transform: transform and calculate data in tables

Code author: Peter Kraus

The function dgpost.utils.transform.transform() processes the below specification in order to do data transformation on an extracted (or supplied) pd.DataFrame.

pydantic model dgbowl_schemas.dgpost.recipe.Transform

Calculate and otherwise transform the data in the tables.

Show JSON schema

{
   "title": "Transform",
   "description": "Calculate and otherwise transform the data in the tables.",
   "type": "object",
   "properties": {
      "table": {
         "title": "Table",
         "type": "string"
      },
      "with": {
         "title": "With",
         "type": "string"
      },
      "using": {
         "items": {
            "type": "object"
         },
         "title": "Using",
         "type": "array"
      }
   },
   "additionalProperties": false,
   "required": [
      "table",
      "with",
      "using"
   ]
}

Config:

• extra: str = forbid

• populate_by_name: bool = True

field table: str [Required]

The name of the table loaded in memory to be transformed.

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

field with_: str [Required] (alias 'with')

The name of the transform function from dgpost’s transform library.

field using: Sequence[Dict[str, Any]] [Required]

Specification of any parameters required by the transform function.

Warning

The arguments passed to the transformation function in the transform.using Sequence have to be dict with str-type keys. The values will be coerced to appropriate types using the transform function decorator: dgpost.transform.helpers.load_data().

dgpost.utils.transform.transform(table, withstr, using)

Return type:

None