CUSTOMER Variability of product ProductGroup based on item TotalCost 28d

SDK code to create CUSTOMER_Variability_of_product_ProductGroup_based_on_item_TotalCost_28d¶

Feature description:

The feature evaluates the distribution of a customer's item's TotalCost across various product's ProductGroup categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific product's ProductGroup categories.

In [ ]:

import featurebyte as fb
fb.use_profile("tutorial")

import featurebyte as fb fb.use_profile("tutorial")

Activate catalog¶

See SDK reference for catalogs

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catalog = fb.Catalog.activate("Grocery Dataset Tutorial")

catalog = fb.Catalog.activate("Grocery Dataset Tutorial")

Set windows for aggregation¶

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windows = ['28d']

windows = ['28d']

Get view from table¶

See SDK reference for views

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# Get view from GROCERYPRODUCT dimension table.
groceryproduct_view = catalog.get_view("GROCERYPRODUCT")

# Get view from GROCERYPRODUCT dimension table. groceryproduct_view = catalog.get_view("GROCERYPRODUCT")

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# Get view from INVOICEITEMS item table.
invoiceitems_view = catalog.get_view("INVOICEITEMS")

# Get view from INVOICEITEMS item table. invoiceitems_view = catalog.get_view("INVOICEITEMS")

Join views¶

See SDK reference for views

In [ ]:

# Join GROCERYPRODUCT view to INVOICEITEMS view.
invoiceitems_view = invoiceitems_view.join(groceryproduct_view, rsuffix="")

# Join GROCERYPRODUCT view to INVOICEITEMS view. invoiceitems_view = invoiceitems_view.join(groceryproduct_view, rsuffix="")

Do window aggregation from INVOICEITEMS¶

See SDK reference for features

See SDK reference to groupby a view

See SDK reference to do aggregation over time

See SDK reference for feature group

See list of aggregation operations

In [ ]:

# Group INVOICEITEMS view by customer entity (GroceryCustomerGuid) across different ProductGroups.
invoiceitems_view_by_customer_across_productgroup =\
invoiceitems_view.groupby(
    ['GroceryCustomerGuid'], category="ProductGroup"
)

# Group INVOICEITEMS view by customer entity (GroceryCustomerGuid) across different ProductGroups. invoiceitems_view_by_customer_across_productgroup =\ invoiceitems_view.groupby( ['GroceryCustomerGuid'], category="ProductGroup" )

In [ ]:

# Distribution representing the cumulative TotalCost of item, categorized by their respective
# product's ProductGroup, for the customer over time.
feature_group =\
invoiceitems_view_by_customer_across_productgroup.aggregate_over(
    "TotalCost", method=fb.AggFunc.SUM,
    feature_names=[
        "CUSTOMER_item_TotalCost_across_product_ProductGroups"
        + "_" + w for w in windows
    ],
    windows=windows
)
# Get CUSTOMER_item_TotalCost_across_product_ProductGroups_28d object from feature group.
customer_item_totalcost_across_product_productgroups_28d =\
feature_group["CUSTOMER_item_TotalCost_across_product_ProductGroups_28d"]

# Distribution representing the cumulative TotalCost of item, categorized by their respective # product's ProductGroup, for the customer over time. feature_group =\ invoiceitems_view_by_customer_across_productgroup.aggregate_over( "TotalCost", method=fb.AggFunc.SUM, feature_names=[ "CUSTOMER_item_TotalCost_across_product_ProductGroups" + "_" + w for w in windows ], windows=windows ) # Get CUSTOMER_item_TotalCost_across_product_ProductGroups_28d object from feature group. customer_item_totalcost_across_product_productgroups_28d =\ feature_group["CUSTOMER_item_TotalCost_across_product_ProductGroups_28d"]

Derive feature from aggregation across categories¶

See list of feature transforms

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# Get Variability of product ProductGroup based on item TotalCost from
# CUSTOMER_item_TotalCost_across_product_ProductGroups_28d
customer_variability_of_product_productgroup_based_on_item_totalcost_28d =\
customer_item_totalcost_across_product_productgroups_28d.cd.entropy()
# Give a name to new feature
customer_variability_of_product_productgroup_based_on_item_totalcost_28d.name = \
"CUSTOMER_Variability_of_product_ProductGroup_based_on_item_TotalCost_28d"

# Get Variability of product ProductGroup based on item TotalCost from # CUSTOMER_item_TotalCost_across_product_ProductGroups_28d customer_variability_of_product_productgroup_based_on_item_totalcost_28d =\ customer_item_totalcost_across_product_productgroups_28d.cd.entropy() # Give a name to new feature customer_variability_of_product_productgroup_based_on_item_totalcost_28d.name = \ "CUSTOMER_Variability_of_product_ProductGroup_based_on_item_TotalCost_28d"

Preview feature¶

Read on the feature primary entity concept

Read on the serving entity concept

See SDK reference for observation table

See SDK reference to preview feature

In [ ]:

#Check the primary entity of the feature'
customer_variability_of_product_productgroup_based_on_item_totalcost_28d.primary_entity

#Check the primary entity of the feature' customer_variability_of_product_productgroup_based_on_item_totalcost_28d.primary_entity

In [ ]:

#Get observation table: 'Preview Table with 10 items'
preview_table = catalog.get_observation_table(
	"Preview Table with 10 items"
)

#Get observation table: 'Preview Table with 10 items' preview_table = catalog.get_observation_table( "Preview Table with 10 items" )

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#Preview CUSTOMER_Variability_of_product_ProductGroup_based_on_item_TotalCost_28d
customer_variability_of_product_productgroup_based_on_item_totalcost_28d.preview(
	preview_table
)

#Preview CUSTOMER_Variability_of_product_ProductGroup_based_on_item_TotalCost_28d customer_variability_of_product_productgroup_based_on_item_totalcost_28d.preview( preview_table )

Save feature¶

See SDK reference to save feature

In [ ]:

# Save feature
customer_variability_of_product_productgroup_based_on_item_totalcost_28d.save()

# Save feature customer_variability_of_product_productgroup_based_on_item_totalcost_28d.save()

Add description and see feature definition file¶

See SDK reference for the definition file of a feature

In [ ]:

# Add description
customer_variability_of_product_productgroup_based_on_item_totalcost_28d.update_description(
	"The feature evaluates the distribution of a customer's item's "
	"TotalCost across various product's ProductGroup categories over a 28d "
	"period using entropy. Higher entropy signifies a more uniform "
	"distribution of item's TotalCost across categories, while lower "
	"entropy suggests a concentration within specific product's "
	"ProductGroup categories."
)
# See feature definition file
customer_variability_of_product_productgroup_based_on_item_totalcost_28d.definition

# Add description customer_variability_of_product_productgroup_based_on_item_totalcost_28d.update_description( "The feature evaluates the distribution of a customer's item's " "TotalCost across various product's ProductGroup categories over a 28d " "period using entropy. Higher entropy signifies a more uniform " "distribution of item's TotalCost across categories, while lower " "entropy suggests a concentration within specific product's " "ProductGroup categories." ) # See feature definition file customer_variability_of_product_productgroup_based_on_item_totalcost_28d.definition