API Docs#
- galah.atlas_counts(taxa=None, scientific_name=None, identifiers=None, specific_epithet=None, filters=None, group_by=None, total_group_by=False, use_data_profile=False, polygon=None, bbox=None, config_file=None, crs=None)#
Prior to downloading data, it is often valuable to have some estimate of how many records are available, both for deciding if the query is feasible, and for estimating how long it will take to download. Alternatively, for some kinds of reporting, the count of observations may be all that is required, for example for understanding how observations are growing or shrinking in particular locations, or for particular taxa.
To this end,
galah.atlas_counts()takes arguments in the same format asgalah.atlas_occurrences(), and provides either a total count of records matching the criteria, or a pandas dataframe of counts matching the criteria supplied to the group_by argument. It can also return the total number of groups by using the total_group_by argument.- Parameters:
taxa (string) – one or more scientific names. Use
galah.search_taxa()to search for valid scientific names.identifiers (string / list) – one or more taxonomic identifiers (such as guid or taxonConceptID) to search.
specific_epithet (list) – search taxonomic levels by using the argument “specificEpithet”.
scientific_name (dictionary) – search taxonomic levels by using the argument “scientificName”.
filters (pandas.DataFrame) – filters, in the form
fieldlogicalvalue(e.g."year=2021")group_by (string) – zero or more individual column names (i.e. fields) to include. See
galah.show_all()andgalah.search_all()to see valid fields.total_group_by (logical) – If
True, galah gives total number of groups in data. Defaults toFalse.use_data_profile (string) – A profile name. Should be a string - the name or abbreviation of a data quality profile to apply to the query. Valid values can be seen using
galah.show_all(profiles=True)polygon (shapely Polygon) – A polygon object denoting a geographical region. Defaults to
None.bbox (dict or shapely Polygon) – A polygon or dictionary object denoting four points, which are the corners of a geographical region. Defaults to
None.crs (str) – The Coordinate Reference System of your shape. All atlases are EPSG: 4326 though default value here is None
config_file (string) – If you want to specify your own config file, put the path and name of the file here. This is applicable when you are running on a server and each user has different configurations. Defaults to
None.
- Return type:
An object of class
pandas.DataFrame.
Examples
Return total records in your chosen atlas
galah.atlas_counts()[19] totalRecords 0 185090015
Return records from 2020 onwards, grouped by year
galah.atlas_counts(filters="year>2019",group_by="year")[19] year count 0 2020 8188386 1 2021 9717209 2 2022 10636634 3 2023 12542573 4 2024 13633019 5 2025 10815812 6 2026 3052695
- galah.atlas_media(taxa=None, scientific_name=None, identifiers=None, specific_epithet=None, filters=None, fields=None, multimedia=None, use_data_profile=False, polygon=None, bbox=None, collect=False, path=None, thumbnail=False, progress_bar=True, config_file=None, mint_doi=False, doi=None, crs=None)#
In addition to text data describing individual occurrences and their attributes, ALA stores images, sounds and videos associated with a given record.
galah.atlas_media()displays metadata for any and all of the media types.- Parameters:
taxa (string / list) – one or more scientific names. Use
galah.search_taxa()to search for valid scientific names.identifiers (string / list) – one or more taxonomic identifiers (such as guid or taxonConceptID) to search.
specific_epithet (list) – search taxonomic levels by using the argument “specificEpithet”.
scientific_name (dictionary) – search taxonomic levels by using the argument “scientificName”.
filters (string / list) – filters, in the form
fieldlogicalvalue(e.g."year=2021")fields (string / list) –
Name of one or more column groups to include. Valid options are “basic”, “event” and “assertions” Default is set to
"fields=basic", which returns:decimalLatitude, decimalLongitude, eventDate, scientificName, taxonConceptID, recordID, dataResourceName, occurrenceStatus
Using
"fields="event"returns:eventRemarks, eventTime, eventID, eventDate, samplingEffort, samplingProtocol
Using
fields="media"returns:multimedia, multimediaLicence, images, videos, sounds
See
galah.show_all()andgalah.search_all()to see all valid fields.multimedia (string / list) – This is for specifying what types of multimedia you would like, i.e “images”. Defaults to [‘images’,’videos’,’sounds’]
assertions (string) – Using “assertions” returns all quality assertion-related columns. These columns are data quality checks run by each living atlas. The list of assertions is shown by
galah.show_all(assertions=True).use_data_profile (logical) – if
True, uses data profile set ingalah_config(). Valid values can be seen usinggalah.show_all(profiles=True). Default isFalsepolygon (shapely Polygon) – A polygon shape denoting a geographical region. Defaults to
None.bbox (dict or shapely Polygon) – A polygon or dictionary type denoting four points, which are the corners of a geographical region. Defaults to
None.crs (str) – The Coordinate Reference System of your shape. All atlases are EPSG: 4326 though default value here is None
collect (logical) – if
True, downloads full-sized images and media files returned to a local directory.path (string) – path to directory where downloaded media will be stored. Defaults to current directory.
