Intermedius
New Member
- Joined
- Oct 12, 2012
- Messages
- 32
Hello,
I am trying to figure out a two lookup that will lookup two columns of data, one with an exact match and the other with an approximate match. i.e.
My issue, is that when i deal with thousands of Materials, with different scale sets, I pickup the wrong scales with Scale lookup 1. SO My objective is to pickup the approximate scale according to that specific material.
Scale Lookup 1 =INDEX($I$5:$I$40,MATCH(D6,$I$5:$I$40,1))
Scale Lookup 2 = =INDEX($I$5:$I$40,MATCH(D5,$I$5:$I$40,1),MATCH(B5,$J$5:$J$40,0))
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My scales can be seen here in matrix form, but I have them in columns side by side for my vertical lookup
<tbody>
</tbody>
I am trying to figure out a two lookup that will lookup two columns of data, one with an exact match and the other with an approximate match. i.e.
My issue, is that when i deal with thousands of Materials, with different scale sets, I pickup the wrong scales with Scale lookup 1. SO My objective is to pickup the approximate scale according to that specific material.
Scale Lookup 1 =INDEX($I$5:$I$40,MATCH(D6,$I$5:$I$40,1))
Scale Lookup 2 = =INDEX($I$5:$I$40,MATCH(D5,$I$5:$I$40,1),MATCH(B5,$J$5:$J$40,0))
Pstng Date | Material | Purchase Order | PO Quantity | Scale Lookup 1 | Scale Lookup 2 | Scale | Material | ||
6/11/2018 | 67274006 | 1235 | 423 | 300 | #REF! | 100 | 67458258 | ||
6/8/2018 | 67291470 | 1236 | 7500 | 5000 | #REF! | 150 | 67458258 | ||
6/6/2018 | 84170740 | 1270 | 500 | 500 | #N/A | 200 | 67458258 | ||
5/26/2018 | 67274072 | 1271 | 1000 | 1000 | #REF! | 250 | 67458258 | ||
5/22/2018 | 67274072 | 1289 | 1000 | 1000 | #REF! | 300 | 67458258 | ||
5/22/2018 | 67376093 | 1312 | 2000 | 1000 | #N/A | 500 | 67458258 | ||
5/17/2018 | 84170957 | 1314 | 600 | 500 | #REF! | 1000 | 67458258 | ||
5/16/2018 | 67363858 | 1317 | 800 | 500 | #N/A | 1500 | 67458258 | ||
5/15/2018 | 67458258 | 1345 | 500 | 500 | 500 | 100 | 67274006 | ||
5/9/2018 | 67274072 | 1367 | 364 | 300 | #REF! | 150 | 67274006 | ||
5/9/2018 | 67274072 | 1368 | 364 | 300 | #REF! | 200 | 67274006 | ||
4/27/2018 | 67458258 | 1417 | 1200 | 1000 | 1000 | 250 | 67274006 | ||
4/27/2018 | 84170740 | 1418 | 500 | 500 | #N/A | 300 | 67274006 | ||
4/27/2018 | 84170957 | 1419 | 200 | 200 | #REF! | 500 | 67274006 | ||
4/21/2018 | 67274072 | 1422 | 500 | 500 | #REF! | 1000 | 67274006 | ||
4/12/2018 | 84170957 | 1470 | 500 | 500 | #REF! | 100 | 67274072 | ||
4/12/2018 | 84170957 | 1471 | 500 | 500 | #REF! | 150 | 67274072 | ||
4/10/2018 | 67274006 | 1472 | 423 | 300 | #REF! | 200 | 67274072 | ||
4/4/2018 | 67274072 | 1477 | 500 | 500 | #REF! | 250 | 67274072 | ||
4/4/2018 | 67291470 | 1489 | 10720 | 10000 | #REF! | 300 | 67274072 | ||
4/4/2018 | 84170715 | 1490 | 200 | 200 | #N/A | 500 | 67274072 | ||
4/4/2018 | 84170715 | 1491 | 200 | 200 | #N/A | 1000 | 67274072 | ||
3/28/2018 | 67274006 | 1525 | 423 | 300 | #REF! | 1500 | 67274072 | ||
3/23/2018 | 67458258 | 1528 | 600 | 500 | 500 | 1000 | 67291470 | ||
3/22/2018 | 67363858 | 1535 | 790 | 500 | #N/A | 5000 | 67291470 | ||
3/19/2018 | 67274072 | 1582 | 139 | 100 | #REF! | 10000 | 67291470 | ||
3/19/2018 | 67274072 | 1583 | 395 | 300 | #REF! | 15000 | 67291470 | ||
3/19/2018 | 67274072 | 1584 | 395 | 300 | #REF! | 20000 | 67291470 | ||
3/15/2018 | 84170957 | 1592 | 400 | 300 | #REF! | 30000 | 67291470 | ||
3/15/2018 | 84170957 | 1593 | 400 | 300 | #REF! | 100 | 84170957 | ||
150 | 84170957 | ||||||||
200 | 84170957 | ||||||||
250 | 84170957 | ||||||||
300 | 84170957 | ||||||||
500 | 84170957 | ||||||||
1000 | 84170957 |
<tbody>
</tbody>
My scales can be seen here in matrix form, but I have them in columns side by side for my vertical lookup
SKU | Scale 1 | Scale 2 | Scale 3 | Scale 4 | Scale 5 | Scale 6 | Scale 7 | Scale 8 | Scale 9 |
67458258 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | 1500 |
67274006 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | |
67274072 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | 1500 |
67291470 | 1000 | 1000 | 5000 | 10000 | 15000 | 20000 | 30000 | ||
67363858 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | 1500 |
67376093 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | 1500 |
84170372 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | |
84170715 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | |
84170733 | 500 | 500 | 1000 | 2000 | 3000 | 5000 | 7000 | 9000 | |
84170740 | 500 | 500 | 1000 | 2000 | 3000 | 5000 | 7000 | 9000 | |
84170781 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | |
84170828 | 100 | 100 | 250 | 500 | 1000 | 2000 | 6000 | 9000 | |
84170957 | 100 | 100 | 150 | 200 | 250 | 300 | 500 | 1000 | |
84171143 | 100 | 100 | 250 | 500 | 1000 | 2000 | 6000 | 9000 |
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