Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
Hi all,
First post here.
I’ve gathered the forum and part of Google. I've found similar topics, but I cannot make it work, I’d be grateful for your help.
I have an hourly time series in Power BI ('Date' and 'Price').
I need to fill a column ('Daily average') REPEATING each ROW the average of the 24h of that day, the key challenge is to change the average when the day changes.
I’ve been trying different approaches with AVERAGEX, VALUES… but I cannot get to find the solution.
It’s easier to see in this example from Excel:
The 'Daily average' is the average of the 24 numbers in column 'Price'.
I'm completely stuck. How could I do it in Power BI (DAX)?
Thank you very much.
Best regards,
Enrique
Solved! Go to Solution.
@edejuan Soooorry, a huge mistake!!
The correct formula:
Hi @BeaBF
Sure! Here you have. Thanks!
Date | Price | Daily average |
19/05/2022 0:00 | 179,94 | 192,12 |
19/05/2022 1:00 | 176,27 | 192,12 |
19/05/2022 2:00 | 177,98 | 192,12 |
19/05/2022 3:00 | 185,06 | 192,12 |
19/05/2022 4:00 | 222,33 | 192,12 |
19/05/2022 5:00 | 235,7 | 192,12 |
19/05/2022 6:00 | 230,01 | 192,12 |
19/05/2022 7:00 | 215,94 | 192,12 |
19/05/2022 8:00 | 198,22 | 192,12 |
19/05/2022 9:00 | 171,59 | 192,12 |
19/05/2022 10:00 | 167,02 | 192,12 |
19/05/2022 11:00 | 163,7 | 192,12 |
19/05/2022 12:00 | 161,18 | 192,12 |
19/05/2022 13:00 | 157,14 | 192,12 |
19/05/2022 14:00 | 157,14 | 192,12 |
19/05/2022 15:00 | 162,1 | 192,12 |
19/05/2022 16:00 | 164,54 | 192,12 |
19/05/2022 17:00 | 182 | 192,12 |
19/05/2022 18:00 | 220,43 | 192,12 |
19/05/2022 19:00 | 236,21 | 192,12 |
19/05/2022 20:00 | 226,03 | 192,12 |
19/05/2022 21:00 | 213,31 | 192,12 |
19/05/2022 22:00 | 211,1 | 192,12 |
19/05/2022 23:00 | 195,98 | 192,12 |
20/05/2022 0:00 | 189,56 | 201,33 |
20/05/2022 1:00 | 188 | 201,33 |
20/05/2022 2:00 | 189,56 | 201,33 |
20/05/2022 3:00 | 208,62 | 201,33 |
20/05/2022 4:00 | 226,51 | 201,33 |
20/05/2022 5:00 | 230,05 | 201,33 |
20/05/2022 6:00 | 230,72 | 201,33 |
20/05/2022 7:00 | 224 | 201,33 |
20/05/2022 8:00 | 204,97 | 201,33 |
20/05/2022 9:00 | 200,28 | 201,33 |
20/05/2022 10:00 | 195 | 201,33 |
20/05/2022 11:00 | 190,07 | 201,33 |
20/05/2022 12:00 | 180,18 | 201,33 |
20/05/2022 13:00 | 174 | 201,33 |
20/05/2022 14:00 | 180,18 | 201,33 |
20/05/2022 15:00 | 190 | 201,33 |
20/05/2022 16:00 | 214,92 | 201,33 |
20/05/2022 17:00 | 225,63 | 201,33 |
20/05/2022 18:00 | 226,87 | 201,33 |
20/05/2022 19:00 | 218,03 | 201,33 |
20/05/2022 20:00 | 205,27 | 201,33 |
20/05/2022 21:00 | 190,17 | 201,33 |
20/05/2022 22:00 | 180 | 201,33 |
20/05/2022 23:00 | 169,27 | 201,33 |
21/05/2022 0:00 | 169,26 | 180,57 |
21/05/2022 1:00 | 165,87 | 180,57 |
21/05/2022 2:00 | 164,84 | 180,57 |
21/05/2022 3:00 | 164,94 | 180,57 |
21/05/2022 4:00 | 164,84 | 180,57 |
21/05/2022 5:00 | 164,85 | 180,57 |
21/05/2022 6:00 | 166,54 | 180,57 |
21/05/2022 7:00 | 172,97 | 180,57 |
21/05/2022 8:00 | 178,82 | 180,57 |
21/05/2022 9:00 | 174,89 | 180,57 |
21/05/2022 10:00 | 170,57 | 180,57 |
21/05/2022 11:00 | 167,45 | 180,57 |
21/05/2022 12:00 | 164,67 | 180,57 |
21/05/2022 13:00 | 161,55 | 180,57 |
21/05/2022 14:00 | 159,33 | 180,57 |
21/05/2022 15:00 | 164,84 | 180,57 |
21/05/2022 16:00 | 171,58 | 180,57 |
21/05/2022 17:00 | 201 | 180,57 |
21/05/2022 18:00 | 219,32 | 180,57 |
21/05/2022 19:00 | 228,11 | 180,57 |
21/05/2022 20:00 | 227,05 | 180,57 |
21/05/2022 21:00 | 216,42 | 180,57 |
21/05/2022 22:00 | 214,57 | 180,57 |
21/05/2022 23:00 | 179,4 | 180,57 |
(I'm having problems with posting, maybe my wifi, I've replied a couple of times but don't see my reply)
Thanks again
@edejuan You can calculate a column like this:
Hi @BeaBF
Thank you very much for your formula.
