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BILLING_SECDEP_INTEREST_PAY

The interest amount for security deposit calculated by billing, based on whether it is a fixed/floating rate

BILLING_SECDEP_INTEREST_PAY data is confidential, and is available only to the relevant participant.

Column Schema

BILLRUNNO

The billing run no. the SDA application is processed and interest calculated

SQL Type: NUMBER(3,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

CONTRACTYEAR

The billing contract year the SDA application is processed and interest calculated

SQL Type: NUMBER(4,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

PARTICIPANTID

The participant ID of the security deposit for whom the interest is paid

For more information, see the dedicated documentation page.

SQL Type: VARCHAR2(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

SECURITY_DEPOSIT_ID

The security deposit ID for which billing has calculated the Interest amount

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

WEEKNO

The billing week no. the SDA application is processed and interest calculated

Warning

There may be 53 weeks in a year, depending on how weeks align to the year start/end.

SQL Type: NUMBER(3,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

INTEREST_ACCT_ID

The interest account ID used by billing for calculating the interest. NULL if INTEREST_CALC_TYPE = FIXED

SQL Type: VARCHAR2(20) Polars Type: str

This column is not mandatory.

INTEREST_AMOUNT

The security deposit interest amount calculated by billing

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

INTEREST_CALC_TYPE

FIXED or DAILY

SQL Type: VARCHAR2(20) Polars Type: pl.Categorical

This column is not mandatory.

INTEREST_RATE

The STATIC Interest Rate used by Billing for calculating the interest. This is NULL if INTEREST_CALC_TYPE <> FIXED

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

New Data Timing

After posting a billing run (final and revision)

Code Examples

Polars

Casting is enums, categoricals etc is not essential, but may speed up parsing. Swapping int for pl.UInt16, pl.Int32 would also speed up parsing. However some of the datatypes are inferred, so they may be wrong.

This code deduplicates for you. Deduplication is normally only required across multiple months.

This code assumes that all columns are present, which may not be true for older files.

import polars as pl
import polars.selectors as cs

csv_paths = ["SOMEFILE.CSV", "OTHERFILE.CSV"]

lf = (
    pl.concat(
        [
            pl.scan_csv(
                csv_path,  # must be unzipped beforehand
                skip_rows=1,  # skip the header
                infer_schema=False,  # much faster
            )
            .filter(cs.by_index(0) == "D")  # drop the footer
            .select(~cs.by_index(range(4)))  # drop metadata columns
            for csv_path in csv_paths
        ],
        how="diagonal_relaxed",
    ).cast(
        {
            "BILLRUNNO": int,  # or pl.UInt16
            "CONTRACTYEAR": int,  # or pl.UInt16
            "PARTICIPANTID": pl.Categorical,
            "SECURITY_DEPOSIT_ID": str,
            "WEEKNO": int,  # or pl.UInt16
            "INTEREST_ACCT_ID": str,
            "INTEREST_AMOUNT": pl.Float64,
            "INTEREST_CALC_TYPE": pl.Categorical,
            "INTEREST_RATE": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['BILLRUNNO', 'CONTRACTYEAR', 'PARTICIPANTID', 'SECURITY_DEPOSIT_ID', 'WEEKNO']
    .unique(
        subset=[
            "BILLRUNNO",
            "CONTRACTYEAR",
            "PARTICIPANTID",
            "SECURITY_DEPOSIT_ID",
            "WEEKNO",
        ],
        keep="any",
    )
)

Nemosis

This table is not yet available in Nemosis.

Availability

Visibility: Private

This table is not available in the public monthly MMSDM archive. Is is only available to registered market participants over FTP inside a VPN.

Deduplication and PDR Loader Configuration

The primary keys are:

The transaction type is "insert", which means that you will usually not see duplicate data. If you do, you can deduplicate based on the primary keys, without sorting first. Rows from different files with the same primary keys should have the same values.

PDR Loader configuration is:

Report Name Report Subtype Version
BILLING SECDEP_INTEREST_PAY 1

This means that the CSV files start with metadata columns:

I,BILLING,SECDEP_INTEREST_PAY,1,...
D,BILLING,SECDEP_INTEREST_PAY,1,...

This page as JSON (schema documented here, but may change)

Download a JSON Schema specification for this table.

Official AEMO schema documentation

Other Information

Package: BILLING_RUN