diff --git a/HomeCredit_columns_description.csv b/HomeCredit_columns_description.csv index dd26f83..8d05e82 100644 --- a/HomeCredit_columns_description.csv +++ b/HomeCredit_columns_description.csv @@ -1,6 +1,6 @@ ,Table,Row,Description,Special 1,application_{train|test}.csv,SK_ID_CURR,ID of loan in our sample, -2,application_{train|test}.csv,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), +2,application_{train|test}.csv,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)", 5,application_{train|test}.csv,NAME_CONTRACT_TYPE,Identification if loan is cash or revolving, 6,application_{train|test}.csv,CODE_GENDER,Gender of the client, 7,application_{train|test}.csv,FLAG_OWN_CAR,Flag if the client owns a car, @@ -11,85 +11,85 @@ 12,application_{train|test}.csv,AMT_ANNUITY,Loan annuity, 13,application_{train|test}.csv,AMT_GOODS_PRICE,For consumer loans it is the price of the goods for which the loan is given, 14,application_{train|test}.csv,NAME_TYPE_SUITE,Who was accompanying client when he was applying for the loan, -15,application_{train|test}.csv,NAME_INCOME_TYPE,Clients income type (businessman, working, maternity leave,…), +15,application_{train|test}.csv,NAME_INCOME_TYPE,"Clients income type (businessman, working, maternity leave,…)", 16,application_{train|test}.csv,NAME_EDUCATION_TYPE,Level of highest education the client achieved, 17,application_{train|test}.csv,NAME_FAMILY_STATUS,Family status of the client, -18,application_{train|test}.csv,NAME_HOUSING_TYPE,What is the housing situation of the client (renting, living with parents, ...), +18,application_{train|test}.csv,NAME_HOUSING_TYPE,"What is the housing situation of the client (renting, living with parents, ...)", 19,application_{train|test}.csv,REGION_POPULATION_RELATIVE,Normalized population of region where client lives (higher number means the client lives in more populated region),normalized 20,application_{train|test}.csv,DAYS_BIRTH,Client's age in days at the time of application,time only relative to the application 21,application_{train|test}.csv,DAYS_EMPLOYED,How many days before the application the person started current employment,time only relative to the application 22,application_{train|test}.csv,DAYS_REGISTRATION,How many days before the application did client change his registration,time only relative to the application 23,application_{train|test}.csv,DAYS_ID_PUBLISH,How many days before the application did client change the identity document with which he applied for the loan,time only relative to the application 24,application_{train|test}.csv,OWN_CAR_AGE,Age of client's car, -25,application_{train|test}.csv,FLAG_MOBIL,Did client provide mobile phone (1=YES, 0=NO), -26,application_{train|test}.csv,FLAG_EMP_PHONE,Did client provide work phone (1=YES, 0=NO), -27,application_{train|test}.csv,FLAG_WORK_PHONE,Did client provide home phone (1=YES, 0=NO), -28,application_{train|test}.csv,FLAG_CONT_MOBILE,Was mobile phone reachable (1=YES, 0=NO), -29,application_{train|test}.csv,FLAG_PHONE,Did client provide home phone (1=YES, 0=NO), -30,application_{train|test}.csv,FLAG_EMAIL,Did client provide email (1=YES, 0=NO), +25,application_{train|test}.csv,FLAG_MOBIL,"Did client provide mobile phone (1=YES, 0=NO)", +26,application_{train|test}.csv,FLAG_EMP_PHONE,"Did client provide work phone (1=YES, 0=NO)", +27,application_{train|test}.csv,FLAG_WORK_PHONE,"Did client provide home phone (1=YES, 0=NO)", +28,application_{train|test}.csv,FLAG_CONT_MOBILE,"Was mobile phone reachable (1=YES, 0=NO)", +29,application_{train|test}.csv,FLAG_PHONE,"Did client provide home phone (1=YES, 0=NO)", +30,application_{train|test}.csv,FLAG_EMAIL,"Did client provide email (1=YES, 0=NO)", 31,application_{train|test}.csv,OCCUPATION_TYPE,What kind of occupation does the client have, 32,application_{train|test}.csv,CNT_FAM_MEMBERS,How many family members does client have, -33,application_{train|test}.csv,REGION_RATING_CLIENT,Our rating of the region where client lives (1,2,3), -34,application_{train|test}.csv,REGION_RATING_CLIENT_W_CITY,Our rating of the region where client lives with taking city into account (1,2,3), +33,application_{train|test}.csv,REGION_RATING_CLIENT,"Our rating of the region where client lives (1,2,3)", +34,application_{train|test}.csv,REGION_RATING_CLIENT_W_CITY,"Our rating of the region where client lives with taking city into account (1,2,3)", 35,application_{train|test}.csv,WEEKDAY_APPR_PROCESS_START,On which day of the week did the client apply for the loan, 36,application_{train|test}.csv,HOUR_APPR_PROCESS_START,Approximately at what hour did the client apply for the loan,rounded -37,application_{train|test}.csv,REG_REGION_NOT_LIVE_REGION,Flag if client's permanent address does not match contact address (1=different, 0=same, at region level), -38,application_{train|test}.csv,REG_REGION_NOT_WORK_REGION,Flag if client's permanent address does not match work address (1=different, 0=same, at region level), -39,application_{train|test}.csv,LIVE_REGION_NOT_WORK_REGION,Flag if client's contact address does not match work address (1=different, 0=same, at region level), -40,application_{train|test}.csv,REG_CITY_NOT_LIVE_CITY,Flag if client's permanent address does not match contact address (1=different, 0=same, at city level), -41,application_{train|test}.csv,REG_CITY_NOT_WORK_CITY,Flag if client's permanent address does not match work address (1=different, 0=same, at city