Using geographical coordinates provided by latitude and longitude columns, enriches the input dataset with a subset of the 2011 Spanish census. See below for the seven features to be added by the step.Documentation Index
Fetch the complete documentation index at: https://docs.graphext.com/llms.txt
Use this file to discover all available pages before exploring further.
Usage
The following example shows how the step can be used in a recipe.Examples
Examples
- Example 1
- Signature
Since the step has no configuration parameters, it’s simply
Inputs & Outputs
The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced
by name e.g. "churn-clf").
Inputs
Inputs
Outputs
Outputs
A numeric column containing the percentage of immigrants registered in the area.
A numeric column containing the percentage of married people in the area.
A numeric column containing the average age in the area.
A numeric column containing the average level of education.
A numeric column containing the average size of households in square meters.
A numeric column containing the average number of household members.
A numeric column containing an index in the range 1-9 summarizing the overall quality of the location; lower
values being better.
Configuration
The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e.step(..., {"param": "value", ...}) -> (output).
Parameters
Parameters
This step doesn’t expect any configuration.