atlas_counts supports server-side grouping of data. Grouping can be
used to return record counts grouped by multiple, valid fields (found by
search_fields. Use galah_group_by when using the
group_by argument of atlas_counts to return record counts summed
by one or more valid fields.
galah_group_by(..., expand = TRUE)zero or more individual column names to include
logical: When passed to group_by argument of
atlas_counts, should factor levels be expanded? Defaults to TRUE.
If any arguments are provided, returns a data.frame with
columns name and type, as per galah_select(); if no arguments
are provided, returns NULL.
Return record counts since 2010 by year
records <- galah_call() |>
galah_filter(year > 2010) |>
galah_group_by(year) |>
atlas_counts()
records #> # A tibble: 12 x 2 #> year count #> <chr> <int> #> 1 2020 5843340 #> 2 2019 5506924 #> 3 2018 5418009 #> 4 2017 4648403 #> 5 2016 3844787 #> 6 2014 3767573 #> 7 2015 3605917 #> 8 2013 3505658 #> 9 2012 2933981 #> 10 2011 2539004 #> 11 2021 1161557 #> 12 2022 41790
Return record counts since 2010 by year and data provider
records <- galah_call() |>
galah_filter(year > 2010) |>
galah_group_by(year, dataResourceName) |>
atlas_counts()
records #> # A tibble: 1,048 x 3 #> year dataResourceName count #> <chr> <chr> <int> #> 1 2020 eBird Australia 4589800 #> 2 2020 iNaturalist Australia 671032 #> 3 2020 NSW BioNet Atlas 372617 #> 4 2020 Earth Guardians Weekly Feed 71783 #> # ... with 1,044 more rows
Return record counts of Litoria species each year since 2015, limiting results to the top 5 each year
records <- galah_call() |>
galah_identify("Litoria") |>
galah_filter(year > 2015) |>
galah_group_by(year, species) |>
atlas_counts(limit = 5)
records #> # A tibble: 35 x 3 #> year species count #> <chr> <chr> <int> #> 1 2018 Litoria peronii 10497 #> 2 2018 Litoria fallax 7013 #> 3 2018 Litoria caerulea 3073 #> 4 2018 Litoria verreauxii 2980 #> # ... with 31 more rows
galah_select(), galah_filter() and
galah_geolocate() for related methods.