level), -42,application_{train|test}.csv,LIVE_CITY_NOT_WORK_CITY,Flag if client's contact address does not match work address (1=different, 0=same, at city level), +37,application_{train|test}.csv,REG_REGION_NOT_LIVE_REGION,"Flag if client's permanent address does not match contact address (1=different, 0=same, at region level)", +38,application_{train|test}.csv,REG_REGION_NOT_WORK_REGION,"Flag if client's permanent address does not match work address (1=different, 0=same, at region level)", +39,application_{train|test}.csv,LIVE_REGION_NOT_WORK_REGION,"Flag if client's contact address does not match work address (1=different, 0=same, at region level)", +40,application_{train|test}.csv,REG_CITY_NOT_LIVE_CITY,"Flag if client's permanent address does not match contact address (1=different, 0=same, at city level)", +41,application_{train|test}.csv,REG_CITY_NOT_WORK_CITY,"Flag if client's permanent address does not match work address (1=different, 0=same, at city level)", +42,application_{train|test}.csv,LIVE_CITY_NOT_WORK_CITY,"Flag if client's contact address does not match work address (1=different, 0=same, at city level)", 43,application_{train|test}.csv,ORGANIZATION_TYPE,Type of organization where client works, 44,application_{train|test}.csv,EXT_SOURCE_1,Normalized score from external data source,normalized 45,application_{train|test}.csv,EXT_SOURCE_2,Normalized score from external data source,normalized 46,application_{train|test}.csv,EXT_SOURCE_3,Normalized score from external data source,normalized -47,application_{train|test}.csv,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,normalized -48,application_{train|test}.csv,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,normalized -49,application_{train|test}.csv,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,normalized -50,application_{train|test}.csv,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,normalized -51,application_{train|test}.csv,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,normalized -52,application_{train|test}.csv,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,normalized -53,application_{train|test}.csv,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,normalized -54,application_{train|test}.csv,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,normalized -55,application_{train|test}.csv,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,normalized -56,application_{train|test}.csv,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,normalized -57,application_{train|test}.csv,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,normalized -58,application_{train|test}.csv,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,normalized -59,application_{train|test}.csv,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,normalized -60,application_{train|test}.csv,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,normalized -61,application_{train|test}.csv,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,normalized -62,application_{train|test}.csv,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,normalized -63,application_{train|test}.csv,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,normalized -64,application_{train|test}.csv,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,normalized -65,application_{train|test}.csv,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,normalized -66,application_{train|test}.csv,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,normalized -67,application_{train|test}.csv,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,normalized -68,application_{train|test}.csv,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,normalized -69,application_{train|test}.csv,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,normalized -70,application_{train|test}.csv,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,normalized -71,application_{train|test}.csv,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,normalized -72,application_{train|test}.csv,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,normalized -73,application_{train|test}.csv,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,normalized -74,application_{train|test}.csv,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,normalized -75,application_{train|test}.csv,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,normalized -76,application_{train|test}.csv,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,normalized -77,application_{train|test}.csv,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,normalized -78,application_{train|test}.csv,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,normalized -79,application_{train|test}.csv,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,normalized -80,application_{train|test}.csv,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,normalized -81,application_{train|test}.csv,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,normalized -82,application_{train|test}.csv,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,normalized -83,application_{train|test}.csv,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,normalized -84,application_{train|test}.csv,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,normalized -85,application_{train|test}.csv,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,normalized -86,application_{train|test}.csv,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,normalized -87,application_{train|test}.csv,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,normalized -88,application_{train|test}.csv,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,normalized -89,application_{train|test}.csv,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,normalized -90,application_{train|test}.csv,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,normalized -91,application_{train|test}.csv,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,normalized -92,application_{train|test}.csv,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,normalized -93,application_{train|test}.csv,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,normalized +47,application_{train|test}.csv,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",normalized +48,application_{train|test}.csv,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",normalized +49,application_{train|test}.csv,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",normalized +50,application_{train|test}.csv,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",normalized +51,application_{train|test}.csv,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",normalized +52,application_{train|test}.csv,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",normalized +53,application_{train|test}.csv,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",normalized +54,application_{train|test}.csv,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",normalized +55,application_{train|test}.csv,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",normalized +56,application_{train|test}.csv,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",normalized +57,application_{train|test}.csv,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",normalized +58,application_{train|test}.csv,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",normalized +59,application_{train|test}.csv,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",normalized +60,application_{train|test}.csv,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",normalized +61,application_{train|test}.csv,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",normalized +62,application_{train|test}.csv,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",normalized +63,application_{train|test}.csv,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",normalized +64,application_{train|test}.csv,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",normalized +65,application_{train|test}.csv,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",normalized +66,application_{train|test}.csv,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",normalized +67,application_{train|test}.csv,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",normalized +68,application_{train|test}.csv,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",normalized +69,application_{train|test}.csv,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",normalized +70,application_{train|test}.csv,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",normalized +71,application_{train|test}.csv,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",normalized +72,application_{train|test}.csv,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",normalized +73,application_{train|test}.csv,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",normalized +74,application_{train|test}.csv,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",normalized +75,application_{train|test}.csv,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",normalized +76,application_{train|test}.csv,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",normalized +77,application_{train|test}.csv,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",normalized +78,application_{train|test}.csv,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",normalized +79,application_{train|test}.csv,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",normalized +80,application_{train|test}.csv,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",normalized +81,application_{train|test}.csv,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",normalized +82,application_{train|test}.csv,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",normalized +83,application_{train|test}.csv,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",normalized +84,application_{train|test}.csv,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",normalized +85,application_{train|test}.csv,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",normalized +86,application_{train|test}.csv,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",normalized +87,application_{train|test}.csv,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",normalized +88,application_{train|test}.csv,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",normalized +89,application_{train|test}.csv,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",normalized +90,application_{train|test}.csv,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",normalized +91,application_{train|test}.csv,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",normalized +92,application_{train|test}.csv,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",normalized +93,application_{train|test}.csv,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",normalized 94,application_{train|test}.csv,OBS_30_CNT_SOCIAL_CIRCLE,How many observation of client's social surroundings with observable 30 DPD (days past due) default, 