CUSTOMER vs OVERALL Avg of INVOICE Count of item 28d

SDK code to create CUSTOMER_vs_OVERALL_Avg_of_INVOICE_Count_of_item_28d¶

Feature description:

Similarity between the customer and all customers measured by the Ratio of the Avg of INVOICE_Count_of_item 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

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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 GROCERYINVOICE event table.
groceryinvoice_view = catalog.get_view("GROCERYINVOICE")

# Get view from GROCERYINVOICE event table. groceryinvoice_view = catalog.get_view("GROCERYINVOICE")

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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")

Do aggregation by invoice in INVOICEITEMS¶

See SDK reference for features

See SDK reference to groupby a view

See SDK reference to do aggregation by invoice

See list of aggregation operations

See SDK reference to add an aggregation by invoice to the event view

In [ ]:

# Group invoiceitems_view by invoice entity (GroceryInvoiceGuid).
invoiceitems_view_by_invoice =\
invoiceitems_view.groupby("GroceryInvoiceGuid")

# Group invoiceitems_view by invoice entity (GroceryInvoiceGuid). invoiceitems_view_by_invoice =\ invoiceitems_view.groupby("GroceryInvoiceGuid")

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# Count the number of item for the invoice.
invoice_count_of_item =\
invoiceitems_view_by_invoice.aggregate(
    None, method=fb.AggFunc.COUNT,
    feature_name="INVOICE_Count_of_item"
)

# Count the number of item for the invoice. invoice_count_of_item =\ invoiceitems_view_by_invoice.aggregate( None, method=fb.AggFunc.COUNT, feature_name="INVOICE_Count_of_item" )

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# Add INVOICE_Count_of_item feature to the GROCERYINVOICE view as a column.
groceryinvoice_view = groceryinvoice_view.add_feature(
    "INVOICE_Count_of_item",
    invoice_count_of_item
)

# Add INVOICE_Count_of_item feature to the GROCERYINVOICE view as a column. groceryinvoice_view = groceryinvoice_view.add_feature( "INVOICE_Count_of_item", invoice_count_of_item )

Do window aggregation from GROCERYINVOICE¶

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

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# Group GROCERYINVOICE view by customer entity (GroceryCustomerGuid).
groceryinvoice_view_by_customer =\
groceryinvoice_view.groupby(['GroceryCustomerGuid'])

# Group GROCERYINVOICE view by customer entity (GroceryCustomerGuid). groceryinvoice_view_by_customer =\ groceryinvoice_view.groupby(['GroceryCustomerGuid'])

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# Get Avg of INVOICE_Count_of_item for the customer over time.
feature_group =\
groceryinvoice_view_by_customer.aggregate_over(
    "INVOICE_Count_of_item", method="avg",
    feature_names=[
        "CUSTOMER_Avg_of_INVOICE_Count_of_item"
        + "_" + w for w in windows
    ],
    windows=windows
)
# Get CUSTOMER_Avg_of_INVOICE_Count_of_item_28d object from feature group.
customer_avg_of_invoice_count_of_item_28d =\
feature_group["CUSTOMER_Avg_of_INVOICE_Count_of_item_28d"]

# Get Avg of INVOICE_Count_of_item for the customer over time. feature_group =\ groceryinvoice_view_by_customer.aggregate_over( "INVOICE_Count_of_item", method="avg", feature_names=[ "CUSTOMER_Avg_of_INVOICE_Count_of_item" + "_" + w for w in windows ], windows=windows ) # Get CUSTOMER_Avg_of_INVOICE_Count_of_item_28d object from feature group. customer_avg_of_invoice_count_of_item_28d =\ feature_group["CUSTOMER_Avg_of_INVOICE_Count_of_item_28d"]

In [ ]:

# Group GROCERYINVOICE view without any groupby key for aggregates on all data.
groceryinvoice_view_by_overall =\
groceryinvoice_view.groupby([])

