Dataset: Fraud Transactions Dataset

About this Dataset

Fraud Transactions Dataset

This dataset is fictional and is trying to simulate real life details. Any similarity to real life cases is purely coincidental.
It has the following columns.

trans_date_trans_time: The date and time of the transaction.

cc_num: credit card number.

merchant: Merchant who was getting paid.

category: In what area does that merchant deal.

amt: Amount of money in American Dollars.

first: first name of the card holder.

last: last name of the card holder.

gender: Gender of the cardholder.Just male and female!

street:Street of card holder residence

city:city of card holder residence

state:state of card holder residence

zip:ZIP code of card holder residence

lat:latitude of card holder

long:longitude of card holder

city_pop:Population of the city

job:trade of the card holder

dob:Date of birth of the card holder

trans_num: Transaction ID

unix_time: Unix time which is the time calculated since 1970 to today.

merch_lat: latitude of the merchant

merch_long:longitude of the merchant

is_fraud: Whether the transaction is fraud(1) or not(0)

Tables

Fraudtest

@kaggle.dermisfit_fraud_transactions_dataset.fraudtest

48.3 MB
555719 rows
23 columns


CREATE TABLE fraudtest (
  "unnamed_0" BIGINT,
  "trans_date_trans_time" TIMESTAMP,
  "cc_num" BIGINT,
  "merchant" VARCHAR,
  "category" VARCHAR,
  "amt" DOUBLE,
  "first" VARCHAR,
  "last" VARCHAR,
  "gender" VARCHAR,
  "street" VARCHAR,
  "city" VARCHAR,
  "state" VARCHAR,
  "zip" BIGINT,
  "lat" DOUBLE,
  "long" DOUBLE,
  "city_pop" BIGINT,
  "job" VARCHAR,
  "dob" TIMESTAMP,
  "trans_num" VARCHAR,
  "unix_time" BIGINT,
  "merch_lat" DOUBLE,
  "merch_long" DOUBLE,
  "is_fraud" BIGINT
);

Fraudtrain

@kaggle.dermisfit_fraud_transactions_dataset.fraudtrain

112.68 MB
1296675 rows
23 columns


CREATE TABLE fraudtrain (
  "unnamed_0" BIGINT,
  "trans_date_trans_time" TIMESTAMP,
  "cc_num" BIGINT,
  "merchant" VARCHAR,
  "category" VARCHAR,
  "amt" DOUBLE,
  "first" VARCHAR,
  "last" VARCHAR,
  "gender" VARCHAR,
  "street" VARCHAR,
  "city" VARCHAR,
  "state" VARCHAR,
  "zip" BIGINT,
  "lat" DOUBLE,
  "long" DOUBLE,
  "city_pop" BIGINT,
  "job" VARCHAR,
  "dob" TIMESTAMP,
  "trans_num" VARCHAR,
  "unix_time" BIGINT,
  "merch_lat" DOUBLE,
  "merch_long" DOUBLE,
  "is_fraud" BIGINT
);