thumbnail (logical) – if
True, downloads thumbnail images rather than the full image. Defaults toFalse.progress_bar (logical) – if
True, shows a progress bar while images are downloading. Defaults toTrue.config_file (string) – If you want to specify your own config file, put the path and name of the file here. This is applicable when you are running on a server and each user has different configurations. Defaults to
None.
- Return type:
An object of class
pandas.DataFrame. Ifcollect=True, available image & media files are downloaded to a user local directory.
Examples
galah.galah_config(atlas="Australia",email="youremail@example.com") galah.atlas_media(taxa="Ornithorhynchus anatinus",filters=["year=2020","decimalLongitude>153.0")
atlas in galah_config: Australia atlas in galah_config again: Australia [23] [17] decimalLongitude scientificName decimalLatitude \ 0 153.005873 Ornithorhynchus anatinus -30.297841 1 153.005912 Ornithorhynchus anatinus -30.298183 2 153.006628 Ornithorhynchus anatinus -30.300649 3 153.007479 Ornithorhynchus anatinus -30.298361 4 153.015910 Ornithorhynchus anatinus -30.311448 5 153.297699 Ornithorhynchus anatinus -28.678673 6 153.300439 Ornithorhynchus anatinus -28.661653 7 153.300439 Ornithorhynchus anatinus -28.661653 8 153.386929 Ornithorhynchus anatinus -28.213785 9 153.386929 Ornithorhynchus anatinus -28.213785 eventDate occurrenceStatus multimedia \ 0 2020-09-26T17:39:00Z PRESENT Image 1 2020-09-04T18:28:00Z PRESENT Image 2 2020-08-30T18:37:43Z PRESENT Image 3 2020-08-30T18:35:00Z PRESENT Image 4 2020-09-08T17:26:47Z PRESENT Image 5 2020-08-13T00:00:00Z PRESENT Image 6 2020-10-12T17:20:00Z PRESENT Image 7 2020-10-12T17:20:00Z PRESENT Image 8 2020-01-17T07:09:00Z PRESENT Image 9 2020-01-17T07:09:00Z PRESENT Image images sounds \ 0 14374712-1c37-4e2d-af28-4572f64e7d3a NaN 1 40aadbde-3918-4bba-9dc9-13fa1da3809b NaN 2 1aad7125-c6c0-4557-b9a2-112c03ac6709 NaN 3 09efd0a0-aa51-4d00-80f9-4e78e19aa89e NaN 4 792a93d4-6436-4222-9a00-00cda0ec1f14 NaN 5 393df479-5fbb-464e-82ed-4d6fd19dd863 NaN 6 7424399a-f327-4ea1-9ffa-aa7a2b69f82b NaN 7 cee7bb9f-6b2e-4c47-8ba8-c9a3bdf92fa0 NaN 8 66904cee-f8ca-4e3a-b7d5-d738f4bd0978 NaN 9 dfdbd258-d90a-484b-af19-2070705f166c NaN taxonConceptID \ 0 https://biodiversity.org.au/afd/taxa/ac61fd14-... 1 https://biodiversity.org.au/afd/taxa/ac61fd14-... 2 https://biodiversity.org.au/afd/taxa/ac61fd14-... 3 https://biodiversity.org.au/afd/taxa/ac61fd14-... 4 https://biodiversity.org.au/afd/taxa/ac61fd14-... 5 https://biodiversity.org.au/afd/taxa/ac61fd14-... 6 https://biodiversity.org.au/afd/taxa/ac61fd14-... 7 https://biodiversity.org.au/afd/taxa/ac61fd14-... 8 https://biodiversity.org.au/afd/taxa/ac61fd14-... 9 https://biodiversity.org.au/afd/taxa/ac61fd14-... recordID dataResourceName videos \ 0 072bc4f0-7581-44c6-b0ec-e3fe58d251fc iNaturalist Australia NaN 1 dd885218-bdb9-404a-8441-e5cd329f6605 iNaturalist Australia NaN 2 72ad295f-112d-442f-83e1-fd385ef9163a iNaturalist Australia NaN 3 42912016-2409-4125-a61f-13ffd4c32fcb iNaturalist Australia NaN 4 6882dfe3-5295-493d-a005-66f8392e9d5b iNaturalist Australia NaN 5 12d8c7f9-9d66-4312-9245-87a0a1021557 iNaturalist Australia NaN 6 2a701513-b21d-4baa-bac4-5e6a3a65252b iNaturalist Australia NaN 7 2a701513-b21d-4baa-bac4-5e6a3a65252b iNaturalist Australia NaN 8 808b0c19-9616-45f1-994e-e3b33fc32836 Earth Guardians Weekly Feed NaN 9 808b0c19-9616-45f1-994e-e3b33fc32836 Earth Guardians Weekly Feed NaN creator license mimeType \ 0 Brett Vercoe http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 1 Brett Vercoe http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 2 Brett Vercoe http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 3 Brett Vercoe http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 4 kerrycameron http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 5 julespetroff http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 6 julespetroff http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 7 julespetroff http://creativecommons.org/licenses/by-nc/4.0/ image/jpeg 8 image/jpeg 9 image/jpeg width height imageUrl 0 2048 1365 https://images.ala.org.au/store/a/3/d/7/143747... 