load_table()

audb.load_table(name, table, *, version=None, map=None, pickle_tables=True, cache_root=None, num_workers=1, verbose=True)[source]

Load a database table.

If you are interested in a single table from a database you can use audb.load_table() to directly load it. This will not download any media files to your disk, but share the cache with audb.load().

Parameters

  • name (str) – name of database

  • table (str) – load table from database

  • version (Optional[str]) – version of database

  • map (Optional[dict[str, str | Sequence[str]]]) – map scheme or scheme fields to column values. For example if your table holds a column speaker with speaker IDs, which is assigned to a scheme that contains a dict mapping speaker IDs to age and gender entries, map={'speaker': ['age', 'gender']} will replace the column with two new columns that map ID values to age and gender, respectively. To also keep the original column with speaker IDS, you can do map={'speaker': ['speaker', 'age', 'gender']}

  • pickle_tables (bool) – if True, tables are cached locally in their original format and as pickle files. This allows for faster loading, when loading from cache

  • cache_root (Optional[str]) – cache folder where databases are stored. If not set audb.default_cache_root() is used

  • num_workers (Optional[int]) – number of parallel jobs or 1 for sequential processing. If None will be set to the number of processors on the machine multiplied by 5

  • verbose (bool) – show debug messages

Return type

DataFrame

Returns

database table

Raises

ValueError – if a table is requested that is not part of the database

Examples

>>> df = audb.load_table("emodb", "emotion", version="1.4.1", verbose=False)
>>> df[:3]
                   emotion  emotion.confidence
file
wav/03a01Fa.wav  happiness                0.90
wav/03a01Nc.wav    neutral                1.00
wav/03a01Wa.wav      anger                0.95
>>> df = audb.load_table("emodb", "files", version="1.4.1", verbose=False)
>>> df[:3]
                                 duration speaker transcription
file
wav/03a01Fa.wav    0 days 00:00:01.898250       3           a01
wav/03a01Nc.wav    0 days 00:00:01.611250       3           a01
wav/03a01Wa.wav 0 days 00:00:01.877812500       3           a01
>>> df = audb.load_table(
...     "emodb",
...     "files",
...     version="1.4.1",
...     map={"speaker": "age"},
...     verbose=False,
... )
>>> df[:3]
                                 duration transcription  age
file
wav/03a01Fa.wav    0 days 00:00:01.898250           a01   31
wav/03a01Nc.wav    0 days 00:00:01.611250           a01   31
wav/03a01Wa.wav 0 days 00:00:01.877812500           a01   31