Files

Transactions.csv

1	Id	Name	Tran_Date	Tran_Amt	Tran_Code	Tran_Desc	SIC_Code					Id	Name	State	Country	Gender	Income
2	1001	Tim	1/29/2019	1453	600	Airlines	2334					1001	Tim	PA	USA	M	60000
3	1001	Tim	1/30/2019	16384	600	Restaurant	4345					1002	Dana	DE	USA	M	87000
4	1001	Tim	1/31/2019	48569	600	Transportation	2445					1003	Mike	AL	USA	M	80738
5	1001	Tim	2/1/2019	4674	600	Movies	3546					1004	Pete	CA	USA	M	45999
6	1001	Tim	2/2/2019	4456	600	Entertainment	4454					1005	Paul	CA	USA	M	54894
7	1001	Tim	2/3/2019	44	600		4565					1006	Jon	DE	USA	M	76554
8	1001	Tim	2/4/2019	45	600	Tickets	4534					1007	Payal	AP	India	F	12334
9	1001	Tim	2/5/2019	12	600	Holiday	3545
10	1001	Tim	2/4/2019	45	400	Tickets	4534
11	1001	Tim	2/5/2019	12	400	Holiday	3545
12	1002	Dana	2/4/2019	2254	600	Airlines	2334
13	1002	Dana	2/5/2019	335	600	Restaurant	4345
14	1003	Mike	2/10/2019	33445	600	Restaurant	4345
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19	Id	Name	Tran_Date	Tran_Amt	Tran_Code	Tran_Desc	SIC_Code
20	1004	Pete	2/5/2019	34.5	600	Holiday	3545
21	1004	Pete	2/4/2019	45.6	600	Airlines	2334
22	1005	Paul	2/5/2019	566	600	Restaurant	4345