Loan Eligible Dataset

Loan Eligibility Predictions With your notebook

@kaggle.vikasukani_loan_eligible_dataset

Table List

2 tables(35.37 KB)

Loan Train

@kaggle.vikasukani_loan_eligible_dataset.loan_train

20.17 KB
614 rows
13 columns

loan_id Loan ID	gender Gender	married Married	dependents Dependents	education Education	self_employed Self Employed	applicantincome ApplicantIncome	coapplicantincome CoapplicantIncome	loanamount LoanAmount	loan_amount_term Loan Amount Term	credit_history Credit History	property_area Property Area	loan_status Loan Status
LP001002	Male	No	0	Graduate	No	5849			360	1	Urban	Y
LP001003	Male	Yes	1	Graduate	No	4583	1508	128	360	1	Rural	N
LP001005	Male	Yes	0	Graduate	Yes	3000		66	360	1	Urban	Y
LP001006	Male	Yes	0	Not Graduate	No	2583	2358	120	360	1	Urban	Y
LP001008	Male	No	0	Graduate	No	6000		141	360	1	Urban	Y
LP001011	Male	Yes	2	Graduate	Yes	5417	4196	267	360	1	Urban	Y
LP001013	Male	Yes	0	Not Graduate	No	2333	1516	95	360	1	Urban	Y
LP001014	Male	Yes	3+	Graduate	No	3036	2504	158	360		Semiurban	N
LP001018	Male	Yes	2	Graduate	No	4006	1526	168	360	1	Urban	Y
LP001020	Male	Yes	1	Graduate	No	12841	10968	349	360	1	Semiurban	N


CREATE TABLE loan_train (
  "loan_id" VARCHAR,
  "gender" VARCHAR,
  "married" VARCHAR,
  "dependents" VARCHAR,
  "education" VARCHAR,
  "self_employed" VARCHAR,
  "applicantincome" BIGINT,
  "coapplicantincome" DOUBLE,
  "loanamount" DOUBLE,
  "loan_amount_term" DOUBLE,
  "credit_history" DOUBLE,
  "property_area" VARCHAR,
  "loan_status" VARCHAR
);

Loan Eligible Dataset

Table List

Loan Train

@kaggle.vikasukani_loan_eligible_dataset.loan_train

loan_id

gender

married

dependents

education

self_employed

applicantincome

coapplicantincome

loanamount

loan_amount_term

credit_history

property_area

loan_status

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