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New release version, update readme, remove cols from trading load
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.gitignore

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@@ -23,3 +23,4 @@ nemosis/build/gui/gui.exe.manifest
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nemosis/build/gui/base_library.zip
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env/*
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nemosis/raw_aemo_data/*
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NEMOSIS.exe

README.md

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@@ -63,7 +63,7 @@ Dynamic tables contain a datetime column that allows NEMOSIS to filter their con
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To learn more about each dynamic table visit the [wiki](https://github.com/UNSW-CEEM/NEMOSIS/wiki).
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You can view the static tables available by printing the NEMOSIS default settings.
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You can view the dynamic tables available by printing the NEMOSIS default settings.
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```python
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from nemosis import defaults
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```python
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from nemosis import dynamic_data_compiler
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dynamic_data_compiler(start_time, end_time, table, raw_data_cache,
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select_columns=['REGIONID', 'SETTLEMENTDATE', 'RRP'])
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price_data = dynamic_data_compiler(start_time, end_time, table, raw_data_cache,
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select_columns=['REGIONID', 'SETTLEMENTDATE', 'RRP'])
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```
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To see what columns a table has, you can inspect NEMOSIS' defaults.
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```python
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from nemosis import dynamic_data_compiler
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dynamic_data_compiler(start_time, end_time, table, raw_data_cache, filter_cols=['REGIONID'], filter_values=(['SA1'],))
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price_data = dynamic_data_compiler(start_time, end_time, table, raw_data_cache, filter_cols=['REGIONID'], filter_values=(['SA1'],))
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```
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Several filters can be applied simultaneously. A common filter is to extract pricing data excluding any physical intervention dispatch runs (`INTERVENTION == 0` is the appropriate filter, see [here](https://github.com/UNSW-CEEM/NEMOSIS/wiki/Column-Summary#intervention)). Below is an example of filtering to get data for Gladstone Unit 1 and Hornsdale Wind Farm 2 excluding any physical dispatch runs:
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```python
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from nemosis import dynamic_data_compiler
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dynamic_data_compiler(start_time, end_time, 'DISPATCHLOAD', raw_data_cache, filter_cols=['DUID', 'INTERVENTION'], filter_values=(['GSTONE1', 'HDWF2'], [0]))
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unit_dispatch_data = dynamic_data_compiler(start_time, end_time, 'DISPATCHLOAD', raw_data_cache, filter_cols=['DUID', 'INTERVENTION'], filter_values=(['GSTONE1', 'HDWF2'], [0]))
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```
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###### Caching options
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```python
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from nemosis import cache_compiler
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price_data = cache_compiler(start_time, end_time, table, raw_data_cache, fformat='parquet')
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cache_compiler(start_time, end_time, table, raw_data_cache, fformat='parquet')
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```
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### Data from static tables

nemosis/defaults.py

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'LOWER60SECLOCALDISPATCH', 'LOWER6SECLOCALDISPATCH', 'RAISE5MINLOCALDISPATCH',
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'RAISE60SECLOCALDISPATCH', 'RAISE6SECLOCALDISPATCH', 'LOWERREGLOCALDISPATCH',
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'RAISEREGLOCALDISPATCH', 'INITIALSUPPLY', 'CLEAREDSUPPLY', 'TOTALINTERMITTENTGENERATION',
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'DEMAND_AND_NONSCHEDGEN', 'UIGF', 'SEMISCHEDULE_CLEAREDMW', 'SEMISCHEDULE_COMPLIANCEMW'],
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'DEMAND_AND_NONSCHEDGEN', 'UIGF'],
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'TRADINGINTERCONNECT': ['SETTLEMENTDATE', 'INTERCONNECTORID', 'MWFLOW', 'METEREDMWFLOW', 'MWLOSSES'],
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setup.py

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setuptools.setup(
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name="nemosis",
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version="1.4.0",
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author="Nicholas Gorman",
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version="2.0.1",
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author="Nicholas Gorman, Abhijith Prakash",
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author_email="[email protected]",
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description="A tool for accessing AEMO data.",
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long_description="A tool for accessing AEMO data.",

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