Advance your Data & AI career with 50 days of live learning, dataviz contests, hands-on challenges, study groups & certifications and more!
Get registeredGet Fabric Certified for FREE during Fabric Data Days. Don't miss your chance! Request now
Hi,
I have a table with discontinous month data like below:
| Category | Product | Date | Price |
| Wellness | Shampoo | Jan 1 2019 | 100 |
| Wellness | Shampoo | Feb 1 2019 | 105 |
| Wellness | Shampoo | Apr 1 2019 | 120 |
| Nutrition | Energy bar | Jan 1 2019 | 200 |
| Nutrition | Energy bar | July 1 2019 | 205 |
| Nutrition | Energy bar | Mar 1 2020 | 225 |
I want to create a new calculated table with price coming for each month. E.g since March 2019 is not present for Shampoo in Wellness then it should bring previous value 105 of Feb 2019. Basically autofill data from Jan 2019 to March 2021 with previous avaiable values. Similarly for Energy it should fill 200 value for months from Feb 2019 to June 2019 then July 2019 value 205 fro July to Feb 2020. Basically an autofilled table with values from minimum available date in table to maximum available date in table.
Solved! Go to Solution.
@Anonymous
This sort of operation better be done in Power Query. Refer Attached working file below my signature.
Create a blank Query, go to the Advanced Editor, clear the existing code, and paste the codes give below and follow the steps.
⭕ Subscribe and learn Power BI from these videos
⚪ Website ⚪ LinkedIn ⚪ PBI User Group
@Anonymous
This sort of operation better be done in Power Query. Refer Attached working file below my signature.
Create a blank Query, go to the Advanced Editor, clear the existing code, and paste the codes give below and follow the steps.
⭕ Subscribe and learn Power BI from these videos
⚪ Website ⚪ LinkedIn ⚪ PBI User Group
Check out the November 2025 Power BI update to learn about new features.
Advance your Data & AI career with 50 days of live learning, contests, hands-on challenges, study groups & certifications and more!
| User | Count |
|---|---|
| 97 | |
| 74 | |
| 50 | |
| 48 | |
| 46 |