Maggie Barr
Board Regular
- Joined
- Jan 28, 2014
- Messages
- 188
Hello, and thank you in advance for taking the time to look over this request.
I am working on a PC in excel 2013, and I have a large data set/sets that I need to flag (or produce in a separate sheet) data that does not fit into several categories. I have a list of bird species with observation dates and breeding codes. From that, I need two things, first to flag (or produce a separate sheet of) records of certain codes that fall outside the breeding windows and, second, all records that have breeding codes that are not likely appropriate for the bird. I am trying to figure out what method would best/most efficiently produce the results I need.
I have three spreadsheets. The first one is where each species has its own breeding window, Column A is the species, Column B is the window (month/day – month/day). The second one is a bit trickier, in that it has Column A is the species list, while the breeding codes are in Row 2, with all the acceptable numbers for the codes in the cells for each species. The third one, the test data, I need to filter/vba/querry out species with the breeding codes of S, H, S7, M, P, and T that have those codes outside the breeding window from sheet1, and in another filter/vba/querry, filter out all the species that have codes in sheet 3 that are numbered a 3 or a 4 in our code sheet, sheet 2. This I think, would be a two tiered filtering process to produce two sets of data for review. If anyone can provide any help or guidance as to what they believe the best method for me to pursue, I would greatly appreciate it. I am not a VBA writer unfortunately, and I do not think running filters in tables will be efficient. I am hoping to find a way to do this in excel since our data is already there, and we will be doing this quite often. Below is an example of what the data looks like.
Thank you in advance for any help you may be able to provide.
Sincerely,
Maggie
Sheet one looks like:
<tbody>
</tbody>
Sheet 2 Looks like:
<tbody>
[TD="colspan: 2"] Possible
[/TD]
[TD="colspan: 8"] Probable
[/TD]
[TD="colspan: 12"] Confirmed
[/TD]
</tbody>
The test Data looks like this:
<tbody>
</tbody>
I am working on a PC in excel 2013, and I have a large data set/sets that I need to flag (or produce in a separate sheet) data that does not fit into several categories. I have a list of bird species with observation dates and breeding codes. From that, I need two things, first to flag (or produce a separate sheet of) records of certain codes that fall outside the breeding windows and, second, all records that have breeding codes that are not likely appropriate for the bird. I am trying to figure out what method would best/most efficiently produce the results I need.
I have three spreadsheets. The first one is where each species has its own breeding window, Column A is the species, Column B is the window (month/day – month/day). The second one is a bit trickier, in that it has Column A is the species list, while the breeding codes are in Row 2, with all the acceptable numbers for the codes in the cells for each species. The third one, the test data, I need to filter/vba/querry out species with the breeding codes of S, H, S7, M, P, and T that have those codes outside the breeding window from sheet1, and in another filter/vba/querry, filter out all the species that have codes in sheet 3 that are numbered a 3 or a 4 in our code sheet, sheet 2. This I think, would be a two tiered filtering process to produce two sets of data for review. If anyone can provide any help or guidance as to what they believe the best method for me to pursue, I would greatly appreciate it. I am not a VBA writer unfortunately, and I do not think running filters in tables will be efficient. I am hoping to find a way to do this in excel since our data is already there, and we will be doing this quite often. Below is an example of what the data looks like.
Thank you in advance for any help you may be able to provide.
