I'm trying to create a formula that will tell me the number of orders that shipped after the order date. I was able to find a formula that spit out for me that there are 14 rows greater than 3/1/2019 but I need it to spit out that there are actually just 9 orders that are greater than B2 due to the duplicate order numbers in Column A. Anybody able to help? I don't know the right questions to ask Google to help me formulate this complicated calculation.

[TABLE="border: 0, cellpadding: 0, cellspacing: 0"]

[TD="width: 84"]Order Nbr[/TD]

[TD="width: 90"]Order Date[/TD]

[TD="width: 132"]Ship Date[/TD]

1647844

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:21[/TD]

1647844

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:21[/TD]

1648106

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:03[/TD]

1648067

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:01[/TD]

1648067

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:01[/TD]

1648067

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:01[/TD]

1648028

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 9:59[/TD]

1648003

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:06[/TD]

1648003

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:06[/TD]

1647930

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:14[/TD]

1647919

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:23[/TD]

1647919

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:23[/TD]

1647830

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:18[/TD]

1647815

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/4/19 10:11[/TD]

1647670

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:18[/TD]

1647669

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:20[/TD]

1647655

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:21[/TD]

1647624

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:24[/TD]

1647624

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:24[/TD]

1647593

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:25[/TD]

1647575

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:17[/TD]

1647573

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:27[/TD]

1647566

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:29[/TD]

1647537

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:30[/TD]

1647498

[/td]

[TD="align: right"]3/1/2019[/TD]

[TD="align: right"]3/1/19 15:28[/TD]

[/TABLE]