call_report.fca.institutions.read_institutions#

call_report.fca.institutions.read_institutions(*, release_dir: Path, dataframe_type: None = None) → NativeDataFrame[source]#

call_report.fca.institutions.read_institutions(*, release_dir: Path, dataframe_type: Literal['pandas']) → pandas.DataFrame

call_report.fca.institutions.read_institutions(*, release_dir: Path, dataframe_type: Literal['pyarrow_table']) → pyarrow.Table

call_report.fca.institutions.read_institutions(*, release_dir: Path, dataframe_type: Literal['polars_dataframe']) → polars.DataFrame

call_report.fca.institutions.read_institutions(*, release_dir: Path, dataframe_type: Literal['polars_lazyframe']) → polars.LazyFrame

Parse a release’s institution roster into a native dataframe.

Locates and parses the D_INST[_<YEAR>].TXT / INST...TXT file pair within release_dir, the same way any other schedule is parsed.

Parameters:

release_dirpathlib.Path: Path to one quarter’s extracted release files.
dataframe_type{“pandas”, “pyarrow_table”, “polars_lazyframe”, “polars_dataframe”}, optional: The dataframe type to convert the result to as a final step. Leave this None (the default) to get back whatever backend call_report.config.get_config currently has configured. Set it when the code that consumes this result needs a specific type, for example a pandas DataFrame while the package is configured to use polars.

Returns:

NativeDataFrame: A native dataframe of the configured backend (or of dataframe_type, if supplied), one row per institution.

Raises: