4. Update Descriptions to Tables

In [1]:

import featurebyte as fb

# Set your profile to the tutorial environment
fb.use_profile("tutorial")

catalog_name = "Loan Applications Dataset SDK Tutorial"
catalog = fb.Catalog.activate(catalog_name)

import featurebyte as fb # Set your profile to the tutorial environment fb.use_profile("tutorial") catalog_name = "Loan Applications Dataset SDK Tutorial" catalog = fb.Catalog.activate(catalog_name)

14:07:25 | INFO     | SDK version: 3.0.1.dev45
INFO    :featurebyte:SDK version: 3.0.1.dev45
14:07:25 | INFO     | No catalog activated.
INFO    :featurebyte:No catalog activated.
14:07:25 | INFO     | Using profile: tutorial
INFO    :featurebyte:Using profile: tutorial
14:07:25 | INFO     | Using configuration file at: /Users/gxav/.featurebyte/config.yaml
INFO    :featurebyte:Using configuration file at: /Users/gxav/.featurebyte/config.yaml
14:07:25 | INFO     | Active profile: tutorial (https://tutorials.featurebyte.com/api/v1)
INFO    :featurebyte:Active profile: tutorial (https://tutorials.featurebyte.com/api/v1)
14:07:25 | INFO     | SDK version: 3.0.1.dev45
INFO    :featurebyte:SDK version: 3.0.1.dev45
14:07:25 | INFO     | No catalog activated.
INFO    :featurebyte:No catalog activated.
14:07:25 | INFO     | Catalog activated: Loan Applications Dataset SDK Tutorial
INFO    :featurebyte.api.catalog:Catalog activated: Loan Applications Dataset SDK Tutorial
16:05:56 | WARNING  | Remote SDK version (1.1.0.dev7) is different from local (1.1.0.dev1). Update local SDK to avoid unexpected behavior.
16:05:56 | INFO     | No catalog activated.
16:05:56 | INFO     | Catalog activated: Grocery Dataset Tutorial

Get tables from the catalog first¶

In [2]:

catalog.list_tables()

catalog.list_tables()

Out[2]:

	id	name	type	status	entities	created_at
0	683d3a70f4d55cd61d526cee	CREDIT_CARD_MONTHLY_BALANCE	time_series_table	PUBLIC_DRAFT	[Client]	2025-06-02T05:45:20.813000
1	683d3a6ef4d55cd61d526ced	LOAN_STATUS	scd_table	PUBLIC_DRAFT	[Loan, PriorApplication]	2025-06-02T05:45:18.744000
2	683d3a6cf4d55cd61d526cec	PREVIOUS_APPLICATION	event_table	PUBLIC_DRAFT	[PriorApplication, Client]	2025-06-02T05:45:16.825000
3	683d3a6af4d55cd61d526ceb	INSTALLMENTS_PAYMENTS	event_table	PUBLIC_DRAFT	[Installment, PriorApplication]	2025-06-02T05:45:14.598000
4	683d3a69f4d55cd61d526cea	BUREAU	event_table	PUBLIC_DRAFT	[Client, BureauReportedCredit]	2025-06-02T05:45:13.206000
5	683d3a66f4d55cd61d526ce9	CLIENT_PROFILE	scd_table	PUBLIC_DRAFT	[Client]	2025-06-02T05:45:11.014000
6	683d3a64f4d55cd61d526ce8	NEW_APPLICATION	dimension_table	PUBLIC_DRAFT	[New Application, Client]	2025-06-02T05:45:08.853000

In [3]:

new_application = catalog.get_table("NEW_APPLICATION")
client_profile = catalog.get_table("CLIENT_PROFILE")
bureau = catalog.get_table("BUREAU")
previous_application = catalog.get_table("PREVIOUS_APPLICATION")
loan_status = catalog.get_table("LOAN_STATUS")
installments_payments = catalog.get_table("INSTALLMENTS_PAYMENTS")
credit_card_balance = catalog.get_table("CREDIT_CARD_MONTHLY_BALANCE")

new_application = catalog.get_table("NEW_APPLICATION") client_profile = catalog.get_table("CLIENT_PROFILE") bureau = catalog.get_table("BUREAU") previous_application = catalog.get_table("PREVIOUS_APPLICATION") loan_status = catalog.get_table("LOAN_STATUS") installments_payments = catalog.get_table("INSTALLMENTS_PAYMENTS") credit_card_balance = catalog.get_table("CREDIT_CARD_MONTHLY_BALANCE")

Discover the current descriptions of tables¶

In [4]:

new_application.description

new_application.description

Out[4]:

'Contains information about new loan applications submitted by clients.'

In [5]:

client_profile.description

client_profile.description

Out[5]:

'Describes the profile for each client.'

In [6]:

bureau.description

bureau.description

Out[6]:

'Lists credits taken by clients from other financial institutions, as reported to the credit bureau.'

In [7]:

previous_application.description

previous_application.description

Out[7]:

'Details prior loan applications by the client.'

