wavesongs.data.xc

wavesongs.data.xc#

Query and download data from Xeno Canto

Functions

download_audios(df_dataset[, rootdir, ...])

Download audios from Xeno Canto with maad.utils.xc_download.

query_audios(specie_names[, max_nb_files, ...])

wavesongs.data.xc.download_audios(df_dataset: DataFrame, rootdir: str = './assets/audio', dataset_name: str = '', overwrite: bool = True, save_csv: bool = True, verbose: bool = True) → DataFrame[source]#

Download audios from Xeno Canto with maad.utils.xc_download.

Parameters:

  • df_dataset (pd.DataFrame) – Data Frame with the information to download.

  • country (str, optional) – _description_. Defaults to “Colombia”.

  • rootdir (str, optional) – _description_. Defaults to “./assets/audio”.

  • dataset_name (str, optional) – _description_. Defaults to ‘’.

  • overwrite (bool, optional) – _description_. Defaults to False.

  • save_csv (bool, optional) – _description_. Defaults to True.

  • verbose (bool, optional) – _description_. Defaults to True.

Returns:

Data Frame

Return type:

df_audios (pd.DataFrame)

wavesongs.data.xc.query_audios(specie_names: List[str] | List[List[str]], max_nb_files: int | None = None, random_seed: int = 2025, info: dict = {}, format_time=True, format_date=True, verbose: bool = True) → DataFrame[source]#

Query me from Xeno Canto with maad.utils.xc_multi_query.

Parameters:

  • specie_names (list[str], list[list[str]]) – List with english and scientific specie names.

  • max_nb_files (int, optional) – Maximum number of files to download. Defaults to None.

  • random_seed (int, optional) – Random seed. Defaults to 2025.

  • info (dict, optional) – Dictionary with information to query. Defaults to {}.

  • format_time (bool, optional) – Format time. Defaults to True.

  • format_date (bool, optional) – Format date. Defaults to True.

  • verbose (bool, optional) – Verbose. Defaults to True.

Returns:

Data Frame

Return type:

df_query (pd.DataFrame)

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