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Training application data from the Home Credit Default Risk competition. The data are credited to Home Credit and the competition's official data page on Kaggle. The copy used to build this package is a third-party mirror published by the Hugging Face user `cantalapiedra`; it is provided as a convenient download location and is not the official source.

Usage

home_credit_application

Format

A data frame with 307,511 observations and 122 variables:

sk_id_curr

ID of loan in our sample

target

Target variable (1 - client with payment difficulties: he/she had late payment more than X days on at least one of the first Y installments of the loan in our sample, 0 - all other cases)

name_contract_type

Identification if loan is cash or revolving

code_gender

Gender of the client

flag_own_car

Flag if the client owns a car

flag_own_realty

Flag if client owns a house or flat

cnt_children

Number of children the client has

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

name_type_suite

Who was accompanying client when he was applying for the loan

name_income_type

Client income type (for example, business, employment, or maternity leave).

name_education_type

Level of highest education the client achieved

name_family_status

Family status of the client

name_housing_type

What is the housing situation of the client (renting, living with parents, ...)

region_population_relative

Normalized population of region where client lives (higher number means the client lives in more populated region)

days_birth

Client's age in days at the time of application

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's 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)

occupation_type

What kind of occupation does the client have

cnt_fam_members

How many family members does client have

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's permanent address does not match contact address (1=different, 0=same, at region level)

reg_region_not_work_region

Flag if client's permanent address does not match work address (1=different, 0=same, at region level)

live_region_not_work_region

Flag if client's contact address does not match work address (1=different, 0=same, at region level)

reg_city_not_live_city

Flag if client's permanent address does not match contact address (1=different, 0=same, at city level)

reg_city_not_work_city

Flag if client's permanent address does not match work address (1=different, 0=same, at city level)

live_city_not_work_city

Flag if client's contact address does not match work address (1=different, 0=same, at city level)

organization_type

Type of organization where client works

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's social surroundings with observable 30 DPD (days past due) default

def_30_cnt_social_circle

How many observation of client's social surroundings defaulted on 30 DPD (days past due)

obs_60_cnt_social_circle

How many observation of client's social surroundings with observable 60 DPD (days past due) default

def_60_cnt_social_circle

How many observation of client's 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)

Source

Official source: Home Credit Default Risk competition on Kaggle, https://www.kaggle.com/competitions/home-credit-default-risk/data. Third-party copy used to build the package: https://huggingface.co/cantalapiedra/poc_scoring_fair/resolve/main/application_train.csv?download=true.

References

Home Credit Default Risk competition, https://www.kaggle.com/competitions/home-credit-default-risk.