Re-calculating data in separate rows

[RfxSi]

Hi, not sure if this is the right sub-forum or not for this thread but at my office we're facing a unique problem, and this may take some time to explain so bear with me:

We have arranged our data into rows of 4 (that is, each 4 rows comprises one set of data). We have established that the first row in each set will be the base we use to divide the other rows by. However, we have thousands of sets of data like this, and doing it by hand would literally take months.

Here's a very dumbed down example of our rows:

Product X Company Y State Pricing Value Relative factor
Shoes Nike CA 50 1.000
Shoes Reebok WA 80 1.600
Shoes Adidas TX 100 2.000
Shoes Converse FL 60 1.200

EDIT: This "table" didn't turn out as I expected -- hopefully you can figure it out. If not let me know.

The relative factor is what we're trying to determine in each of these. We base it on the pricing value in row 1 for each set of data. In this case, for Nike, the relative factor is 1 (50/50). For Reebok, the relative factor is 1.600 because it's (80/50). For Adidas the relative factor is 2 (2/1), and so on.

Is there a way we can have this done automatically for each set (remember, set being each four rows) of data?

Thanks

[arthurbr]

Hi,
you can attach a zipped file of your sample data.
A little more explanation about what you are trying to do would be helpful

[Teethless mama]

Hi, not sure if this is the right sub-forum or not for this thread but at my office we're facing a unique problem, and this may take some time to explain so bear with me:

We have arranged our data into rows of 4 (that is, each 4 rows comprises one set of data). We have established that the first row in each set will be the base we use to divide the other rows by. However, we have thousands of sets of data like this, and doing it by hand would literally take months.

Here's a very dumbed down example of our rows:

Product X Company Y State Pricing Value Relative factor
Shoes Nike CA 50 1.000
Shoes Reebok WA 80 1.600
Shoes Adidas TX 100 2.000
Shoes Converse FL 60 1.200

EDIT: This "table" didn't turn out as I expected -- hopefully you can figure it out. If not let me know.

The relative factor is what we're trying to determine in each of these. We base it on the pricing value in row 1 for each set of data. In this case, for Nike, the relative factor is 1 (50/50). For Reebok, the relative factor is 1.600 because it's (80/50). For Adidas the relative factor is 2 (2/1), and so on.

Is there a way we can have this done automatically for each set (remember, set being each four rows) of data?

Thanks

Try this:

In E2: =D2/50

copy down as far as needed