1 2048 1365 https://images.ala.org.au/store/b/9/0/8/40aadb... 2 1365 2048 https://images.ala.org.au/store/9/0/7/6/1aad71... 3 2048 1238 https://images.ala.org.au/store/e/9/8/a/09efd0... 4 927 701 https://images.ala.org.au/store/4/1/f/1/792a93... 5 638 426 https://images.ala.org.au/store/3/6/8/d/393df4... 6 713 401 https://images.ala.org.au/store/b/2/8/f/742439... 7 661 500 https://images.ala.org.au/store/0/a/f/2/cee7bb... 8 2988 5312 https://images.ala.org.au/store/8/7/9/0/66904c... 9 2988 5312 https://images.ala.org.au/store/c/6/6/1/dfdbd2...
- galah.atlas_occurrences(taxa=None, scientific_name=None, specific_epithet=None, identifiers=None, filters=None, fields=None, use_data_profile=False, species_list=False, status_accepted=True, polygon=None, bbox=None, crs=None, mint_doi=False, doi=None, print_doi=True, config_file=None)#
The most common form of data stored by living atlases are observations of individual life forms, known as ‘occurrences’. This function allows the user to search for occurrence records that match their specific criteria, and return them as a
pandas.DataFramefor analysis. Optionally, the user can also request a DOI for a given download to facilitate citation and reuse of specific data resources.- Parameters:
taxa (string) – one or more scientific names. Use
galah.search_taxa()to search for valid scientific names.identifiers (string / list) – one or more taxonomic identifiers (such as guid or taxonConceptID) to search.
specific_epithet (list) – search taxonomic levels by using the argument “specificEpithet”.
scientific_name (dictionary) – search taxonomic levels by using the argument “scientificName”.
filters (string / list) – filters, in the form
fieldlogicalvalue(e.g."year=2021")test (logical) – Test if the API is up and running correctly. Prints status of Atlas and returns.
fields (string / list) –
Name of one or more column groups to include. Valid options are “basic”, “event” and “assertions” Default is set to
"fields=basic", which returns:decimalLatitude, decimalLongitude, eventDate, scientificName, taxonConceptID, recordID, dataResourceName, occurrenceStatus
Using
"fields="event"returns:eventRemarks, eventTime, eventID, eventDate, samplingEffort, samplingProtocol
Using
fields="media"returns:multimedia, multimediaLicence, images, videos, sounds
Using
fields="assertionsreturns:all available assertions from the ALA
See
galah.show_all()andgalah.search_all()to see all valid fields.assertions (string / list) – Using “assertions” returns all quality assertion-related columns. These columns are data quality checks run by each living atlas. The list of assertions is shown by
galah.show_all(assertions=True).use_data_profile (string) – A profile name. Should be a string - the name or abbreviation of a data quality profile to apply to the query. Valid values can be seen using
galah.show_all(profiles=True)species_list (logical) – Denotes whether or not you want a species list for GBIF. Default to
False. For species lists, refer toatlas_speciesstatus_accepted (logical) – Denotes whether or not you want only accepted taxonomic ranks for GBIF. Default to
True. For species lists, refer toatlas_speciespolygon (shapely Polygon) – A polygon shape denoting a geographical region. Defaults to
None.bbox (dict or shapely Polygon) – A polygon or dictionary type denoting four points, which are the corners of a geographical region. Defaults to
None.crs (str) – The Coordinate Reference System of your shape. All atlases are EPSG: 4326 though default value here is None
config_file (string) – If you want to specify your own config file, put the path and name of the file here. This is applicable when you are running on a server and each user has different configurations. Defaults to
None.
