CUSTOMER invoice Amount across invoice Weekdays 14d

SDK code to create CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d¶

Feature description:

Distribution representing the cumulative Amount of invoice, categorized by their respective invoice's Weekday, for the customer over a 14d period. The result is presented as a dictionary where the Weekday of invoice serves as the key and its corresponding sum of Amount forms the value.

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 = ['14d']

windows = ['14d']

Get view from table¶

See SDK reference for views

In [ ]:

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

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

Extract Date parts¶

See SDK reference for view columns

See list of datetime transforms

In [ ]:

# 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

See SDK reference for feature group

See list of aggregation operations

In [ ]:

# 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" )

In [ ]:

# Distribution representing the cumulative Amount of invoice, categorized by their respective
# invoice's Weekday, for the customer over time.
feature_group =\
groceryinvoice_view_by_customer_across_weekday_of_invoice.aggregate_over(
    "Amount", method=fb.AggFunc.SUM,
    feature_names=[
        "CUSTOMER_invoice_Amount_across_invoice_Weekdays"
        + "_" + w for w in windows
    ],
    windows=windows
)
# Get CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d object from feature group.
customer_invoice_amount_across_invoice_weekdays_14d =\
feature_group["CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d"]

# Distribution representing the cumulative Amount of invoice, categorized by their respective # invoice's Weekday, for the customer over time. feature_group =\ groceryinvoice_view_by_customer_across_weekday_of_invoice.aggregate_over( "Amount", method=fb.AggFunc.SUM, feature_names=[ "CUSTOMER_invoice_Amount_across_invoice_Weekdays" + "_" + w for w in windows ], windows=windows ) # Get CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d object from feature group. customer_invoice_amount_across_invoice_weekdays_14d =\ feature_group["CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d"]

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_invoice_amount_across_invoice_weekdays_14d.primary_entity

#Check the primary entity of the feature' customer_invoice_amount_across_invoice_weekdays_14d.primary_entity

In [ ]:

#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()

In [ ]:

#Preview CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d
customer_invoice_amount_across_invoice_weekdays_14d.preview(
	preview_table
)

#Preview CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d customer_invoice_amount_across_invoice_weekdays_14d.preview( preview_table )

Save feature¶

See SDK reference to save feature

In [ ]:

# Save feature
customer_invoice_amount_across_invoice_weekdays_14d.save()

# Save feature customer_invoice_amount_across_invoice_weekdays_14d.save()

Add description and see feature definition file¶

See SDK reference for the definition file of a feature

In [ ]:

# Add description
customer_invoice_amount_across_invoice_weekdays_14d.update_description(
	"Distribution representing the cumulative Amount of invoice, "
	"categorized by their respective invoice's Weekday, for the customer "
	"over a 14d period. The result is presented as a dictionary where the "
	"Weekday of invoice serves as the key and its corresponding sum of "
	"Amount forms the value."
)
# See feature definition file
customer_invoice_amount_across_invoice_weekdays_14d.definition

# Add description customer_invoice_amount_across_invoice_weekdays_14d.update_description( "Distribution representing the cumulative Amount of invoice, " "categorized by their respective invoice's Weekday, for the customer " "over a 14d period. The result is presented as a dictionary where the " "Weekday of invoice serves as the key and its corresponding sum of " "Amount forms the value." ) # See feature definition file customer_invoice_amount_across_invoice_weekdays_14d.definition