# Group GROCERYINVOICE view without any groupby key for aggregates on all data. groceryinvoice_view_by_overall =\ groceryinvoice_view.groupby([])

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# Get Avg of INVOICE_Count_of_item over time.
feature_group =\
groceryinvoice_view_by_overall.aggregate_over(
    "INVOICE_Count_of_item", method="avg",
    feature_names=[
        "OVERALL_Avg_of_INVOICE_Count_of_item"
        + "_" + w for w in windows
    ],
    windows=windows
)
# Get OVERALL_Avg_of_INVOICE_Count_of_item_28d object from feature group.
overall_avg_of_invoice_count_of_item_28d =\
feature_group["OVERALL_Avg_of_INVOICE_Count_of_item_28d"]

# Get Avg of INVOICE_Count_of_item over time. feature_group =\ groceryinvoice_view_by_overall.aggregate_over( "INVOICE_Count_of_item", method="avg", feature_names=[ "OVERALL_Avg_of_INVOICE_Count_of_item" + "_" + w for w in windows ], windows=windows ) # Get OVERALL_Avg_of_INVOICE_Count_of_item_28d object from feature group. overall_avg_of_invoice_count_of_item_28d =\ feature_group["OVERALL_Avg_of_INVOICE_Count_of_item_28d"]

Derive Similarity feature across entities¶

See list of feature transforms

In [ ]:

# Derive Similarity feature from Ratio of
# CUSTOMER_Avg_of_INVOICE_Count_of_item_28d
# to OVERALL_Avg_of_INVOICE_Count_of_item_28d
customer_vs_overall_avg_of_invoice_count_of_item_28d = (
    customer_avg_of_invoice_count_of_item_28d
    / overall_avg_of_invoice_count_of_item_28d
)
# Give a name to new feature
customer_vs_overall_avg_of_invoice_count_of_item_28d.name = \
"CUSTOMER_vs_OVERALL_Avg_of_INVOICE_Count_of_item_28d"

# Derive Similarity feature from Ratio of # CUSTOMER_Avg_of_INVOICE_Count_of_item_28d # to OVERALL_Avg_of_INVOICE_Count_of_item_28d customer_vs_overall_avg_of_invoice_count_of_item_28d = ( customer_avg_of_invoice_count_of_item_28d / overall_avg_of_invoice_count_of_item_28d ) # Give a name to new feature customer_vs_overall_avg_of_invoice_count_of_item_28d.name = \ "CUSTOMER_vs_OVERALL_Avg_of_INVOICE_Count_of_item_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_avg_of_invoice_count_of_item_28d.primary_entity

#Check the primary entity of the feature' customer_vs_overall_avg_of_invoice_count_of_item_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_Avg_of_INVOICE_Count_of_item_28d
customer_vs_overall_avg_of_invoice_count_of_item_28d.preview(
	preview_table
)

#Preview CUSTOMER_vs_OVERALL_Avg_of_INVOICE_Count_of_item_28d customer_vs_overall_avg_of_invoice_count_of_item_28d.preview( preview_table )

Save feature¶

See SDK reference to save feature

In [ ]:

# Save feature
customer_vs_overall_avg_of_invoice_count_of_item_28d.save()

# Save feature customer_vs_overall_avg_of_invoice_count_of_item_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_avg_of_invoice_count_of_item_28d.update_description(
	"Similarity between the customer and all customers measured by the "
	"Ratio of the Avg of INVOICE_Count_of_item over 28d for both entities."
)
# See feature definition file
customer_vs_overall_avg_of_invoice_count_of_item_28d.definition

# Add description customer_vs_overall_avg_of_invoice_count_of_item_28d.update_description( "Similarity between the customer and all customers measured by the " "Ratio of the Avg of INVOICE_Count_of_item over 28d for both entities." ) # See feature definition file customer_vs_overall_avg_of_invoice_count_of_item_28d.definition