ITEM Quantity Z Score to OVERALL item Quantity 14d

SDK code to create ITEM_Quantity_Z_Score_to_OVERALL_item_Quantity_14d¶

Feature description:

Z-Score of the item Quantity in relation to the distribution of item Quantity among all items over a 14d period.

In [ ]:

import featurebyte as fb
fb.use_profile("tutorial")

import featurebyte as fb fb.use_profile("tutorial")

Activate catalog¶

See SDK reference for catalogs

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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¶

See SDK reference for views

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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")

Create Lookup feature¶

See SDK reference for features

See SDK reference to declare a lookup feature

In [ ]:

# Create lookup feature from Quantity column for item entity.
item_quantity =\
invoiceitems_view["Quantity"].as_feature("ITEM_Quantity")

# Create lookup feature from Quantity column for item entity. item_quantity =\ invoiceitems_view["Quantity"].as_feature("ITEM_Quantity")

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

See SDK reference for feature group

See list of aggregation operations

In [ ]:

# 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 Quantity over time.
feature_group =\
invoiceitems_view_by_overall.aggregate_over(
    "Quantity", method="avg",
    feature_names=[
        "OVERALL_Avg_of_item_Quantity"
        + "_" + w for w in windows
    ],
    windows=windows
)
# Get OVERALL_Avg_of_item_Quantity_14d object from feature group.
overall_avg_of_item_quantity_14d =\
feature_group["OVERALL_Avg_of_item_Quantity_14d"]

# Get Avg of Quantity over time. feature_group =\ invoiceitems_view_by_overall.aggregate_over( "Quantity", method="avg", feature_names=[ "OVERALL_Avg_of_item_Quantity" + "_" + w for w in windows ], windows=windows ) # Get OVERALL_Avg_of_item_Quantity_14d object from feature group. overall_avg_of_item_quantity_14d =\ feature_group["OVERALL_Avg_of_item_Quantity_14d"]

In [ ]:

# Get Std of Quantity over time.
feature_group =\
invoiceitems_view_by_overall.aggregate_over(
    "Quantity", method="std",
    feature_names=[
        "OVERALL_Std_of_item_Quantity"
        + "_" + w for w in windows
    ],
    windows=windows
)
# Get OVERALL_Std_of_item_Quantity_14d object from feature group.
overall_std_of_item_quantity_14d =\
feature_group["OVERALL_Std_of_item_Quantity_14d"]

# Get Std of Quantity over time. feature_group =\ invoiceitems_view_by_overall.aggregate_over( "Quantity", method="std", feature_names=[ "OVERALL_Std_of_item_Quantity" + "_" + w for w in windows ], windows=windows ) # Get OVERALL_Std_of_item_Quantity_14d object from feature group. overall_std_of_item_quantity_14d =\ feature_group["OVERALL_Std_of_item_Quantity_14d"]

Compare lookup with aggregation¶

See list of feature transforms

In [ ]:

# Get the Z-Score of the item Quantity in relation to the distribution of item Quantity among all
# items over a 14d period.
item_quantity_z_score_to_overall_item_quantity_14d = (
    item_quantity
    - overall_avg_of_item_quantity_14d
) / overall_std_of_item_quantity_14d
# Give a name to new feature
item_quantity_z_score_to_overall_item_quantity_14d.name = \
"ITEM_Quantity_Z_Score_to_OVERALL_item_Quantity_14d"

# Get the Z-Score of the item Quantity in relation to the distribution of item Quantity among all # items over a 14d period. item_quantity_z_score_to_overall_item_quantity_14d = ( item_quantity - overall_avg_of_item_quantity_14d ) / overall_std_of_item_quantity_14d # Give a name to new feature item_quantity_z_score_to_overall_item_quantity_14d.name = \ "ITEM_Quantity_Z_Score_to_OVERALL_item_Quantity_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'
item_quantity_z_score_to_overall_item_quantity_14d.primary_entity

#Check the primary entity of the feature' item_quantity_z_score_to_overall_item_quantity_14d.primary_entity

In [ ]:

#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_Quantity_Z_Score_to_OVERALL_item_Quantity_14d
item_quantity_z_score_to_overall_item_quantity_14d.preview(
	preview_table
)

#Preview ITEM_Quantity_Z_Score_to_OVERALL_item_Quantity_14d item_quantity_z_score_to_overall_item_quantity_14d.preview( preview_table )

Save feature¶

See SDK reference to save feature

In [ ]:

# Save feature
item_quantity_z_score_to_overall_item_quantity_14d.save()

# Save feature item_quantity_z_score_to_overall_item_quantity_14d.save()

Add description and see feature definition file¶

See SDK reference for the definition file of a feature

In [ ]:

# Add description
item_quantity_z_score_to_overall_item_quantity_14d.update_description(
	"Z-Score of the item Quantity in relation to the distribution of item "
	"Quantity among all items over a 14d period."
)
# See feature definition file
item_quantity_z_score_to_overall_item_quantity_14d.definition

# Add description item_quantity_z_score_to_overall_item_quantity_14d.update_description( "Z-Score of the item Quantity in relation to the distribution of item " "Quantity among all items over a 14d period." ) # See feature definition file item_quantity_z_score_to_overall_item_quantity_14d.definition