CUSTOMER vs OVERALL Avg of item Discount 28d
SDK code to create CUSTOMER_vs_OVERALL_Avg_of_item_Discount_28d¶
Feature description:
Similarity between the customer and all customers measured by the Ratio of the Avg of item Discount over 28d for both entities.
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import featurebyte as fb
fb.use_profile("tutorial")
import featurebyte as fb
fb.use_profile("tutorial")
Activate catalog¶
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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¶
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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 window aggregation from INVOICEITEMS¶
See SDK reference for features
See SDK reference to groupby a view
See SDK reference to do aggregation over time
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# Group INVOICEITEMS view by customer entity (GroceryCustomerGuid).
invoiceitems_view_by_customer =\
invoiceitems_view.groupby(['GroceryCustomerGuid'])
# Group INVOICEITEMS view by customer entity (GroceryCustomerGuid).
invoiceitems_view_by_customer =\
invoiceitems_view.groupby(['GroceryCustomerGuid'])
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# Get Avg of Discount for the customer over time.
feature_group =\
invoiceitems_view_by_customer.aggregate_over(
"Discount", method="avg",
feature_names=[
"CUSTOMER_Avg_of_item_Discount"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Avg_of_item_Discount_28d object from feature group.
customer_avg_of_item_discount_28d =\
feature_group["CUSTOMER_Avg_of_item_Discount_28d"]
# Get Avg of Discount for the customer over time.
feature_group =\
invoiceitems_view_by_customer.aggregate_over(
"Discount", method="avg",
feature_names=[
"CUSTOMER_Avg_of_item_Discount"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Avg_of_item_Discount_28d object from feature group.
customer_avg_of_item_discount_28d =\
feature_group["CUSTOMER_Avg_of_item_Discount_28d"]
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# Group INVOICEITEMS view without any groupby key for aggregates on all data.
invoiceitems_view_by_overall =\
invoiceitems_view.groupby([])
# Group INVOICEITEMS view without any groupby key for aggregates on all data.
invoiceitems_view_by_overall =\
invoiceitems_view.groupby([])
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# Get Avg of Discount over time.
feature_group =\
invoiceitems_view_by_overall.aggregate_over(
"Discount", method="avg",
feature_names=[
"OVERALL_Avg_of_item_Discount"
+ "_" + w for w in windows
],
windows=windows
)
# Get OVERALL_Avg_of_item_Discount_28d object from feature group.
overall_avg_of_item_discount_28d =\
feature_group["OVERALL_Avg_of_item_Discount_28d"]
# Get Avg of Discount over time.
feature_group =\
invoiceitems_view_by_overall.aggregate_over(
"Discount", method="avg",
feature_names=[
"OVERALL_Avg_of_item_Discount"
+ "_" + w for w in windows
],
windows=windows
)
# Get OVERALL_Avg_of_item_Discount_28d object from feature group.
overall_avg_of_item_discount_28d =\
feature_group["OVERALL_Avg_of_item_Discount_28d"]
Derive Similarity feature across entities¶
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# Derive Similarity feature from Ratio of
# CUSTOMER_Avg_of_item_Discount_28d
# to OVERALL_Avg_of_item_Discount_28d
customer_vs_overall_avg_of_item_discount_28d = (
customer_avg_of_item_discount_28d
/ overall_avg_of_item_discount_28d
)
# Give a name to new feature
customer_vs_overall_avg_of_item_discount_28d.name = \
"CUSTOMER_vs_OVERALL_Avg_of_item_Discount_28d"
# Derive Similarity feature from Ratio of
# CUSTOMER_Avg_of_item_Discount_28d
# to OVERALL_Avg_of_item_Discount_28d
customer_vs_overall_avg_of_item_discount_28d = (
customer_avg_of_item_discount_28d
/ overall_avg_of_item_discount_28d
)
# Give a name to new feature
customer_vs_overall_avg_of_item_discount_28d.name = \
"CUSTOMER_vs_OVERALL_Avg_of_item_Discount_28d"
Preview feature¶
Read on the feature primary entity concept
Read on the serving entity concept
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#Check the primary entity of the feature'
customer_vs_overall_avg_of_item_discount_28d.primary_entity
#Check the primary entity of the feature'
customer_vs_overall_avg_of_item_discount_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_item_Discount_28d
customer_vs_overall_avg_of_item_discount_28d.preview(
preview_table
)
#Preview CUSTOMER_vs_OVERALL_Avg_of_item_Discount_28d
customer_vs_overall_avg_of_item_discount_28d.preview(
preview_table
)
Save feature¶
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# Save feature
customer_vs_overall_avg_of_item_discount_28d.save()
# Save feature
customer_vs_overall_avg_of_item_discount_28d.save()
Add description and see feature definition file¶
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# Add description
customer_vs_overall_avg_of_item_discount_28d.update_description(
"Similarity between the customer and all customers measured by the "
"Ratio of the Avg of item Discount over 28d for both entities."
)
# See feature definition file
customer_vs_overall_avg_of_item_discount_28d.definition
# Add description
customer_vs_overall_avg_of_item_discount_28d.update_description(
"Similarity between the customer and all customers measured by the "
"Ratio of the Avg of item Discount over 28d for both entities."
)
# See feature definition file
customer_vs_overall_avg_of_item_discount_28d.definition