Regards to transforming data prior to joining with another data set.
Attached are 2 different samples of data. Both are in similar format, and have plenty of same columns.
The price list is where the bulk of what I am going to use will come from. It is the full inventory for a site. the total number of units, number of occupied, number of vacant etc... It is rolled up in to a single row for each unit type at every site. The vacant unit sample is only of those units that are not occupied, and it gets broken out where every single unoccupied unit gets it's own row. This is where things are getting complicated. From the Vacant unit file I just need the info from the daysvacant column, since there is say 7 rows of 5x5 drive ups at the same site all with different amounts of 'daysvacant' I was thinking the best option would be to a min, max, and med, columns for 'daysvacant'. The bigger aspect is i am not sure how to counter the multiple rows of the same units, and have it be able to cooperate with the price list that has single rows for single unit types.
Any suggestion or direction is greatly appreciated!
- 10.6K All Categories
- 13 Getting Started in the Community
- 29 Beastmode & Analytics
- 2.1K Data Platform & Data Science
- 59 Domo Everywhere
- 2.7K Charting
- 2.4K Ideas Exchange
- 1.3K Connectors
- 362 Workbench
- 300 Use Cases & Best Practices
- 499 APIs
- 118 Apps
- 48 News
- 753 Onboarding
- 1.1K 日本支部
- 4 Private Company Board