I have a data table that holds the data I need to forecast sales from a product over the next 10 years. The data includes 10 fields each with the number of products sold in each year. The data also includes a further 10 fields with the price per product in each of these 10 years (see illustrative structure below):
Product | Y1 sales | Y2 sales | Y3 sales | ... | Y1 price | Y2 price | Y3 price | ... |
X | 10 | 50 | 100 | $1 | $1.50 | $2.00 | ||
Y | 5 | 10 | 25 | $10 | $12 | $12.50 |
What would be the easiest / most efficient way of performing the generic calculation:
Y[n] revenue = Y[n] sales * Y[n] price
Hence creating 10 new columns each with the corresponding years revenue? I would like to avoid having to use the formula tool and having a separate expression for each as the actual data set I am working with has a significantly larger number of fields.
Any advice would be much appreciated
Solved! Go to Solution.
Hi @AndrewVogel ,
I used the Transpose and Crosstab tools to create the calculations. This will be future-proofed against additional rows.
This is the workflow:
Which gives the following results:
Hope this helps.
M
Great! Thanks @mceleavey