segment_rows
Create a segmentation using graphext’s advanced query syntax (similar to Elasticsearch).
Usage
The following examples show how the step can be used in a recipe.
This simple query creates a new segmentation differentiating between adults and minors:
This simple query creates a new segmentation differentiating between adults and minors:
Flag clients that are exactly 19 years old and 21 years old
Bin competitors who are over 27 years of age but below the mean age
Select all who belong to the cool class
Segment all belonging to the most frequent 4 classes and least frequent 3
For those aged 18, separate on who earn more than 5 dollars monthly on average and 5 or less
General syntax for using the step in a recipe. Shows the inputs and outputs the step is expected to receive and will produce respectively. For futher details see sections below.
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").
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).
The graphext advanced query used to identify the rows to include in each segment.