_order(x = locs)
```
## Get Weather Data for These Locations in 2020
Using the previously used list of GPS points, fetch weather data from SILO for 2020.
This is just a non-working example, replace `your_api_key` with your email address below.
See `?extract_patched_point()` for more help on how to use this function.
### A Note on API Keys
The examples in this README assume that you have stored your API key in your .Renviron file.
See [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.
```{r ppd}
three_sites <-
extract_patched_point(
x = locs,
start_date = "20200101",
end_date = "20201231",
api_key = Sys.getenv("SILO_API_KEY")
)
```
## Join the Weather Data with AE Zone, Soil Order and Site Information
Now using `dplyr::left_join()`, create a single `data.frame()` of the location, GPS coordinates, agroecological zone and weather data.
```{r join-all}
left_join(z, three_sites, by = c(
"location" = "location",
"x" = "x",
"y" = "y"
)) %>%
left_join(s)
```
## Code of Conduct
Please note that the {extractOz} project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.