Sincerely,
Maggie
Sheet one looks like:
Species | Safe Date Window | |
Species 1 | 1/25 - 8/1 | |
Species 2 | 3/1 - 7/1 | |
Species 3 | 3/1 - 8/25 | |
Species 4 | 3/1 - 11/1 | |
Species 5 | 3/15 - 7/25 | |
Species 6 | 3/16 - 7/31 | |
Species 7 | 3/25 - 7/1 | |
Species 8 | 3/25 - 7/15 | |
Species 9 | 4/1 - 7/1 | |
Species 10 | 4/1 - 7/20 | |
Species 11 | 4/1 - 8/1 | |
Species 12 | 4/1 - 8/5 |
<tbody>
</tbody>
Sheet 2 Looks like:
Species | ||||||||||||||||||||||
H | S | S7 | M | P | T | C | N | A | B | PE | CN | NB | DD | UN | ON | FL | CF | FY | FS | NE | NY | |
Species 1 | 4 | 4 | 4 | 4 | 3 | 2 | 2 | 4 | 4 | 4 | 3 | 4 | 4 | 4 | 4 | 4 | 3 | 3 | 3 | 4 | 4 | 4 |
Species 2 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 1 | 3 | 4 | 4 | 2 | 3 | 4 | 4 | 4 | 4 | 1 | 1 | 2 | 3 | 3 |
Species 3 | 3 | 4 | 4 | 4 | 4 | 3 | 3 | 2 | 2 | 2 | 3 | 4 | 3 | 4 | 4 | 1 | 3 | 3 | 3 | 4 | 1 | 2 |
Species 4 | 1 | 4 | 4 | 4 | 2 | 4 | 4 | 1 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 1 | 4 | 1 | 1 | 4 | 3 | 3 |
Species 5 | 2 | 2 | 2 | 3 | 2 | 3 | 3 | 3 | 3 | 4 | 3 | 1 | 1 | 4 | 4 | 1 | 3 | 2 | 1 | 2 | 1 | 1 |
Species 6 | 1 | 4 | 4 | 4 | 2 | 4 | 4 | 1 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 1 | 4 | 1 | 1 | 4 | 3 | 3 |
Species 7 | 3 | 3 | 3 | 4 | 3 | 3 | 3 | 3 | 3 | 4 | 4 | 3 | 3 | 4 | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
Species 8 | 1 | 4 | 4 | 4 | 2 | 2 | 2 | 3 | 2 | 4 | 3 | 4 | 4 | 3 | 3 | 1 | 1 | 4 | 4 | 4 | 2 | 3 |
Species 9 | 1 | 4 | 4 | 4 | 2 | 4 | 4 | 1 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 1 | 4 | 1 | 1 | 4 | 3 | 3 |
Species 10 | 2 | 4 | 4 | 4 | 2 | 2 | 1 | 1 | 2 | 4 | 3 | 1 | 1 | 4 | 4 | 1 | 1 | 3 | 1 | 2 | 3 | 1 |
Species 11 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 1 | 4 | 3 | 1 | 2 | 4 | 4 | 2 | 2 | 1 | 1 | 4 | 1 | 1 |
Species 12 | 3 | 4 | 4 | 4 | 3 | 4 | 3 | 3 | 4 | 4 | 4 | 3 | 3 | 4 | 4 | 3 | 3 | 4 | 3 | 4 | 3 | 3 |
<tbody>
[TD="colspan: 2"] Possible
[/TD]
[TD="colspan: 8"] Probable
[/TD]
[TD="colspan: 12"] Confirmed
[/TD]
</tbody>
The test Data looks like this:
COMMON NAME | BREEDING CODE | OBSERVATION DATE |
Species 1 | P | 6/1/2017 |
Species 2 | S | 6/1/2017 |
Species 3 | S | 6/1/2017 |
Species 4 | S | 6/1/2017 |
Species 5 | C | 6/1/2017 |
Species 6 | C | 6/1/2017 |
Species 7 | C | 6/1/2017 |
Species 8 | C | 6/1/2017 |
Species 9 | C | 6/1/2017 |
Species 10 | S | 6/1/2017 |
Species 11 | S | 6/1/2017 |
Species 12 | H | 6/1/2017 |
Species 13 | S | 6/1/2017 |
Species 14 | M | 6/1/2017 |
Species 15 | H | 6/1/2017 |
Species 16 | H | 6/1/2017 |
Species 17 | H | 6/1/2017 |
Species 18 | H | 6/1/2017 |
Species 19 | S | 6/1/2017 |
Species 20 | S | 6/1/2017 |
Species 21 | NY | 6/1/2017 |
Species 22 | H | 6/1/2017 |
Species 23 | F | 6/1/2017 |
Species 24 | FY | 6/1/2017 |
Species 25 | S | 6/1/2017 |
Species 26 | S | 6/1/2017 |
<tbody>
</tbody>