- Return type:
An object of class
pandas.DataFrame.
Examples
Download records of Vulpes vulpes in 2023
import galah galah.galah_config(atlas="Australia",email="your-email@example.com") galah.atlas_occurrences(taxa="Vulpes vulpes",filters="year=2023")
atlas in galah_config: Australia atlas in galah_config again: Australia [23] [17] recordID scientificName \ 0 0000b436-0613-4991-839a-14b57e573bc9 Vulpes vulpes 1 00010f5d-f8fd-4546-be65-3a1c954e85aa Vulpes vulpes 2 000a75de-419e-4ad4-bda5-85ba4b552837 Vulpes vulpes 3 001355be-9407-4911-950c-625b7ae3d340 Vulpes vulpes 4 0018cc1a-7104-4044-b87d-717e27cba27e Vulpes vulpes ... ... ... 10530 ffe44ebf-dc5b-4509-98ee-3ae22057a81a Vulpes vulpes 10531 ffe5d7b2-5061-450d-af02-0012b0fc4d32 Vulpes vulpes 10532 ffebb23c-58c3-4bf8-8f5c-b49f890154c9 Vulpes vulpes 10533 fff5636e-01b7-4b62-a21b-24af14390e77 Vulpes vulpes 10534 fff87988-89de-4533-837c-61f6cf8a82e6 Vulpes vulpes taxonConceptID decimalLatitude \ 0 https://biodiversity.org.au/afd/taxa/2869ce8a-... -34.892754 1 https://biodiversity.org.au/afd/taxa/2869ce8a-... -34.194160 2 https://biodiversity.org.au/afd/taxa/2869ce8a-... -34.531578 3 https://biodiversity.org.au/afd/taxa/2869ce8a-... -33.367572 4 https://biodiversity.org.au/afd/taxa/2869ce8a-... -35.599890 ... ... ... 10530 https://biodiversity.org.au/afd/taxa/2869ce8a-... -37.753096 10531 https://biodiversity.org.au/afd/taxa/2869ce8a-... -38.846330 10532 https://biodiversity.org.au/afd/taxa/2869ce8a-... -33.834716 10533 https://biodiversity.org.au/afd/taxa/2869ce8a-... -33.803655 10534 https://biodiversity.org.au/afd/taxa/2869ce8a-... -37.388981 decimalLongitude eventDate dataResourceName \ 0 138.557344 2023-12-07T00:00:00Z FeralScan 1 139.634240 2023-03-26T00:00:00Z SA Fauna 2 150.638468 2023-02-22T00:00:00Z NSW BioNet Atlas 3 151.382845 2023-08-29T00:00:00Z FeralScan 4 138.332510 2023-08-07T00:00:00Z SA Fauna ... ... ... ... 10530 144.935377 2023-11-22T00:00:00Z FeralScan 10531 146.187360 2023-03-21T00:00:00Z Victorian Biodiversity Atlas 10532 151.141071 2023-02-20T00:00:00Z FeralScan 10533 151.153854 2023-11-09T00:00:00Z FeralScan 10534 144.266958 2023-01-05T15:16:00Z iNaturalist Australia occurrenceStatus 0 PRESENT 1 PRESENT 2 PRESENT 3 PRESENT 4 PRESENT ... ... 10530 PRESENT 10531 PRESENT 10532 PRESENT 10533 PRESENT 10534 PRESENT [10535 rows x 8 columns]Download records of Vulpes vulpes in 2023, returning only
eventDatefieldimport galah galah.galah_config(atlas="Australia",email="your-email@example.com") galah.atlas_occurrences(taxa="Vulpes vulpes",filters="year=2023",fields="eventDate")
atlas in galah_config: Australia atlas in galah_config again: Australia [23] [17] eventDate 0 NaN 1 NaN 2 NaN 3 NaN 4 NaN ... ... 10530 2023-12-31T00:00:00Z 10531 2023-12-31T00:00:00Z 10532 2023-12-31T00:00:00Z 10533 2023-12-31T14:01:00Z 10534 2023-12-31T16:56:00Z [10535 rows x 1 columns]
- galah.atlas_species(taxa=None, scientific_name=None, identifiers=None, specific_epithet=None, rank='species', group_by=None, filters=None, status_accepted=True, use_data_profile=False, counts=False, polygon=None, bbox=None, crs=None, config_file=None)#
While there are reasons why users may need to check every record meeting their search criteria (i.e. using
galah.atlas_occurrences()), a common use case is to simply identify which species occur in a specified region, time period, or taxonomic group. This function returns apandas.DataFramewith one row per species, and columns giving associated taxonomic information.- Parameters:
taxa (string / list) – one or more scientific names. Use
galah.search_taxa()to search for valid scientific names.identifiers (string / list) – one or more taxonomic identifiers (such as guid or taxonConceptID) to search.
