@@ -63,7 +63,7 @@ Dynamic tables contain a datetime column that allows NEMOSIS to filter their con
6363
6464To learn more about each dynamic table visit the [ wiki] ( https://github.com/UNSW-CEEM/NEMOSIS/wiki ) .
6565
66- You can view the static tables available by printing the NEMOSIS default settings.
66+ You can view the dynamic tables available by printing the NEMOSIS default settings.
6767
6868``` python
6969from nemosis import defaults
@@ -108,8 +108,8 @@ To return only a subset of a particular table's columns, use the `select_columns
108108``` python
109109from nemosis import dynamic_data_compiler
110110
111- dynamic_data_compiler(start_time, end_time, table, raw_data_cache,
112- select_columns = [' REGIONID' , ' SETTLEMENTDATE' , ' RRP' ])
111+ price_data = dynamic_data_compiler(start_time, end_time, table, raw_data_cache,
112+ select_columns = [' REGIONID' , ' SETTLEMENTDATE' , ' RRP' ])
113113```
114114
115115To see what columns a table has, you can inspect NEMOSIS' defaults.
@@ -128,15 +128,15 @@ In the example below, the table will be filtered to only return rows where `REGI
128128``` python
129129from nemosis import dynamic_data_compiler
130130
131- dynamic_data_compiler(start_time, end_time, table, raw_data_cache, filter_cols = [' REGIONID' ], filter_values = ([' SA1' ],))
131+ price_data = dynamic_data_compiler(start_time, end_time, table, raw_data_cache, filter_cols = [' REGIONID' ], filter_values = ([' SA1' ],))
132132```
133133
134134Several 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:
135135
136136``` python
137137from nemosis import dynamic_data_compiler
138138
139- dynamic_data_compiler(start_time, end_time, ' DISPATCHLOAD' , raw_data_cache, filter_cols = [' DUID' , ' INTERVENTION' ], filter_values = ([' GSTONE1' , ' HDWF2' ], [0 ]))
139+ unit_dispatch_data = dynamic_data_compiler(start_time, end_time, ' DISPATCHLOAD' , raw_data_cache, filter_cols = [' DUID' , ' INTERVENTION' ], filter_values = ([' GSTONE1' , ' HDWF2' ], [0 ]))
140140```
141141
142142###### Caching options
@@ -170,7 +170,7 @@ The example below downloads parquet data into the cache.
170170``` python
171171from nemosis import cache_compiler
172172
173- price_data = cache_compiler(start_time, end_time, table, raw_data_cache, fformat = ' parquet' )
173+ cache_compiler(start_time, end_time, table, raw_data_cache, fformat = ' parquet' )
174174```
175175
176176### Data from static tables
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