The recent PR #7231 adds an API reference page for in-memory data representation.
With this, detailed documentation on the most commonly used time series machine types were also added.
However, documentation for the less common formats is still missing - we should add this.
Recipe:
- pick one type and help document it! (one pull request per type). See below for a list of undocumented types.
- use
get_examples from sktime.datatypes to generate some examples, and look at MTYPE_REGISTER for a short description. You can also use convert_to to see how already documented types convert to the documented one.
- add a docstring to the class in one of the
_check modules, e.g., sktime.datatypes._panel._check for one of the Panel mtypes. The name of the class is the same as below. All modules already contain complete examples, so "follow the pattern".
To identify a missing case, see the list below.
Alternatively, you can also:
- search for classes with empty docstrings in one of the
datasets _check modules, within the _series, _panel, _hierarchical or _table submodules.
- look at the "Data Format Specifications" page on the API reference (link), click through concrete representations and search for empty docstrings.
Docstrings should be completed with a description of the in-memory type. Example descriptions can be found for the more common types, in the API reference, or the aforementioned modules.
Classes currently empty:
FYI @Abhay-Lejith and @pranavvp16, as you wrote some of the respective plug-ins - helping with the docs would be much appreciated, since you know most about these!
The recent PR #7231 adds an API reference page for in-memory data representation.
With this, detailed documentation on the most commonly used time series machine types were also added.
However, documentation for the less common formats is still missing - we should add this.
Recipe:
get_examplesfromsktime.datatypesto generate some examples, and look atMTYPE_REGISTERfor a short description. You can also useconvert_toto see how already documented types convert to the documented one._checkmodules, e.g.,sktime.datatypes._panel._checkfor one of thePanelmtypes. The name of the class is the same as below. All modules already contain complete examples, so "follow the pattern".To identify a missing case, see the list below.
Alternatively, you can also:
datasets_checkmodules, within the_series,_panel,_hierarchicalor_tablesubmodules.Docstrings should be completed with a description of the in-memory type. Example descriptions can be found for the more common types, in the API reference, or the aforementioned modules.
Classes currently empty:
SeriesXArraySeriesDaskSeriesPolarsEagerSeriesGluontsListSeriesGluontsPandasPanelDaskPanelPolarsEagerPanelGluontsListPanelGluontsPandasHierarchicalDaskHierarchicalPolarsEagerTablePdDataFrameTablePdSeriesTableNp1DTableNp2DTableListOfDictTablePolarsEagerFYI @Abhay-Lejith and @pranavvp16, as you wrote some of the respective plug-ins - helping with the docs would be much appreciated, since you know most about these!