specific_epithet (list) – search taxonomic levels by using the argument “specificEpithet”.
scientific_name (dictionary) – search taxonomic levels by using the argument “scientificName”.
rank (string) – the rank you ultimately want to get names for, i.e. “genus” or “species”. Default is
species.filters (string) – filters, in the form
fieldlogicalvalue(e.g."year=2021")status_accepted (logical) – If
True, galah gives you only the accepted taxonomic ranks. Default isFalse. **FOR GBIF ONLYpolygon (shapely Polygon) – A polygon shape denoting a geographical region. Defaults to
None.bbox (dict or shapely Polygon) – A polygon or dictionary type denoting four points, which are the corners of a geographical region. Defaults to
None.crs (str) – The Coordinate Reference System of your shape. All atlases are EPSG: 4326 though default value here is None
config_file (string) – If you want to specify your own config file, put the path and name of the file here. This is applicable when you are running on a server and each user has different configurations. Defaults to
None.
- Return type:
An object of class
pandas.DataFrame.
Examples
galah.atlas_species(taxa="Heleioporus")[17] Species \ 0 https://biodiversity.org.au/afd/taxa/4437371b-... 1 https://biodiversity.org.au/afd/taxa/d497c571-... 2 https://biodiversity.org.au/afd/taxa/f0d1bb06-... 3 https://biodiversity.org.au/afd/taxa/55de9548-... 4 https://biodiversity.org.au/afd/taxa/4f42e8dd-... 5 https://biodiversity.org.au/afd/taxa/40389159-... Species Name Scientific Name Authorship Taxon Rank Kingdom \ 0 Heleioporus eyrei (Gray, 1845) species Animalia 1 Heleioporus australiacus (Shaw & Nodder, 1795) species Animalia 2 Heleioporus albopunctatus Gray, 1841 species Animalia 3 Heleioporus psammophilus (Lee & Main, 1954) species Animalia 4 Heleioporus barycragus Lee, 1967 species Animalia 5 Heleioporus inornatus (Lee & Main, 1954) species Animalia Phylum Class Order Family Genus \ 0 Chordata Amphibia Anura Limnodynastidae Heleioporus 1 Chordata Amphibia Anura Limnodynastidae Heleioporus 2 Chordata Amphibia Anura Limnodynastidae Heleioporus 3 Chordata Amphibia Anura Limnodynastidae Heleioporus 4 Chordata Amphibia Anura Limnodynastidae Heleioporus 5 Chordata Amphibia Anura Limnodynastidae Heleioporus Vernacular Name 0 Moaning Frog 1 Giant Burrowing Frog 2 Western Spotted Frog 3 Sand Frog 4 Western Marsh Frog 5 Plains Frog
- galah.galah_config(email=None, email_notify=None, atlas=None, data_profile=None, ranks=None, reason=None, verbose=None, timeout=600, usernameGBIF=None, passwordGBIF=None, config_file=None, authenticate=None, auth_filename=None, auth_clear=None, qgis=None)#
The galah package supports large data downloads, and also interfaces with the ALA which requires that users of some services provide a registered email address and reason for downloading data. The
galah_config()function provides a way to manage these issues as simply as possible.- Parameters:
email (string) – An email address that has been registered with the chosen atlas. For the ALA, you can register here.
email_notify (string) – Used to receive an email for each query to
galah.atlas_occurrences(). Defaults toNone, but can be useful in some instances, for example for tracking DOIs assigned to specific downloads for later citation.atlas (string) – Living Atlas to point to,
Australiaby default. Can be an organisation name, acronym, or region (seeshow_all(atlases=True)for admissible values)data_profile (string) – A profile name. Should be a string - the name or abbreviation of a data quality profile to apply to the query. Valid values can be seen using
galah.show_all(profiles=True)ranks (string) – A string letting galah know what taxonomic ranks to show. Use ‘all’ to see all 69 possible ranks, and ‘gbif’ to see the 9 most common ranks.
