CUSTOMER vs OVERALL item TotalCost across product ProductGroups 28d

SDK code to create CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_28d¶

Feature description:

Similarity between the customer and all customers measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective product's ProductGroup, over 28d for both entities.

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 = ['28d']

windows = ['28d']

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")

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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" )

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# 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"]

In [ ]:

# Group INVOICEITEMS view across different ProductGroups.
invoiceitems_view_by_overall_across_productgroup =\
invoiceitems_view.groupby(
    [], category="ProductGroup"
)

# Group INVOICEITEMS view across different ProductGroups. invoiceitems_view_by_overall_across_productgroup =\ invoiceitems_view.groupby( [], category="ProductGroup" )

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# Distribution representing the cumulative TotalCost of item, categorized by their respective
# product's ProductGroup, over time.
feature_group =\
invoiceitems_view_by_overall_across_productgroup.aggregate_over(
    "TotalCost", method=fb.AggFunc.SUM,
    feature_names=[
        "OVERALL_item_TotalCost_across_product_ProductGroups"
        + "_" + w for w in windows
    ],
    windows=windows
)
# Get OVERALL_item_TotalCost_across_product_ProductGroups_28d object from feature group.
overall_item_totalcost_across_product_productgroups_28d =\
feature_group["OVERALL_item_TotalCost_across_product_ProductGroups_28d"]

# Distribution representing the cumulative TotalCost of item, categorized by their respective # product's ProductGroup, over time. feature_group =\ invoiceitems_view_by_overall_across_productgroup.aggregate_over( "TotalCost", method=fb.AggFunc.SUM, feature_names=[ "OVERALL_item_TotalCost_across_product_ProductGroups" + "_" + w for w in windows ], windows=windows ) # Get OVERALL_item_TotalCost_across_product_ProductGroups_28d object from feature group. overall_item_totalcost_across_product_productgroups_28d =\ feature_group["OVERALL_item_TotalCost_across_product_ProductGroups_28d"]

Derive Similarity feature across entities¶

See list of feature transforms

In [ ]:

# Derive Similarity feature from cosine similarity between
# CUSTOMER_item_TotalCost_across_product_ProductGroups_28d
# and OVERALL_item_TotalCost_across_product_ProductGroups_28d
customer_vs_overall_item_totalcost_across_product_productgroups_28d =\
customer_item_totalcost_across_product_productgroups_28d.cd.cosine_similarity(
        overall_item_totalcost_across_product_productgroups_28d
    )
# Give a name to new feature
customer_vs_overall_item_totalcost_across_product_productgroups_28d.name = \
"CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_28d"

# Derive Similarity feature from cosine similarity between # CUSTOMER_item_TotalCost_across_product_ProductGroups_28d # and OVERALL_item_TotalCost_across_product_ProductGroups_28d customer_vs_overall_item_totalcost_across_product_productgroups_28d =\ customer_item_totalcost_across_product_productgroups_28d.cd.cosine_similarity( overall_item_totalcost_across_product_productgroups_28d ) # Give a name to new feature customer_vs_overall_item_totalcost_across_product_productgroups_28d.name = \ "CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_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_vs_overall_item_totalcost_across_product_productgroups_28d.primary_entity

#Check the primary entity of the feature' customer_vs_overall_item_totalcost_across_product_productgroups_28d.primary_entity

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#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_vs_OVERALL_item_TotalCost_across_product_ProductGroups_28d
customer_vs_overall_item_totalcost_across_product_productgroups_28d.preview(
	preview_table
)

#Preview CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_28d customer_vs_overall_item_totalcost_across_product_productgroups_28d.preview( preview_table )

Save feature¶

See SDK reference to save feature

In [ ]:

# Save feature
customer_vs_overall_item_totalcost_across_product_productgroups_28d.save()

# Save feature customer_vs_overall_item_totalcost_across_product_productgroups_28d.save()

Add description and see feature definition file¶

See SDK reference for the definition file of a feature

In [ ]:

# Add description
customer_vs_overall_item_totalcost_across_product_productgroups_28d.update_description(
	"Similarity between the customer and all customers measured by the "
	"Cosine Similarity between the Distribution representing the cumulative"
	" TotalCost of item, categorized by their respective product's "
	"ProductGroup, over 28d for both entities."
)
# See feature definition file
customer_vs_overall_item_totalcost_across_product_productgroups_28d.definition

# Add description customer_vs_overall_item_totalcost_across_product_productgroups_28d.update_description( "Similarity between the customer and all customers measured by the " "Cosine Similarity between the Distribution representing the cumulative" " TotalCost of item, categorized by their respective product's " "ProductGroup, over 28d for both entities." ) # See feature definition file customer_vs_overall_item_totalcost_across_product_productgroups_28d.definition