readabs 0.1.8

Get ABS timeseries data in pandas DataFrames

readabs

Description

Readabs is an open-source Python package to download and work with timeseries data from the Australian Bureau of Statistics (ABS) and the Reserve Bank of Australia (RBA), using pandas DataFrames.

Import

import readabs as ra
from readabs import metacol as mc  # column names for ABS metadata
from readabs import rba_metacol as rm  # column names for RBA metadata

ABS Functions

• abs_catalogue() - returns a pandas DataFrame of ABS catalogue numbers. Note: typically, an ABS Catalogue item comprises multiple data tables.
• print_abs_catalogue() - prints a formatted table of ABS catalogue numbers.
• read_abs_cat() - returns a tuple containing the complete ABS Catalogue information as a python dictionary of pandas DataFrames (one for each table in the catalogue), as well as the associated metadata in a separate DataFrame.
• read_abs_series() - get one or more series for a specified catalogue and the specified series identifier(s). Returns a tuple of two DataFrames, one for the primary data and one for the metadata.
• read_abs_by_desc() - get one or more series, for a specified catalogue number, based on searching for matching data item descriptions. Returns a tuple of (1) a dictionary with the series name as the key and the pandas Series as the value and (2) a DataFrame of metadata.
• search_abs_meta() - searches the ABS metadata for 1 or more rows that match the desired search-terms. Returns the matching rows from the metadata.
• find_abs_id() - search the ABS metadata for the unique series that matches the search terms. Returns a tuple of the table name, series_id and units for the series_id that matches the search terms. Raises an exception if no items, or more than one item in the metadata matches the search terms.

RBA Functions

• rba_catalogue() - returns a pandas DataFrame of RBA catalogue numbers. Note: whereas multiple data tables are associated with an ABS catalogue number, only a single table is associated with an RBA catalogue number.
• print_rba_catalogue() - prints a formatted table of RBA catalogue numbers.
• read_rba_table() - read a table from the RBA website and return the actual data and the metadata in a tuple of two DataFrames.
• read_rba_ocr() - read the Official Cash Rate (OCR) from the RBA website. Returns a pandas Series with either daily or monthly frequency.

Utility Functions

• recalibrate() - returns a pandas Series/DataFrame where the units have been scaled to be less than 1,000. Also adjusts the units label.
• recalibrate_value() - recalibrate a single numeric value.
• percent_change() - calculate percentage change for time series data.
• annualise_rates() - convert rates to annualized values.
• annualise_percentages() - convert percentages to annualized values.
• qtly_to_monthly() - convert quarterly data to monthly frequency.
• monthly_to_qtly() - convert monthly data to quarterly frequency.

Data Types and Metadata

• Datatype - enumeration for ABS data types.
• ReadArgs - TypedDict for keyword arguments used by ABS reading functions.
• metacol - column names for ABS metadata.
• rba_metacol - column names for RBA metadata.

For more information

For complete details, refer to the API documentation in the ./docs directory, or visit the generated HTML documentation.

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