reason (integer) – A number (integer) providing the reason you are downloading data. Default is set to 4 (scientific research). For a list of all possible reasons run
galah.show_all_reasons()verbose (logical) – If
True, galah gives you the URLs used to query all the data. Default toFalse.usernameGBIF (string) – Your username for GBIF atlas. Default is ‘’.
passwordGBIF (string) – Your password for GBIF atlas. Default is ‘’.
authenticate (logical) – An argument to
- Returns:
- No arguments (A
pandas.DataFrameof all current configuration options.)- >=1 arguments (None)
Examples
import galah galah.galah_config(email='yourname@example.com')
- galah.search_all(assertions=None, atlases=None, apis=None, collection=None, datasets=None, fields=None, licences=None, lists=None, profiles=None, providers=None, ranks=None, reasons=None, column_name=None, verbose=False, config_file=None)#
The living atlases store a huge amount of information, above and beyond the occurrence records that are their main output. In galah, one way that users can investigate this information is by searching for a specific option or category for the type of information they are interested in.
search_all()is a helper function that can do searches within multiple types of information.- Parameters:
assertions (string) – Search for results of data quality checks run by each atlas
atlases (string) – Search for what atlases are available
apis (string) – Search for what APIs & functions are available for each atlas
collection (string) – Search for the specific collections within those institutions
datasets (string) – Search for the data groupings within those collections
fields (string) – Search for fields that are stored in an atlas
licences (string) – Search for copyright licences applied to media
lists (string) – Search for what species lists are available
profiles (string) – Search for what data profiles are available
providers (string) – Search for which institutions have provided data
ranks (string) – Search for valid taxonomic ranks (e.g. Kingdom, Class, Order, etc.)
reasons (string) – Search for what values are acceptable as ‘download reasons’ for a specified atlas
column_name (string) – Determines what column in the table this function will search for the string specified as the argument
- Return type:
An object of class
pandas.DataFramecontaining all data of interest.
Examples
import galah galah.search_all(apis='Australia')
atlas system api_name \ 0 Australia collections collections_collections 1 Australia species species_lookup 2 Australia species species_children 3 Australia spatial spatial_layers 4 Australia records records_species 5 Australia records records_occurrences 6 Australia records records_fields 7 Australia records records_facets 8 Australia records records_facets 9 Australia records records_counts 10 Australia records records_assertions 11 Australia name-matching names_search_single 12 Australia name-matching names_search_epithet 13 Australia name-matching names_search_multiple 14 Australia species names_search_bulk_species 15 Australia name-matching names_lookup 16 Australia logger logger_reasons 17 Australia lists lists_lookup 18 Australia lists lists_all 19 Australia images image_download 20 Australia images image_bulk_metadata 21 Australia images image_metadata 22 Australia images image_licences 23 Australia doi doi_download 24 Australia data-quality profiles_lookup 25 Australia data-quality profiles_all 26 Australia collections collections_providers 27 Australia collections collections_datasets 28 Australia occurrences occurrences_qid 29 Australia authentication authentication api_url \ 0 https://api.ala.org.au/metadata/ws/collection 1 https://api.ala.org.au/species/childConcepts/{id} 2 https://api.ala.org.au/species/childConcepts/{... 3 https://api.ala.org.au/spatial-service/fields 4 https://api.ala.org.au/occurrences/occurrences... 5 https://api.ala.org.au/occurrences/occurrences... 6 https://api.ala.org.au/occurrences/index/fields 7 https://api.ala.org.au/occurrences/occurrences... 8 https://api.ala.org.au/occurrences/occurrences... 9 https://api.ala.org.au/occurrences/occurrences... 10 https://api.ala.org.au/occurrences/assertions/... 11 https://api.ala.org.au/namematching/api/search... 12 https://api.ala.org.au/namematching/api/search... 13 https://api.ala.org.au/namematching/api/search... 14 https://api.ala.org.au/species/species/lookup/... 15 https://api.ala.org.au/namematching/api/getByT... 16 https://api.ala.org.au/logger/service/logger/r... 17 https://api.ala.org.au/specieslist/ws/speciesL... 18 https://api.ala.org.au/specieslist/ws/speciesList 19 https://api.ala.org.au/images/ws/image/{id}/or... 20 https://api.ala.org.au/images/ws/getImageInfoF... 