Playground: Healthcare¶
The notebook creates a fresh catalog using the healthcare dataset. You can use it to practice feature engineering.
Load the featurebyte library and connect to the local instance of featurebyte¶
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# library imports
import pandas as pd
import numpy as np
# load the featurebyte SDK
import featurebyte as fb
# start the local server, then wait for it to be healthy before proceeding
fb.playground()
# library imports
import pandas as pd
import numpy as np
# load the featurebyte SDK
import featurebyte as fb
# start the local server, then wait for it to be healthy before proceeding
fb.playground()
02:08:26 | INFO | Using configuration file at: /home/chester/.featurebyte/config.yaml 02:08:26 | INFO | Active profile: local (http://127.0.0.1:8088) 02:08:26 | INFO | SDK version: 0.2.2 02:08:26 | INFO | Active catalog: default 02:08:26 | INFO | 0 feature list, 0 feature deployed 02:08:26 | INFO | (1/4) Starting featurebyte services Container redis Running Container spark-thrift Running Container mongo-rs Running Container featurebyte-server Running Container featurebyte-worker Running Container mongo-rs Waiting Container redis Waiting Container mongo-rs Waiting Container mongo-rs Healthy Container mongo-rs Healthy Container redis Healthy 02:08:27 | INFO | (2/4) Creating local spark feature store 02:08:27 | INFO | (3/4) Import datasets 02:08:28 | INFO | Dataset grocery already exists, skipping import 02:08:28 | INFO | Dataset healthcare already exists, skipping import 02:08:28 | INFO | Dataset creditcard already exists, skipping import 02:08:28 | INFO | (4/4) Playground environment started successfully. Ready to go! 🚀
Create a pre-built catalog for this tutorial, with the data, metadata, and features already set up¶
Note that creating a pre-built catalog is not a step you will do in real-life. This is a function specific to this quick-start tutorial to quickly skip over many of the preparatory steps and get you to a point where you can materialize features.
In a real-life project you would do data modeling, declaring the tables, entities, and the associated metadata. This would not be a frequent task, but forms the basis for best-practice feature engineering.
Load the featurebyte library and connect to the local instance of featurebyte¶
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# get the functions to create a pre-built catalog
from prebuilt_catalogs import *
# create a new catalog for this tutorial
catalog = create_tutorial_catalog(PrebuiltCatalog.Playground_Healthcare)
# get the functions to create a pre-built catalog
from prebuilt_catalogs import *
# create a new catalog for this tutorial
catalog = create_tutorial_catalog(PrebuiltCatalog.Playground_Healthcare)
Cleaning up existing tutorial catalogs
02:08:28 | INFO | Catalog activated: healthcare playground 20230511:0208
Building a playground catalog for healthcare named [healthcare playground 20230511:0208]
Creating new catalog
Catalog created
Registering the source tables
Registering the entities
Tagging the entities to columns in the data tables
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# suggested script to load the tables and views into your notebook
# get the table objects
medicalproduct_table = catalog.get_table("MEDICALPRODUCT")
specialtygroup_table = catalog.get_table("SPECIALTYGROUP")
icd9hierarchy_table = catalog.get_table("ICD9HIERARCHY")
labobservation_table = catalog.get_table("LABOBSERVATION")
labresult_table = catalog.get_table("LABRESULT")
prescription_table = catalog.get_table("PRESCRIPTION")
visit_table = catalog.get_table("VISIT")
statedetails_table = catalog.get_table("STATEDETAILS")
allergy_table = catalog.get_table("ALLERGY")
patientsmokingstatus_table = catalog.get_table("PATIENTSMOKINGSTATUS")
diagnosis_table = catalog.get_table("DIAGNOSIS")
patient_table = catalog.get_table("PATIENT")
# get the view objects
medicalproduct_view = medicalproduct_table.get_view()
specialtygroup_view = specialtygroup_table.get_view()
icd9hierarchy_view = icd9hierarchy_table.get_view()
labobservation_view = labobservation_table.get_view()
labresult_view = labresult_table.get_view()
prescription_view = prescription_table.get_view()
visit_view = visit_table.get_view()
statedetails_view = statedetails_table.get_view()
allergy_view = allergy_table.get_view()
patientsmokingstatus_view = patientsmokingstatus_table.get_view()
diagnosis_view = diagnosis_table.get_view()
patient_view = patient_table.get_view()
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