class DatasetModel(loggers.ModelLoggerMixin, models.Model):
Minimal model representing a dataset.
This is basically a Django representation of the LyDataset class.
Its DatasetModel.load_dataframe method makes use of the function
cached_load_dataframe to load the dataset into a pandas DataFrame.
Note that this function uses joblib to cache the results of the function call
in a persistent location given by the JOBLIB_CACHE_DIR setting.
| Class | |
Meta options for the DatasetModel. |
| Method | __str__ |
Return the name of the dataset. |
| Method | get |
Assemble kwargs from this model's field. |
| Method | get |
Create a LyDataset from this model. |
| Method | get |
Return the GitHub repository object. |
| Method | load |
Load the underlying table. |
| Method | save |
Update the is_private field based on the GitHub repository. |
| Class Variable | institution |
Undocumented |
| Class Variable | last |
Undocumented |
| Class Variable | ref |
Undocumented |
| Class Variable | repo |
Undocumented |
| Class Variable | subsite |
Undocumented |
| Class Variable | year |
Undocumented |
| Instance Variable | is |
Undocumented |
| Instance Variable | last |
Undocumented |
| Property | name |
Return the name of the dataset. |
Assemble kwargs from this model's field.
These will both be used to call the cached_load_dataframe function as well
as initialize a LyDataset object.
Load the underlying table.
This calls the cached_load_dataframe function with the assembled
kwargs and returns the resulting pd.DataFrame.
lyprox.loggers.ModelLoggerMixin.saveUpdate the is_private field based on the GitHub repository.