Piping with galah_call()

You may have noticed in the above examples that dplyr pipes begin with some data, while galah pipes all begin with galah_call() (be sure to add the parentheses!). This function tells galah that you will be using pipes to construct your query. Follow this with your preferred pipe (|> from base or %>% from magrittr). You can then narrow your query line-by-line using galah_ functions. Finally, end with an atlas_ function to identify what type of data you want from your query.

Here is an example using counts of bandicoot records:

galah_call() |>
  galah_identify("perameles") |>
  galah_filter(year >= 2020) |>
  galah_group_by(species, year) |>
  atlas_counts()

## # A tibble: 11 × 3
##    year  species                count
##    <chr> <chr>                  <int>
##  1 2021  Perameles nasuta        2465
##  2 2021  Perameles bougainville    70
##  3 2021  Perameles gunnii          59
##  4 2021  Perameles pallescens      23
##  5 2020  Perameles nasuta        1386
##  6 2020  Perameles gunnii          39
##  7 2020  Perameles pallescens      11
##  8 2020  Perameles bougainville     1
##  9 2022  Perameles nasuta         292
## 10 2022  Perameles gunnii          53
## 11 2022  Perameles pallescens      26

And a second example, to download occurrence records of bandicoots in 2021, and also to include information on which records had zero coordinates:

galah_call() |>
  galah_identify("perameles") |>
  galah_filter(year == 2021) |>
  galah_select(group = "basic", ZERO_COORDINATE) |>
  atlas_occurrences() |>
  head()

## # A tibble: 6 × 9
##   decimalLatitude decimalLongitude eventDate           scientificName   taxonConceptID              recor…¹ dataR…² occur…³ ZERO_…⁴
##             <dbl>            <dbl> <dttm>              <chr>            <chr>                       <chr>   <chr>   <chr>   <lgl>  
## 1           -43.1             148. 2021-05-09 08:06:02 Perameles gunnii https://biodiversity.org.a… 6f258c… iNatur… PRESENT FALSE  
## 2           -43.0             147. 2021-03-31 21:00:16 Perameles gunnii https://biodiversity.org.a… 40d963… iNatur… PRESENT FALSE  
## 3           -43.0             148. 2021-06-24 12:55:00 Perameles gunnii https://biodiversity.org.a… 62724c… iNatur… PRESENT FALSE  
## 4           -43.0             147. 2021-02-06 14:09:00 Perameles gunnii https://biodiversity.org.a… ef4fe0… iNatur… PRESENT FALSE  
## 5           -43.0             147. 2021-09-14 04:39:45 Perameles gunnii https://biodiversity.org.a… 7900b1… iNatur… PRESENT FALSE  
## 6           -42.9             147. 2021-07-21 19:42:41 Perameles gunnii https://biodiversity.org.a… c3cc63… iNatur… PRESENT FALSE  
## # … with abbreviated variable names ¹​recordID, ²​dataResourceName, ³​occurrenceStatus, ⁴​ZERO_COORDINATE

Note that the order in which galah_ functions are added doesn’t matter, as long as galah_call() goes first, and an atlas_ function comes last.

Using dplyr functions in galah

As of version 1.5.1, it is possible to call dplyr functions natively within galah to amend how queries are processed, i.e.:

# galah syntax
galah_call() |>
  galah_filter(year >= 2020) |>
  galah_group_by(year) |>
  atlas_counts()

## # A tibble: 3 × 2
##   year    count
##   <chr>   <int>
## 1 2021  7127224
## 2 2020  6403158
## 3 2022  1353727

# dplyr syntax
galah_call() |>
  filter(year >= 2020) |>
  group_by(year) |>
  count()

## # A tibble: 3 × 2
##   year    count
##   <chr>   <int>
## 1 2021  7127224
## 2 2020  6403158
## 3 2022  1353727

The full list of masked functions is:

• identify() ({graphics}) as a synonym for galah_identify()
• select() ({dplyr}) as a synonym for galah_select()
• group_by() ({dplyr}) as a synonym for galah_group_by()
• slice_head() ({dplyr}) as a synonym for the limit argument in atlas_counts()
• st_crop() ({sf}) as a synonym for galah_polygon()
• count() ({dplyr}) as a synonym for atlas_counts()