21 https://api.ala.org.au/images/ws/image/{imageID} 22 https://api.ala.org.au/images/ws/licence 23 https://api.ala.org.au/doi/api/doi/{doi_string... 24 https://api.ala.org.au/dqf-service/api/v1/data... 25 https://api.ala.org.au/dqf-service/api/v1/data... 26 https://api.ala.org.au/metadata/ws/dataProvider 27 https://api.ala.org.au/metadata/ws/dataResource 28 https://api.ala.org.au/occurrences/qid 29 https://api.ala.org.au/common/api/getAuthConfig called_by functional method 0 show_all-collections True GET 1 atlas_taxonomy True GET 2 atlas_taxonomy True GET 3 show_all-fields True GET 4 atlas_species True GET 5 atlas_occurrences True GET 6 show_all-fields True GET 7 show_values-fields True GET 8 atlas_counts True GET 9 atlas_counts True GET 10 show_all-assertions True GET 11 search_taxa True GET 12 search_taxa True GET 13 search_taxa True POST 14 atlas_species True POST 15 search_identifiers True GET 16 show_all-reasons True GET 17 show_values-lists True GET 18 show_all-lists True GET 19 media_download True GET 20 media_metadata True POST 21 media_metadata True GET 22 show_all-licences True GET 23 doi_download True GET 24 show_values-profiles True GET 25 show_all-profiles True GET 26 show_all-providers True GET 27 show_all-datasets True GET 28 atlas_occurrences True POST 29 get_authentication_tokens True GET
- galah.search_taxa(taxa=None, identifiers=None, specific_epithet=None, scientific_name=None, config_file=None)#
Look up taxonomic names before downloading data from the ALA, using
atlas_occurrences(),atlas_species()oratlas_counts(). Taxon information returned bysearch_taxa()may be passed to thetaxaargument ofatlasfunctions.search_taxa()allows users to disambiguate homonyms (i.e. where the same name refers to taxa in different clades) prior to downloading data.- Parameters:
taxa (string) – one or more scientific names to search.
identifiers (string / list) – one or more taxonomic identifiers (such as guid or taxonConceptID) to search.
specific_epithet (list) – search taxonomic levels by using the argument “specificEpithet”.
scientific_name (dictionary) – search taxonomic levels by using the argument “scientificName”.
verbose (logical) – If
True, galah gives more information like URLs of your queries. Defaults toFalse
- Return type:
An object of class
pandas.DataFrame.
Examples
Get taxonomic identifiers for “Vulpes vulpes”
import galah galah.search_taxa(taxa="Vulpes vulpes")
[17] scientificName scientificNameAuthorship ... issues vernacularName 0 Vulpes vulpes Linnaeus, 1758 ... [noIssue] Fox [1 rows x 14 columns]
Get the species name from a taxonomic identifier
import galah galah.search_taxa(identifiers="https://id.biodiversity.org.au/node/apni/2914510")
[13] scientificName scientificNameAuthorship \ 0 Eucalyptus blakelyi Maiden taxonConceptID rank matchType \ 0 https://id.biodiversity.org.au/node/apni/2914510 species taxonIdMatch kingdom phylum classs order family genus \ 0 Plantae Charophyta Equisetopsida Myrtales Myrtaceae Eucalyptus species issues vernacularName 0 Eucalyptus blakelyi noIssue Blakely's Red GumSearch taxonomic levels by using the key word “specificEpithet”
import galah galah.search_taxa(specific_epithet=["class=aves","family=pardalotidae","genus=pardalotus","specificEpithet=punctatus"])
[16] scientificName scientificNameAuthorship \ 0 Pardalotus (Pardalotus) punctatus (Shaw, 1792) taxonConceptID rank matchType \ 0 https://biodiversity.org.au/afd/taxa/5254fe03-... species exactMatch kingdom phylum classs order family genus \ 0 Animalia Chordata Aves Passeriformes Pardalotidae Pardalotus species issues vernacularName 0 Pardalotus punctatus noIssue Spotted PardaloteSearch taxonomic levels by using the key word “scientificName”
import galah galah.search_taxa(scientific_name={"family": ["pardalotidae","maluridae"],"scientificName": ["pardolatus striatus","malurus cyaneus"]})
[16] scientificName scientificNameAuthorship \ 0 Pardalotus (Pardalotinus) striatus (Gmelin, 1789) 1 Malurus (Malurus) cyaneus (Ellis, 1782) taxonConceptID rank matchType \ 0 https://biodiversity.org.au/afd/taxa/e3103245-... species fuzzyMatch 1 https://biodiversity.org.au/afd/taxa/ae56080e-... species exactMatch kingdom phylum classs order family genus \ 0 Animalia Chordata Aves Passeriformes Pardalotidae Pardalotus 1 Animalia Chordata Aves Passeriformes Maluridae Malurus species issues vernacularName 0 Pardalotus striatus noIssue Striated Pardalote 1 Malurus cyaneus noIssue Superb Fairy-wren
- galah.search_values(field=None, value=None, lists=False, column_name=None, config_file=None)#
Users may wish to see the specific values within a chosen field, profile or list to narrow queries or understand more about the information of interest.