95,application_{train|test}.csv,DEF_30_CNT_SOCIAL_CIRCLE,How many observation of client's social surroundings defaulted on 30 DPD (days past due) , 96,application_{train|test}.csv,OBS_60_CNT_SOCIAL_CIRCLE,How many observation of client's social surroundings with observable 60 DPD (days past due) default, @@ -121,7 +121,7 @@ 122,application_{train|test}.csv,AMT_REQ_CREDIT_BUREAU_MON,Number of enquiries to Credit Bureau about the client one month before application (excluding one week before application), 123,application_{train|test}.csv,AMT_REQ_CREDIT_BUREAU_QRT,Number of enquiries to Credit Bureau about the client 3 month before application (excluding one month before application), 124,application_{train|test}.csv,AMT_REQ_CREDIT_BUREAU_YEAR,Number of enquiries to Credit Bureau about the client one day year (excluding last 3 months before application), -125,bureau.csv,SK_ID_CURR,ID of loan in our sample - one loan in our sample can have 0,1,2 or more related previous credits in credit bureau ,hashed +125,bureau.csv,SK_ID_CURR,"ID of loan in our sample - one loan in our sample can have 0,1,2 or more related previous credits in credit bureau ",hashed 126,bureau.csv,SK_BUREAU_ID,Recoded ID of previous Credit Bureau credit related to our loan (unique coding for each loan application),hashed 127,bureau.csv,CREDIT_ACTIVE,Status of the Credit Bureau (CB) reported credits, 128,bureau.csv,CREDIT_CURRENCY,Recoded currency of the Credit Bureau credit,recoded @@ -135,21 +135,21 @@ 136,bureau.csv,AMT_CREDIT_SUM_DEBT,Current debt on Credit Bureau credit, 137,bureau.csv,AMT_CREDIT_SUM_LIMIT,Current credit limit of credit card reported in Credit Bureau, 138,bureau.csv,AMT_CREDIT_SUM_OVERDUE,Current amount overdue on Credit Bureau credit, -139,bureau.csv,CREDIT_TYPE,Type of Credit Bureau credit (Car, cash,...), +139,bureau.csv,CREDIT_TYPE,"Type of Credit Bureau credit (Car, cash,...)", 140,bureau.csv,DAYS_CREDIT_UPDATE,How many days before loan application did last information about the Credit Bureau credit come,time only relative to the application 141,bureau.csv,AMT_ANNUITY,Annuity of the Credit Bureau credit, 142,bureau_balance.csv,SK_BUREAU_ID,Recoded ID of Credit Bureau credit (unique coding for each application) - use this to join to CREDIT_BUREAU table ,hashed 143,bureau_balance.csv,MONTHS_BALANCE,Month of balance relative to application date (-1 means the freshest balance date),time only relative to the application -144,bureau_balance.csv,STATUS,Status of Credit Bureau loan during the month (active, closed, DPD0-30,… [C means closed, X means status unknown, 0 means no DPD, 1 means maximal did during month between 1-30, 2 means DPD 31-60,… 5 means DPD 120+ or sold or written off ] ), -145,POS_CASH_balance.csv,SK_ID_PREV ,ID of previous credit in Home Credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit), +144,bureau_balance.csv,STATUS,"Status of Credit Bureau loan during the month (active, closed, DPD0-30,… [C means closed, X means status unknown, 0 means no DPD, 1 means maximal did during month between 1-30, 2 means DPD 31-60,… 5 means DPD 120+ or sold or written off ] )", +145,POS_CASH_balance.csv,SK_ID_PREV ,"ID of previous credit in Home Credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit)", 146,POS_CASH_balance.csv,SK_ID_CURR,ID of loan in our sample, -147,POS_CASH_balance.csv,MONTHS_BALANCE,Month of balance relative to application date (-1 means the information to the freshest monthly snapshot, 0 means the information at application - often it will be the same as -1 as many banks are not updating the information to Credit Bureau regularly ),time only relative to the application +147,POS_CASH_balance.csv,MONTHS_BALANCE,"Month of balance relative to application date (-1 means the information to the freshest monthly snapshot, 0 means the information at application - often it will be the same as -1 as many banks are not updating the information to Credit Bureau regularly )",time only relative to the application 148,POS_CASH_balance.csv,CNT_INSTALMENT,Term of previous credit (can change over time), 149,POS_CASH_balance.csv,CNT_INSTALMENT_FUTURE,Installments left to pay on the previous credit, 150,POS_CASH_balance.csv,NAME_CONTRACT_STATUS,Contract status during the month, 151,POS_CASH_balance.csv,SK_DPD,DPD (days past due) during the month of previous credit, 152,POS_CASH_balance.csv,SK_DPD_DEF,DPD during the month with tolerance (debts with low loan amounts are ignored) of the previous credit, -153,credit_card_balance.csv,SK_ID_PREV ,ID of previous credit in Home credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit),hashed +153,credit_card_balance.csv,SK_ID_PREV ,"ID of previous credit in Home credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit)",hashed 154,credit_card_balance.csv,SK_ID_CURR,ID of loan in our sample,hashed 155,credit_card_balance.csv,MONTHS_BALANCE,Month of balance relative to application date (-1 means the freshest balance date),time only relative to the application 156,credit_card_balance.csv,AMT_BALANCE,Balance during the month of previous credit, @@ -169,15 +169,15 @@ 170,credit_card_balance.csv,CNT_DRAWINGS_OTHER_CURRENT,Number of other drawings during this month on the previous credit, 171,credit_card_balance.csv,CNT_DRAWINGS_POS_CURRENT,Number of drawings for goods during this month on the previous credit, 172,credit_card_balance.csv,CNT_INSTALMENT_MATURE_CUM,Number of paid installments on the previous