count_rows_by_keys

Counts rows with the same value.

Usage

This calculator allows you to count the number of occurrences that share the same value across defined columns. This calculator must be stored in model to be used.

This calculator can be used with the following method:

count_rows_by_key

Examples:

• The user wants to count the number of products per promotional event.

• The user wants to count the number of products per department.

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Main Parameters

The bold options represent the default values when the parameters are optional.

• input_columns list of columns used as input of the calculators: The list of columns that will be used to fill the output column.

• output_columns list of columns added by the calculators : Name of the filled column added to the dataset.

• global (true, false) Should this calculator be performed before data splitting during training for cross-validation

• steps [optionnal] (training, prediction, postprocessing) List of steps in a pipeline where columns from this calculator are added to the data. Note that when the training option is listed, the calculator is actually added during preprocessing.

• store_in_model [optionnal] (true, false) Please indicate whether the "calculated" columns by the calculator should be stored in the model or not to avoid recalculating them during prediction. This is only relevant if the calculated columns are added to both training and prediction. Without this parameter, the values will not be stored in the model. The following parameters only make sense if this parameter is set to true.

• stored_columns [required if store_in_model is true] List indicating the columns to be stored among the output_columns.

• stored_keys [required if store_in_model is true] List indicating the columns to use for identifying the correct values to join on the data for prediction among the stored values (logically, they are to be chosen from the input_columns).

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Specific Parameters

• keys_to_count Columns for which we want to compute cardinality.

• group_by Columns used for grouping keys to count.

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Examples

1. The user wants to count the number of products (item_id) per promotional event (event_id) :

calculated_cols:
  items_per_event:
    method: count_rows_by_keys
    input_columns:
    - item_id
    - event_id
    output_columns:
    - nb_items_per_event
    params:
      keys_to_count:
      - item_id
      group_by:
      - event_id
      store_in_model: True
      stored_keys:
      - event_id