search_values()allows users for search for specific values within a specified field.- Parameters:
field (string) – A string to specify what type of parameters should be searched.
value (string) – A string specifying a search term. Not case sensitive.
lists (logical) – This lets
show_values()know if you want to look up fields, or if you want to look up species in lists. Default is False.verbose (logical) – This option is available for users who want to know what URLs this function is using to get the value. Default to False.
- Return type:
An object of class
pandas.DataFrame.
Examples
import galah galah.search_values(field='basisOfRecord',value='OBS')
#.. program-output:: python -c ‘import galah; print(galah.search_values(field='basisOfRecord',value='obs'))’
- galah.show_all(assertions=False, atlases=False, apis=False, collection=False, datasets=False, fields=False, licences=False, lists=False, profiles=False, providers=False, ranks=False, reasons=False, config_file=None)#
The living atlases store a huge amount of information, above and beyond the occurrence records that are their main output. In galah, one way that users can investigate this information is by showing all the available options or categories for the type of information they are interested in.
show_all()is a helper function that can display multiple types of information, displaying all valid options for the information specified.- Parameters:
assertions (logical) – Show results of data quality checks run by each atlas
atlases (logical) – Show what atlases are available
apis (logical) – Show what APIs & functions are available for each atlas
collection (logical) – Show the specific collections within those institutions
datasets (logical) – Shows all the data groupings within those collections
fields (logical) – Show fields that are stored in an atlas
licences (logical) – Show what copyright licenses are applied to media
lists (logical) – Show what species lists are available
profiles (logical) – Show what data profiles are available
providers (logical) – Show which institutions have provided data
ranks (logical) – Show valid taxonomic ranks (e.g. Kingdom, Class, Order, etc.)
reasons (logical) – Show what values are acceptable as ‘download reasons’ for a specified atlas
- Return type:
An object of class
pandas.DataFramecontaining all data of interest.
Examples
import galah galah.show_all(datasets=True)
name \ 0 ALA Taxonomy List for Species Missing from Co... 1 "A" Flora EPBC 2 "H to O" flora EPBC 3 "P to Z" flora EPBC 4 (Appendix 2) Stratigraphic distribution of key... ... ... 8287 Zooplankton data from voyages of the research ... 8288 Zooplankton samples from Heron net trawls alon... 8289 Zooplankton sampling in the coastal waters of ... 8290 Zoos Victoria Moth Tracker 8291 zza uri uid 0 https://collections.ala.org.au/ws/dataResource... dr23929 1 https://collections.ala.org.au/ws/dataResource... dr24170 2 https://collections.ala.org.au/ws/dataResource... dr24172 3 https://collections.ala.org.au/ws/dataResource... dr24173 4 https://collections.ala.org.au/ws/dataResource... dr30390 ... ... ... 8287 https://collections.ala.org.au/ws/dataResource... dr29594 8288 https://collections.ala.org.au/ws/dataResource... dr23120 8289 https://collections.ala.org.au/ws/dataResource... dr15943 8290 https://collections.ala.org.au/ws/dataResource... dr22371 8291 https://collections.ala.org.au/ws/dataResource... dr33432 [8292 rows x 3 columns]
- galah.show_values(field=None, lists=False, config_file=None)#
Users may wish to see the specific values within a chosen field, profile or list to narrow queries or understand more about the information of interest.
show_values()provides users with these values.- Parameters:
field (string) – A string to specify what type of parameters should be shown.
lists (logical) – This lets
show_values()know if you want to look up fields, or if you want to look up species in lists. Default is False.verbose (logical) – This option is available for users who want to know what URLs this function is using to get the value. Default is False.
- Return type:
An object of class
pandas.DataFrame.
Examples
import galah galah.show_values(field='basisOfRecord')
field category 0 basisOfRecord HUMAN_OBSERVATION 1 basisOfRecord PRESERVED_SPECIMEN 2 basisOfRecord OCCURRENCE 3 basisOfRecord OBSERVATION 4 basisOfRecord MACHINE_OBSERVATION 5 basisOfRecord MATERIAL_SAMPLE 6 basisOfRecord LIVING_SPECIMEN 7 basisOfRecord FOSSIL_SPECIMEN 8 basisOfRecord MATERIAL_CITATION