INVOICE Amount Z Score to OVERALL invoice Amount 14d
SDK code to create INVOICE_Amount_Z_Score_to_OVERALL_invoice_Amount_14d¶
Feature description:
Z-Score of the invoice Amount in relation to the distribution of invoice Amount among all invoices 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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# Create lookup feature from Amount column for invoice entity.
invoice_amount =\
groceryinvoice_view["Amount"].as_feature("INVOICE_Amount")
# Create lookup feature from Amount column for invoice entity.
invoice_amount =\
groceryinvoice_view["Amount"].as_feature("INVOICE_Amount")
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 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 Amount over time.
feature_group =\
groceryinvoice_view_by_overall.aggregate_over(
"Amount", method="avg",
feature_names=[
"OVERALL_Avg_of_invoice_Amount"
+ "_" + w for w in windows
],
windows=windows
)
# Get OVERALL_Avg_of_invoice_Amount_14d object from feature group.
overall_avg_of_invoice_amount_14d =\
feature_group["OVERALL_Avg_of_invoice_Amount_14d"]
# Get Avg of Amount over time.
feature_group =\
groceryinvoice_view_by_overall.aggregate_over(
"Amount", method="avg",
feature_names=[
"OVERALL_Avg_of_invoice_Amount"
+ "_" + w for w in windows
],
windows=windows
)
# Get OVERALL_Avg_of_invoice_Amount_14d object from feature group.
overall_avg_of_invoice_amount_14d =\
feature_group["OVERALL_Avg_of_invoice_Amount_14d"]
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# Get Std of Amount over time.
feature_group =\
groceryinvoice_view_by_overall.aggregate_over(
"Amount", method="std",
feature_names=[
"OVERALL_Std_of_invoice_Amount"
+ "_" + w for w in windows
],
windows=windows
)
# Get OVERALL_Std_of_invoice_Amount_14d object from feature group.
overall_std_of_invoice_amount_14d =\
feature_group["OVERALL_Std_of_invoice_Amount_14d"]
# Get Std of Amount over time.
feature_group =\
groceryinvoice_view_by_overall.aggregate_over(
"Amount", method="std",
feature_names=[
"OVERALL_Std_of_invoice_Amount"
+ "_" + w for w in windows
],
windows=windows
)
# Get OVERALL_Std_of_invoice_Amount_14d object from feature group.
overall_std_of_invoice_amount_14d =\
feature_group["OVERALL_Std_of_invoice_Amount_14d"]
Compare lookup with aggregation¶
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# Get the Z-Score of the invoice Amount in relation to the distribution of invoice Amount among all
# invoices over a 14d period.
invoice_amount_z_score_to_overall_invoice_amount_14d = (
invoice_amount
- overall_avg_of_invoice_amount_14d
) / overall_std_of_invoice_amount_14d
# Give a name to new feature
invoice_amount_z_score_to_overall_invoice_amount_14d.name = \
"INVOICE_Amount_Z_Score_to_OVERALL_invoice_Amount_14d"
# Get the Z-Score of the invoice Amount in relation to the distribution of invoice Amount among all
# invoices over a 14d period.
invoice_amount_z_score_to_overall_invoice_amount_14d = (
invoice_amount
- overall_avg_of_invoice_amount_14d
) / overall_std_of_invoice_amount_14d
# Give a name to new feature
invoice_amount_z_score_to_overall_invoice_amount_14d.name = \
"INVOICE_Amount_Z_Score_to_OVERALL_invoice_Amount_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'
invoice_amount_z_score_to_overall_invoice_amount_14d.primary_entity
#Check the primary entity of the feature'
invoice_amount_z_score_to_overall_invoice_amount_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 INVOICE_Amount_Z_Score_to_OVERALL_invoice_Amount_14d
invoice_amount_z_score_to_overall_invoice_amount_14d.preview(
preview_table
)
#Preview INVOICE_Amount_Z_Score_to_OVERALL_invoice_Amount_14d
invoice_amount_z_score_to_overall_invoice_amount_14d.preview(
preview_table
)
Save feature¶
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# Save feature
invoice_amount_z_score_to_overall_invoice_amount_14d.save()
# Save feature
invoice_amount_z_score_to_overall_invoice_amount_14d.save()
Add description and see feature definition file¶
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# Add description
invoice_amount_z_score_to_overall_invoice_amount_14d.update_description(
"Z-Score of the invoice Amount in relation to the distribution of "
"invoice Amount among all invoices over a 14d period."
)
# See feature definition file
invoice_amount_z_score_to_overall_invoice_amount_14d.definition
# Add description
invoice_amount_z_score_to_overall_invoice_amount_14d.update_description(
"Z-Score of the invoice Amount in relation to the distribution of "
"invoice Amount among all invoices over a 14d period."
)
# See feature definition file
invoice_amount_z_score_to_overall_invoice_amount_14d.definition