ITEM UnitPrice Z Score to CUSTOMER item UnitPrice 14d
SDK code to create ITEM_UnitPrice_Z_Score_to_CUSTOMER_item_UnitPrice_14d¶
Feature description:
Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all items with the same customer as that item over a 14d period.
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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 = ['14d']
windows = ['14d']
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")
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# Create lookup feature from UnitPrice column for item entity.
item_unitprice =\
invoiceitems_view["UnitPrice"].as_feature("ITEM_UnitPrice")
# Create lookup feature from UnitPrice column for item entity.
item_unitprice =\
invoiceitems_view["UnitPrice"].as_feature("ITEM_UnitPrice")
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 UnitPrice for the customer over time.
feature_group =\
invoiceitems_view_by_customer.aggregate_over(
"UnitPrice", method="avg",
feature_names=[
"CUSTOMER_Avg_of_item_UnitPrice"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Avg_of_item_UnitPrice_14d object from feature group.
customer_avg_of_item_unitprice_14d =\
feature_group["CUSTOMER_Avg_of_item_UnitPrice_14d"]
# Get Avg of UnitPrice for the customer over time.
feature_group =\
invoiceitems_view_by_customer.aggregate_over(
"UnitPrice", method="avg",
feature_names=[
"CUSTOMER_Avg_of_item_UnitPrice"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Avg_of_item_UnitPrice_14d object from feature group.
customer_avg_of_item_unitprice_14d =\
feature_group["CUSTOMER_Avg_of_item_UnitPrice_14d"]
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# Get Std of UnitPrice for the customer over time.
feature_group =\
invoiceitems_view_by_customer.aggregate_over(
"UnitPrice", method="std",
feature_names=[
"CUSTOMER_Std_of_item_UnitPrice"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Std_of_item_UnitPrice_14d object from feature group.
customer_std_of_item_unitprice_14d =\
feature_group["CUSTOMER_Std_of_item_UnitPrice_14d"]
# Get Std of UnitPrice for the customer over time.
feature_group =\
invoiceitems_view_by_customer.aggregate_over(
"UnitPrice", method="std",
feature_names=[
"CUSTOMER_Std_of_item_UnitPrice"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Std_of_item_UnitPrice_14d object from feature group.
customer_std_of_item_unitprice_14d =\
feature_group["CUSTOMER_Std_of_item_UnitPrice_14d"]
Compare lookup with aggregation¶
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# Get the Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all
# items with the same customer as that item over a 14d period.
item_unitprice_z_score_to_customer_item_unitprice_14d = (
item_unitprice
- customer_avg_of_item_unitprice_14d
) / customer_std_of_item_unitprice_14d
# Give a name to new feature
item_unitprice_z_score_to_customer_item_unitprice_14d.name = \
"ITEM_UnitPrice_Z_Score_to_CUSTOMER_item_UnitPrice_14d"
# Get the Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all
# items with the same customer as that item over a 14d period.
item_unitprice_z_score_to_customer_item_unitprice_14d = (
item_unitprice
- customer_avg_of_item_unitprice_14d
) / customer_std_of_item_unitprice_14d
# Give a name to new feature
item_unitprice_z_score_to_customer_item_unitprice_14d.name = \
"ITEM_UnitPrice_Z_Score_to_CUSTOMER_item_UnitPrice_14d"
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'
item_unitprice_z_score_to_customer_item_unitprice_14d.primary_entity
#Check the primary entity of the feature'
item_unitprice_z_score_to_customer_item_unitprice_14d.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 ITEM_UnitPrice_Z_Score_to_CUSTOMER_item_UnitPrice_14d
item_unitprice_z_score_to_customer_item_unitprice_14d.preview(
preview_table
)
#Preview ITEM_UnitPrice_Z_Score_to_CUSTOMER_item_UnitPrice_14d
item_unitprice_z_score_to_customer_item_unitprice_14d.preview(
preview_table
)
Save feature¶
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# Save feature
item_unitprice_z_score_to_customer_item_unitprice_14d.save()
# Save feature
item_unitprice_z_score_to_customer_item_unitprice_14d.save()
Add description and see feature definition file¶
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# Add description
item_unitprice_z_score_to_customer_item_unitprice_14d.update_description(
"Z-Score of the item UnitPrice in relation to the distribution of item "
"UnitPrice among all items with the same customer as that item over a "
"14d period."
)
# See feature definition file
item_unitprice_z_score_to_customer_item_unitprice_14d.definition
# Add description
item_unitprice_z_score_to_customer_item_unitprice_14d.update_description(
"Z-Score of the item UnitPrice in relation to the distribution of item "
"UnitPrice among all items with the same customer as that item over a "
"14d period."
)
# See feature definition file
item_unitprice_z_score_to_customer_item_unitprice_14d.definition