create_spatial

Format

create_spatial_lag(table, column, strategy='mean', result_table=None, key_column=None,
    weights=None, weights_def=None, save_weights_as=None, spatial_col=None, crs=None)

Parameters

The parameters for this pre-defined function are described in the following table.

Parameter	Description
`table`	Name of the spatial table.
`column`	The column of interest whose values are used to compute the spatial lag.
`strategy`	The strategy to be used to calculate the spatial lag; there are two possible choices: mean and median.
`result_table`	If specified, it calls the function `oml.create` to store a pandas `DataFrame` containing spatial lag in a table with the specified name.
`key_column`	If specified, the specified column is added to the resulting `DataFrame`. Otherwise, a column with the index of the `DataFrame` is attached to the result.
`weights`	Required when trying to use spatial weights already stored in the data store. Internally it calls the function `olm.ds.load`. The supported parameters are `ds_name` and `obj_name`, indicating the data store name and object name, respectively.
`weights_def`	Required if the parameter `weights` is not defined. Establishes the relationship between neighboring locations. This is passed as a json object specifying the type of the weights definition and its parameters. Each parameter is defined in detail in the API Reference documentation. The following lists the supported types and parameters: KNN: `[k]` Kernel: `[bandwidth, fixed, k, function]` DistanceBand: `[threshold, p, alpha, binary]` Queen Rook
`save_weights_as`	Only used if `weights_def` is defined. Specifies how the spatial weights are stored in the data store. The value is a json file that determines the parameters of `oml.ds.save`. The supported parameters are: `[ds_name, obj_name, overwrite_ds, append, overwrite_obj, grantable, compression]`. Some parameter names slightly differ from those in the `oml.ds.save` function. The parameter `overwrite_obj` is used to indicate whether an already existing object should be replaced with the current object.
`spatial_col`	Specifies the column containing the geometries. The column can be specified in the table’s metadata. If not specified, the column name is retrieved from the table.
`crs`	Specifies the Coordinate Reference System. If not specified, it is inferred from the table.

Example

The following code calculates the spatial lag of a specific column according to given spatial weights. For each row, it calculates the average value of a particular column from neighboring locations. It uses the median_income column and spatial weights from a datastore.

select *
    from table( 
        pyqEval(
            '{  
                "oml_connect": true, 
                "table": "oml_user.la_block_groups", 
                "key_column": "geoid",
                "column": "median_income",
                "weights": {"ds_name":"spatial", "obj_name": "la_bg_knn4"}
            }',
            '{ "geoid": "VARCHAR2(50)", "MEDIAN_INCOME_SLAG": "NUMBER" }',
            'create_spatial_lag'
        )
    );

The result contains the average income from neighboring locations for each row. Note that the index comes from the key_column parameter, which is the geoid column in this case.

Description of create_spatial_lag.png follows

Description of the illustration create_spatial_lag.png