CUSTOMER item TotalCost across product ProductGroups 14d

SDK code to create CUSTOMER_item_TotalCost_across_product_ProductGroups_14d¶

Feature description:

Distribution representing the cumulative TotalCost of item, categorized by their respective product's ProductGroup, for the customer over a 14d period. The result is presented as a dictionary where the ProductGroup serves as the key and its corresponding sum of TotalCost forms the value.

In [ ]:

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

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

Activate catalog¶

See SDK reference for catalogs

In [ ]:

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

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

Set windows for aggregation¶

In [ ]:

windows = ['14d']

windows = ['14d']

Get view from table¶

See SDK reference for views

In [ ]:

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

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

In [ ]:

# 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_14d object from feature group.
customer_item_totalcost_across_product_productgroups_14d =\
feature_group["CUSTOMER_item_TotalCost_across_product_ProductGroups_14d"]

# 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_14d object from feature group. customer_item_totalcost_across_product_productgroups_14d =\ feature_group["CUSTOMER_item_TotalCost_across_product_ProductGroups_14d"]

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_item_totalcost_across_product_productgroups_14d.primary_entity

#Check the primary entity of the feature' customer_item_totalcost_across_product_productgroups_14d.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" )

In [ ]:

#Preview CUSTOMER_item_TotalCost_across_product_ProductGroups_14d
customer_item_totalcost_across_product_productgroups_14d.preview(
	preview_table
)

#Preview CUSTOMER_item_TotalCost_across_product_ProductGroups_14d customer_item_totalcost_across_product_productgroups_14d.preview( preview_table )

Save feature¶

See SDK reference to save feature

In [ ]:

# Save feature
customer_item_totalcost_across_product_productgroups_14d.save()

# Save feature customer_item_totalcost_across_product_productgroups_14d.save()

Add description and see feature definition file¶

See SDK reference for the definition file of a feature

In [ ]:

# Add description
customer_item_totalcost_across_product_productgroups_14d.update_description(
	"Distribution representing the cumulative TotalCost of item, "
	"categorized by their respective product's ProductGroup, for the "
	"customer over a 14d period. The result is presented as a dictionary "
	"where the ProductGroup serves as the key and its corresponding sum of "
	"TotalCost forms the value."
)
# See feature definition file
customer_item_totalcost_across_product_productgroups_14d.definition

# Add description customer_item_totalcost_across_product_productgroups_14d.update_description( "Distribution representing the cumulative TotalCost of item, " "categorized by their respective product's ProductGroup, for the " "customer over a 14d period. The result is presented as a dictionary " "where the ProductGroup serves as the key and its corresponding sum of " "TotalCost forms the value." ) # See feature definition file customer_item_totalcost_across_product_productgroups_14d.definition