In [8]:

loan_status.description

loan_status.description

Out[8]:

'Tracks whether loan was terminated.'

In [9]:

installments_payments.description

installments_payments.description

Out[9]:

'Logs monthly installments for loans at the time of payment.'

In [10]:

credit_card_balance.description

credit_card_balance.description

Out[10]:

'Monthly balance summaries for credit cards.'

Update descriptions of one table¶

In [11]:

new_application.update_description('new loan applications.')

new_application.update_description('new loan applications.')

In [12]:

new_application.description

new_application.description

Out[12]:

'new loan applications.'

In [13]:

new_application.update_description('Records new loan applications.')

new_application.update_description('Records new loan applications.')

Discover the current descriptions of columns for NEW_APPLICATION¶

You can either display all columns together

In [14]:

import pandas as pd
pd.DataFrame(new_application.info(verbose=True)["columns_info"])

import pandas as pd pd.DataFrame(new_application.info(verbose=True)["columns_info"])

Out[14]:

	name	dtype	entity	semantic	critical_data_info	description
0	SK_ID_CURR	INT	New Application	dimension_id	None	ID of application
1	ClientID	INT	Client	None	None	ID of the client
2	CONTRACT_TYPE	VARCHAR	None	None	None	Identification if loan is cash or revolving
3	AMT_INCOME_TOTAL	FLOAT	None	None	None	Income of the client
4	AMT_CREDIT	FLOAT	None	None	None	Credit amount of the loan
...	...	...	...	...	...	...
107	AMT_REQ_CREDIT_BUREAU_WEEK	FLOAT	None	None	None	Number of enquiries to Credit Bureau about the...
108	AMT_REQ_CREDIT_BUREAU_MON	FLOAT	None	None	None	Number of enquiries to Credit Bureau about the...
109	AMT_REQ_CREDIT_BUREAU_QRT	FLOAT	None	None	None	Number of enquiries to Credit Bureau about the...
110	AMT_REQ_CREDIT_BUREAU_YEAR	FLOAT	None	None	None	Number of enquiries to Credit Bureau about the...
111	available_at	TIMESTAMP	None	record_creation_timestamp	None	Timestamp the record was added to the database

112 rows × 6 columns

Or display each column one by one

In [15]:

for column in new_application.columns:
    print(f"{column}: {new_application[column].description}")

for column in new_application.columns: print(f"{column}: {new_application[column].description}")

