teehr.LocationAttributeTable

class teehr.LocationAttributeTable(ev)

Bases: BaseTable

Access methods to location attributes table.

Methods

distinct_values	Return distinct values for a column.
field_enum	Get the location attribute fields enum.
fields	Return table columns as a list.
filter	Apply a filter.
load_csv	Import location_attributes from CSV file format.
load_parquet	Import location_attributes from parquet file format.
order_by	Apply an order_by.
query	Run a query against the table with filters and order_by.
to_geopandas	Return GeoPandas DataFrame.
to_pandas	Return Pandas DataFrame for Location Attributes.
to_sdf	Return PySpark DataFrame.
validate	Validate the dataset table against the schema.

field_enum() → LocationAttributeFields

Get the location attribute fields enum.

load_csv(in_path: Path | str, pattern: str = '**/*.csv', field_mapping: dict | None = None, **kwargs)

Import location_attributes from CSV file format.

Parameters:

• in_path (Union[Path, str]) – The input file or directory path. CSV file format.

• field_mapping (dict, optional) – A dictionary mapping input fields to output fields. Format: {input_field: output_field}

• **kwargs – Additional keyword arguments are passed to pd.read_parquet().

Notes

The TEEHR Location Attribute table schema includes fields:

• location_id

• attribute_name

• value

load_parquet(in_path: Path | str, pattern: str = '**/*.parquet', field_mapping: dict | None = None, **kwargs)

Import location_attributes from parquet file format.

Parameters:

• in_path (Union[Path, str]) – The input file or directory path. Parquet file format.

• field_mapping (dict, optional) – A dictionary mapping input fields to output fields. Format: {input_field: output_field}

• **kwargs – Additional keyword arguments are passed to pd.read_parquet().

Notes

The TEEHR Location Attribute table schema includes fields:

• location_id

• attribute_name

• value

to_geopandas()

Return GeoPandas DataFrame.

to_pandas()

Return Pandas DataFrame for Location Attributes.