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PARTICIPANTCLASS

PARTICIPANTCLASS sets out valid participant classifications.

PARTICIPANTCLASS data is public, so is available to all participants.

Source

PARTICIPANTCLASS updates only if classifications change. This table changes infrequently.

Column Schema

PARTICIPANTCLASSID

Class of participant

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

Examples:

  • MARKET PARTICIPANT
  • NONMARKET
  • POOL PARTICIPANT
  • SPECIAL PARTICIPANT

DESCRIPTION

Description of participant class

SQL Type: VARCHAR2(64) Polars Type: str

This column is not mandatory.

Examples:

  • Market participant
  • Non Market Participant
  • Pool Participant
  • Special Participant

LASTCHANGED

Last date and time record changed

For more information, see the dedicated documentation page.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 1998/06/30 22:01:24

New Data Timing

When classifications change

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

# e.g. "2029/03/15 00:05:00"
dt_s_fmt = "%Y/%m/%d %H:%M:%S"

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",
    )
    .with_columns(
        pl.col("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast({"PARTICIPANTCLASSID": str, "DESCRIPTION": str})
    # Deduplicate
    # We want one row per ['PARTICIPANTCLASSID']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["PARTICIPANTCLASSID"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_PARTICIPANTCLASS_FILE01_202609010000.zip

PARTICIPANTCLASSIDDESCRIPTIONLASTCHANGED
NONMARKETNon Market Participant1998/06/30 22:01:24
MARKET PARTICIPANTMarket participant1998/06/30 22:01:24
SPECIAL PARTICIPANTSpecial Participant1998/06/30 22:01:24
POOL PARTICIPANTPool Participant1998/11/26 16:54:56

CSETP.WORLDDVD_PARTICIPANTCLASSAEMOPUBLIC2026/10/0916:21:29001791526889499MONTHLY_ARCHIVE001791526889499
IPARTICIPANT_REGISTRATIONPARTICIPANTCLASS1PARTICIPANTCLASSIDDESCRIPTIONLASTCHANGED
DPARTICIPANT_REGISTRATIONPARTICIPANTCLASS1NONMARKETNon Market Participant1998/06/30 22:01:24
DPARTICIPANT_REGISTRATIONPARTICIPANTCLASS1MARKET PARTICIPANTMarket participant1998/06/30 22:01:24
DPARTICIPANT_REGISTRATIONPARTICIPANTCLASS1SPECIAL PARTICIPANTSpecial Participant1998/06/30 22:01:24
DPARTICIPANT_REGISTRATIONPARTICIPANTCLASS1POOL PARTICIPANTPool Participant1998/11/26 16:54:56
CEND OF REPORT7

PARTICIPANTCLASSID,DESCRIPTION,LASTCHANGED
NONMARKET,"Non Market Participant","1998/06/30 22:01:24"
"MARKET PARTICIPANT","Market participant","1998/06/30 22:01:24"
"SPECIAL PARTICIPANT","Special Participant","1998/06/30 22:01:24"
"POOL PARTICIPANT","Pool Participant","1998/11/26 16:54:56"

C,SETP.WORLD,DVD_PARTICIPANTCLASS,AEMO,PUBLIC,2026/10/09,16:21:29,001791526889499,MONTHLY_ARCHIVE,001791526889499
I,PARTICIPANT_REGISTRATION,PARTICIPANTCLASS,1,PARTICIPANTCLASSID,DESCRIPTION,LASTCHANGED
D,PARTICIPANT_REGISTRATION,PARTICIPANTCLASS,1,NONMARKET,"Non Market Participant","1998/06/30 22:01:24"
D,PARTICIPANT_REGISTRATION,PARTICIPANTCLASS,1,"MARKET PARTICIPANT","Market participant","1998/06/30 22:01:24"
D,PARTICIPANT_REGISTRATION,PARTICIPANTCLASS,1,"SPECIAL PARTICIPANT","Special Participant","1998/06/30 22:01:24"
D,PARTICIPANT_REGISTRATION,PARTICIPANTCLASS,1,"POOL PARTICIPANT","Pool Participant","1998/11/26 16:54:56"
C,"END OF REPORT",7

Availability

Visibility: Public

This table is in the public monthly MMSDM archive.

I have collated the list of all those files into one place, in this CSV metadata file. (Columns year, month, url, compressed_size in bytes).

The earliest available data is month 1 of 2015. The most recent available data is month 9 of 2026.

Every month in between has a file. (No gaps.)

Data Size

Each year of data is approximately 6 KB when zipped, 58 KB as unzipped CSV.

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
PARTICIPANT_REGISTRATION PARTICIPANTCLASS 1

This means that the CSV files start with metadata columns:

I,PARTICIPANT_REGISTRATION,PARTICIPANTCLASS,1,...
D,PARTICIPANT_REGISTRATION,PARTICIPANTCLASS,1,...

Indexes

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: PARTICIPANT_REGISTRATION