SK_ID_CURR: ID of application
ClientID: ID of the client
CONTRACT_TYPE: Identification if loan is cash or revolving
AMT_INCOME_TOTAL: Income of the client
AMT_CREDIT: Credit amount of the loan
AMT_ANNUITY: Loan annuity
AMT_GOODS_PRICE: For consumer loans it is the price of the goods for which the loan is given
TYPE_SUITE: Who was accompanying client when he was applying for the loan
REGION_POPULATION_RELATIVE: Normalized population of region where client lives (higher number means the client lives in more populated region)
application_time: Application timestamp
DAYS_EMPLOYED: How many days before the application the person started current employment
DAYS_REGISTRATION: How many days before the application did client change his registration
DAYS_ID_PUBLISH: How many days before the application did client change the identity document with which he applied for the loan
OWN_CAR_AGE: Age of client car
FLAG_MOBIL: Did client provide mobile phone (1=YES, 0=NO)
FLAG_EMP_PHONE: Did client provide work phone (1=YES, 0=NO)
FLAG_WORK_PHONE: Did client provide home phone (1=YES, 0=NO)
FLAG_CONT_MOBILE: Was mobile phone reachable (1=YES, 0=NO)
FLAG_PHONE: Did client provide home phone (1=YES, 0=NO)
FLAG_EMAIL: Did client provide email (1=YES, 0=NO)
REGION_RATING_CLIENT: Our rating of the region where client lives (1,2,3)
REGION_RATING_CLIENT_W_CITY: Our rating of the region where client lives with taking city into account (1,2,3)
WEEKDAY_APPR_PROCESS_START: On which day of the week did the client apply for the loan
HOUR_APPR_PROCESS_START: Approximately at what hour did the client apply for the loan
REG_REGION_NOT_LIVE_REGION: Flag if client permanent address does not match contact address (1=different, 0=same, at region level)
REG_REGION_NOT_WORK_REGION: Flag if client permanent address does not match work address (1=different, 0=same, at region level)
LIVE_REGION_NOT_WORK_REGION: Flag if client contact address does not match work address (1=different, 0=same, at region level)
REG_CITY_NOT_LIVE_CITY: Flag if client permanent address does not match contact address (1=different, 0=same, at city level)
REG_CITY_NOT_WORK_CITY: Flag if client permanent address does not match work address (1=different, 0=same, at city level)
LIVE_CITY_NOT_WORK_CITY: Flag if client contact address does not match work address (1=different, 0=same, at city level)
EXT_SOURCE_1: Normalized score from external data source
EXT_SOURCE_2: Normalized score from external data source
EXT_SOURCE_3: Normalized score from external data source
APARTMENTS_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
BASEMENTAREA_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
YEARS_BEGINEXPLUATATION_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
YEARS_BUILD_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
COMMONAREA_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
ELEVATORS_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
ENTRANCES_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
FLOORSMAX_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
FLOORSMIN_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LANDAREA_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LIVINGAPARTMENTS_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LIVINGAREA_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
NONLIVINGAPARTMENTS_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
NONLIVINGAREA_AVG: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
APARTMENTS_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
BASEMENTAREA_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
YEARS_BEGINEXPLUATATION_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
YEARS_BUILD_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
COMMONAREA_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
ELEVATORS_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
ENTRANCES_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
FLOORSMAX_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
FLOORSMIN_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LANDAREA_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LIVINGAPARTMENTS_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LIVINGAREA_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
NONLIVINGAPARTMENTS_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
NONLIVINGAREA_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
APARTMENTS_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
BASEMENTAREA_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
YEARS_BEGINEXPLUATATION_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
YEARS_BUILD_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
COMMONAREA_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
ELEVATORS_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
ENTRANCES_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
FLOORSMAX_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
FLOORSMIN_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LANDAREA_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LIVINGAPARTMENTS_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
LIVINGAREA_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
NONLIVINGAPARTMENTS_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
NONLIVINGAREA_MEDI: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
FONDKAPREMONT_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
HOUSETYPE_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
TOTALAREA_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
WALLSMATERIAL_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
EMERGENCYSTATE_MODE: Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor
OBS_30_CNT_SOCIAL_CIRCLE: How many observation of client social surroundings with observable 30 DPD (days past due) default
DEF_30_CNT_SOCIAL_CIRCLE: How many observation of client social surroundings defaulted on 30 DPD (days past due)
OBS_60_CNT_SOCIAL_CIRCLE: How many observation of client social surroundings with observable 60 DPD (days past due) default
DEF_60_CNT_SOCIAL_CIRCLE: How many observation of client social surroundings defaulted on 60 (days past due) DPD
DAYS_LAST_PHONE_CHANGE: How many days before application did client change phone
FLAG_DOCUMENT_2: Did client provide document 2
FLAG_DOCUMENT_3: Did client provide document 3
FLAG_DOCUMENT_4: Did client provide document 4
FLAG_DOCUMENT_5: Did client provide document 5
FLAG_DOCUMENT_6: Did client provide document 6
FLAG_DOCUMENT_7: Did client provide document 7
FLAG_DOCUMENT_8: Did client provide document 8
FLAG_DOCUMENT_9: Did client provide document 9
FLAG_DOCUMENT_10: Did client provide document 10
FLAG_DOCUMENT_11: Did client provide document 11
FLAG_DOCUMENT_12: Did client provide document 12
FLAG_DOCUMENT_13: Did client provide document 13
FLAG_DOCUMENT_14: Did client provide document 14
FLAG_DOCUMENT_15: Did client provide document 15
FLAG_DOCUMENT_16: Did client provide document 16
FLAG_DOCUMENT_17: Did client provide document 17
FLAG_DOCUMENT_18: Did client provide document 18
FLAG_DOCUMENT_19: Did client provide document 19
FLAG_DOCUMENT_20: Did client provide document 20
FLAG_DOCUMENT_21: Did client provide document 21
AMT_REQ_CREDIT_BUREAU_HOUR: Number of enquiries to Credit Bureau about the client one hour before application
AMT_REQ_CREDIT_BUREAU_DAY: Number of enquiries to Credit Bureau about the client one day before application (excluding one hour before application)
AMT_REQ_CREDIT_BUREAU_WEEK: Number of enquiries to Credit Bureau about the client one week before application (excluding one day before application)
AMT_REQ_CREDIT_BUREAU_MON: Number of enquiries to Credit Bureau about the client one month before application (excluding one week before application)
AMT_REQ_CREDIT_BUREAU_QRT: Number of enquiries to Credit Bureau about the client 3 month before application (excluding one month before application)
AMT_REQ_CREDIT_BUREAU_YEAR: Number of enquiries to Credit Bureau about the client one day year (excluding last 3 months before application)
available_at: Timestamp the record was added to the database

Update column descriptions¶

If the description is incorrect or incomplete, you can edit it

In [16]:

# By using the table method: update_column_description
new_application.update_column_description(
    "DAYS_EMPLOYED",
    "How many days before the application the person started current employment"
)

# By using the table method: update_column_description new_application.update_column_description( "DAYS_EMPLOYED", "How many days before the application the person started current employment" )

In [17]:

# Or by using the column method: update_description
new_application.DAYS_EMPLOYED.update_description(
    "How many days before the application the person started current employment"
)

# Or by using the column method: update_description new_application.DAYS_EMPLOYED.update_description( "How many days before the application the person started current employment" )

That's it for this tutorial. Again, this is an optional step, but it can drastically improve FeatureByte's feature ideation.

SDK reference for¶

• Table.info