credit, -173,credit_card_balance.csv,NAME_CONTRACT_STATUS,Contract status (active signed,...) on the previous credit, +173,credit_card_balance.csv,NAME_CONTRACT_STATUS,"Contract status (active signed,...) on the previous credit", 174,credit_card_balance.csv,SK_DPD,DPD (Days past due) during the month on the previous credit, 175,credit_card_balance.csv,SK_DPD_DEF,DPD (Days past due) during the month with tolerance (debts with low loan amounts are ignored) of the previous credit, -176,previous_application.csv,SK_ID_PREV ,ID of previous credit in Home credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loan applications in Home Credit, previous application could, but not necessarily have to lead to credit) ,hashed +176,previous_application.csv,SK_ID_PREV ,"ID of previous credit in Home credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loan applications in Home Credit, previous application could, but not necessarily have to lead to credit) ",hashed 177,previous_application.csv,SK_ID_CURR,ID of loan in our sample,hashed -178,previous_application.csv,NAME_CONTRACT_TYPE,Contract product type (Cash loan, consumer loan [POS] ,...) of the previous application, +178,previous_application.csv,NAME_CONTRACT_TYPE,"Contract product type (Cash loan, consumer loan [POS] ,...) of the previous application", 179,previous_application.csv,AMT_ANNUITY,Annuity of previous application, 180,previous_application.csv,AMT_APPLICATION,For how much credit did client ask on the previous application, -181,previous_application.csv,AMT_CREDIT,Final credit amount on the previous application. This differs from AMT_APPLICATION in a way that the AMT_APPLICATION is the amount for which the client initially applied for, but during our approval process he could have received different amount - AMT_CREDIT, +181,previous_application.csv,AMT_CREDIT,"Final credit amount on the previous application. This differs from AMT_APPLICATION in a way that the AMT_APPLICATION is the amount for which the client initially applied for, but during our approval process he could have received different amount - AMT_CREDIT", 182,previous_application.csv,AMT_DOWN_PAYMENT,Down payment on the previous application, 183,previous_application.csv,AMT_GOODS_PRICE,Goods price of good that client asked for (if applicable) on the previous application, 184,previous_application.csv,WEEKDAY_APPR_PROCESS_START,On which day of the week did the client apply for previous application, @@ -189,14 +189,14 @@ 190,previous_application.csv,RATE_INTEREST_PRIMARY,Interest rate normalized on previous credit,normalized 191,previous_application.csv,RATE_INTEREST_PRIVILEGED,Interest rate normalized on previous credit,normalized 192,previous_application.csv,NAME_CASH_LOAN_PURPOSE,Purpose of the cash loan, -193,previous_application.csv,NAME_CONTRACT_STATUS,Contract status (approved, cancelled, ...) of previous application, +193,previous_application.csv,NAME_CONTRACT_STATUS,"Contract status (approved, cancelled, ...) of previous application", 194,previous_application.csv,DAYS_DECISION,Relative to current application when was the decision about previous application made,time only relative to the application 195,previous_application.csv,NAME_PAYMENT_TYPE,Payment method that client chose to pay for the previous application, 196,previous_application.csv,CODE_REJECT_REASON,Why was the previous application rejected, 197,previous_application.csv,NAME_TYPE_SUITE,Who accompanied client when applying for the previous application, 198,previous_application.csv,NAME_CLIENT_TYPE,Was the client old or new client when applying for the previous application, 199,previous_application.csv,NAME_GOODS_CATEGORY,What kind of goods did the client apply for in the previous application, -200,previous_application.csv,NAME_PORTFOLIO,Was the previous application for CASH, POS, CAR, …, +200,previous_application.csv,NAME_PORTFOLIO,"Was the previous application for CASH, POS, CAR, …", 201,previous_application.csv,NAME_PRODUCT_TYPE,Was the previous application x-sell o walk-in, 202,previous_application.csv,CHANNEL_TYPE,Through which channel we acquired the client on the previous application, 203,previous_application.csv,SELLERPLACE_AREA,Selling area of seller place of the previous application, @@ -210,7 +210,7 @@ 211,previous_application.csv,DAYS_LAST_DUE,Relative to application date of current application when was the last due date of the previous application,time only relative to the application 212,previous_application.csv,DAYS_TERMINATION,Relative to application date of current application when was the expected termination of the previous application,time only relative to the application 213,previous_application.csv,NFLAG_INSURED_ON_APPROVAL,Did the client requested insurance during the previous application, -214,installments_payments.csv,SK_ID_PREV ,ID of previous credit in Home credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit),hashed +214,installments_payments.csv,SK_ID_PREV ,"ID of previous credit in Home credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit)",hashed 215,installments_payments.csv,SK_ID_CURR,ID of loan in our sample,hashed 216,installments_payments.csv,NUM_INSTALMENT_VERSION,Version of installment calendar (0 is for credit card) of previous credit. Change of installment version from month to month signifies that some parameter of payment calendar has changed, 217,installments_payments.csv,NUM_INSTALMENT_NUMBER,On which installment we observe payment,