CUSTOMER Unique Count of invoice Weekday 14d
SDK code to create CUSTOMER_Unique_Count_of_invoice_Weekday_14d¶
Feature description:
Unique Count of invoice Weekday for the customer 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 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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# Extract day_of_week date part from Timestamp column for GROCERYINVOICE view.
groceryinvoice_view["Weekday of invoice"] = groceryinvoice_view["Timestamp"].dt.day_of_week
# Extract day_of_week date part from Timestamp column for GROCERYINVOICE view.
groceryinvoice_view["Weekday of invoice"] = groceryinvoice_view["Timestamp"].dt.day_of_week
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
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# Group GROCERYINVOICE view by customer entity (GroceryCustomerGuid) across different Weekday of
# invoices.
groceryinvoice_view_by_customer_across_weekday_of_invoice =\
groceryinvoice_view.groupby(
['GroceryCustomerGuid'], category="Weekday of invoice"
)
# Group GROCERYINVOICE view by customer entity (GroceryCustomerGuid) across different Weekday of
# invoices.
groceryinvoice_view_by_customer_across_weekday_of_invoice =\
groceryinvoice_view.groupby(
['GroceryCustomerGuid'], category="Weekday of invoice"
)
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# Count invoice across different Weekday of invoices for the customer over time.
feature_group =\
groceryinvoice_view_by_customer_across_weekday_of_invoice.aggregate_over(
None, method=fb.AggFunc.COUNT,
feature_names=[
"CUSTOMER_Count_of_invoice_across_invoice_Weekdays"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Count_of_invoice_across_invoice_Weekdays_14d object from feature group.
customer_count_of_invoice_across_invoice_weekdays_14d =\
feature_group["CUSTOMER_Count_of_invoice_across_invoice_Weekdays_14d"]
# Count invoice across different Weekday of invoices for the customer over time.
feature_group =\
groceryinvoice_view_by_customer_across_weekday_of_invoice.aggregate_over(
None, method=fb.AggFunc.COUNT,
feature_names=[
"CUSTOMER_Count_of_invoice_across_invoice_Weekdays"
+ "_" + w for w in windows
],
windows=windows
)
# Get CUSTOMER_Count_of_invoice_across_invoice_Weekdays_14d object from feature group.
customer_count_of_invoice_across_invoice_weekdays_14d =\
feature_group["CUSTOMER_Count_of_invoice_across_invoice_Weekdays_14d"]
Derive feature from aggregation across categories¶
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# Get Unique Count of invoice Weekday from
# CUSTOMER_Count_of_invoice_across_invoice_Weekdays_14d
customer_unique_count_of_invoice_weekday_14d =\
customer_count_of_invoice_across_invoice_weekdays_14d.cd.unique_count()
# Give a name to new feature
customer_unique_count_of_invoice_weekday_14d.name = \
"CUSTOMER_Unique_Count_of_invoice_Weekday_14d"
# Get Unique Count of invoice Weekday from
# CUSTOMER_Count_of_invoice_across_invoice_Weekdays_14d
customer_unique_count_of_invoice_weekday_14d =\
customer_count_of_invoice_across_invoice_weekdays_14d.cd.unique_count()
# Give a name to new feature
customer_unique_count_of_invoice_weekday_14d.name = \
"CUSTOMER_Unique_Count_of_invoice_Weekday_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'
customer_unique_count_of_invoice_weekday_14d.primary_entity
#Check the primary entity of the feature'
customer_unique_count_of_invoice_weekday_14d.primary_entity
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#Get observation table: 'Preview Table with 10 Customers'
preview_table = catalog.get_observation_table(
"Preview Table with 10 Customers"
).to_pandas()
#Get observation table: 'Preview Table with 10 Customers'
preview_table = catalog.get_observation_table(
"Preview Table with 10 Customers"
).to_pandas()
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#Preview CUSTOMER_Unique_Count_of_invoice_Weekday_14d
customer_unique_count_of_invoice_weekday_14d.preview(
preview_table
)
#Preview CUSTOMER_Unique_Count_of_invoice_Weekday_14d
customer_unique_count_of_invoice_weekday_14d.preview(
preview_table
)
Save feature¶
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# Save feature
customer_unique_count_of_invoice_weekday_14d.save()
# Save feature
customer_unique_count_of_invoice_weekday_14d.save()
Add description and see feature definition file¶
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# Add description
customer_unique_count_of_invoice_weekday_14d.update_description(
"Unique Count of invoice Weekday for the customer over a 14d period."
)
# See feature definition file
customer_unique_count_of_invoice_weekday_14d.definition
# Add description
customer_unique_count_of_invoice_weekday_14d.update_description(
"Unique Count of invoice Weekday for the customer over a 14d period."
)
# See feature definition file
customer_unique_count_of_invoice_weekday_14d.definition