Bank Customer Churn Data

A comprehensive dataset for Churn Prediction

@kaggle.pentakrishnakishore_bank_customer_churn_data

Table List

1 table(2.05 MB)

Churn Prediction

@kaggle.pentakrishnakishore_bank_customer_churn_data.churn_prediction

2.05 MB
28382 rows
21 columns

customer_id Customer Id	vintage Vintage	age Age	gender Gender	dependents Dependents	occupation Occupation	city City	customer_nw_category Customer Nw Category	branch_code Branch Code	current_balance Current Balance	previous_month_end_balance Previous Month End Balance	average_monthly_balance_prevq Average Monthly Balance PrevQ	average_monthly_balance_prevq2 Average Monthly Balance PrevQ2	current_month_credit Current Month Credit	previous_month_credit Previous Month Credit	current_month_debit Current Month Debit	previous_month_debit Previous Month Debit	current_month_balance Current Month Balance	previous_month_balance Previous Month Balance	churn Churn	last_transaction Last Transaction
1	2101	66	Male		self_employed	187	2	755	1458.71	1458.71	1458.71	1449.07	0.2	0.2	0.2	0.2	1458.71	1458.71		Tue May 21 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
2	2348	35	Male		self_employed		2	3214	5390.37	8704.66	7799.26	12419.41	0.56	0.56	5486.27	100.56	6496.78	8787.61		Fri Nov 01 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
4	2194	31	Male		salaried	146	2	41	3913.16	5815.29	4910.17	2815.94	0.61	0.61	6046.73	259.23	5006.28	5070.14
5	2329	90	nan		self_employed	1020	2	582	2291.91	2291.91	2084.54	1006.54	0.47	0.47	0.47	2143.33	2291.91	1669.79	1	Tue Aug 06 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
6	1579	42	Male	2	self_employed	1494	3	388	927.72	1401.72	1643.31	1871.12	0.33	714.61	588.62	1538.06	1157.15	1677.16	1	Sun Nov 03 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
7	1923	42	Female		self_employed	1096	2	1666	15202.2	16059.34	15211.29	13798.82	0.36	0.36	857.5	286.07	15719.44	15349.75		Fri Nov 01 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
8	2048	72	Male		retired	1020	1	1	7006.93	7714.19	7859.74	11232.37	0.64	0.64	1299.64	439.26	7076.06	7755.98		Tue Sep 24 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
9	2009	46	Male		self_employed	623	2	317	10096.58	8519.53	6511.82	16314.17	0.27	0.27	443.13	5688.44	8563.84	5317.04		Fri Jul 12 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
10	2053	31	Male		salaried	1096	2	4110	1355.86	1355.86	1702.44	1126.13	714.51	121.09	714.51	359.44	1183.45	1857.42		Thu Dec 12 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
11	2295	40	Male	3	self_employed	1020	2	38	4957.95	4244.38	2168.53	1864.33	6912.29	4206.13	1887.3	1348.85	1823.16	2416.69		Tue Dec 31 2019 00:00:00 GMT+0000 (Coordinated Universal Time)


CREATE TABLE churn_prediction (
  "customer_id" BIGINT,
  "vintage" BIGINT,
  "age" BIGINT,
  "gender" VARCHAR,
  "dependents" DOUBLE,
  "occupation" VARCHAR,
  "city" DOUBLE,
  "customer_nw_category" BIGINT,
  "branch_code" BIGINT,
  "current_balance" DOUBLE,
  "previous_month_end_balance" DOUBLE,
  "average_monthly_balance_prevq" DOUBLE,
  "average_monthly_balance_prevq2" DOUBLE,
  "current_month_credit" DOUBLE,
  "previous_month_credit" DOUBLE,
  "current_month_debit" DOUBLE,
  "previous_month_debit" DOUBLE,
  "current_month_balance" DOUBLE,
  "previous_month_balance" DOUBLE,
  "churn" BIGINT,
  "last_transaction" TIMESTAMP
);