link_rows_by_id
Create network links using one or more lists of target ids.
For each row this step iterates over the lists of IDs in one or more target columns, and if a ID exists also
in the source column, the corresponding rows will be connected.
Note that while this step allows multiple input columns to be used as link targets, it does not allow for the
specification of link weights. See the step
link_rows for creating weighted networks. All link weights will
be set to 1.0 by default. But see the weight_factor param to specify another constant instead.
Usage
The following example shows how the step can be used in a recipe.Examples
Examples
Given a dataset
ds, where each row is associated with a twitter user (identified by column account_id), the following line connects each of these users with other users specified in columns reply_ids and mention_ids.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 column containing for each item a list of row numbers identfying all other items it
will be linked to.
A column containing for each item a list of weights identfying the “importance” of each
link to other items identified in the
targets column (counting how many times a consecutive
pair of items was found together in the sequences).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
Multiply link weights by this number.