I'm afraid it doesn't work, it returns this:
Date | Price | Daily average (expected result) | BeaBF |
19/05/2022 0:00 | 179,94 | 192,12 | 65,94 |
19/05/2022 1:00 | 176,27 | 192,12 | 65,94 |
19/05/2022 2:00 | 177,98 | 192,12 | 65,94 |
19/05/2022 3:00 | 185,06 | 192,12 | 65,94 |
19/05/2022 4:00 | 222,33 | 192,12 | 65,94 |
19/05/2022 5:00 | 235,7 | 192,12 | 65,94 |
19/05/2022 6:00 | 230,01 | 192,12 | 65,94 |
19/05/2022 7:00 | 215,94 | 192,12 | 65,94 |
19/05/2022 8:00 | 198,22 | 192,12 | 65,94 |
19/05/2022 9:00 | 171,59 | 192,12 | 65,94 |
19/05/2022 10:00 | 167,02 | 192,12 | 65,94 |
19/05/2022 11:00 | 163,7 | 192,12 | 65,94 |
19/05/2022 12:00 | 161,18 | 192,12 | 65,94 |
19/05/2022 13:00 | 157,14 | 192,12 | 65,94 |
19/05/2022 14:00 | 157,14 | 192,12 | 65,94 |
19/05/2022 15:00 | 162,1 | 192,12 | 65,94 |
19/05/2022 16:00 | 164,54 | 192,12 | 65,94 |
19/05/2022 17:00 | 182 | 192,12 | 65,94 |
19/05/2022 18:00 | 220,43 | 192,12 | 65,94 |
19/05/2022 19:00 | 236,21 | 192,12 | 65,94 |
19/05/2022 20:00 | 226,03 | 192,12 | 65,94 |
19/05/2022 21:00 | 213,31 | 192,12 | 65,94 |
19/05/2022 22:00 | 211,1 | 192,12 | 65,94 |
19/05/2022 23:00 | 195,98 | 192,12 | 65,94 |
20/05/2022 0:00 | 189,56 | 201,33 | 63,94 |
20/05/2022 1:00 | 188 | 201,33 | 63,94 |
20/05/2022 2:00 | 189,56 | 201,33 | 63,94 |
20/05/2022 3:00 | 208,62 | 201,33 | 63,94 |
20/05/2022 4:00 | 226,51 | 201,33 | 63,94 |
20/05/2022 5:00 | 230,05 | 201,33 | 63,94 |
20/05/2022 6:00 | 230,72 | 201,33 | 63,94 |
20/05/2022 7:00 | 224 | 201,33 | 63,94 |
20/05/2022 8:00 | 204,97 | 201,33 | 63,94 |
20/05/2022 9:00 | 200,28 | 201,33 | 63,94 |
20/05/2022 10:00 | 195 | 201,33 | 63,94 |
20/05/2022 11:00 | 190,07 | 201,33 | 63,94 |
20/05/2022 12:00 | 180,18 | 201,33 | 63,94 |
20/05/2022 13:00 | 174 | 201,33 | 63,94 |
20/05/2022 14:00 | 180,18 | 201,33 | 63,94 |
20/05/2022 15:00 | 190 | 201,33 | 63,94 |
20/05/2022 16:00 | 214,92 | 201,33 | 63,94 |
20/05/2022 17:00 | 225,63 | 201,33 | 63,94 |
20/05/2022 18:00 | 226,87 | 201,33 | 63,94 |
20/05/2022 19:00 | 218,03 | 201,33 | 63,94 |
20/05/2022 20:00 | 205,27 | 201,33 | 63,94 |
20/05/2022 21:00 | 190,17 | 201,33 | 63,94 |
20/05/2022 22:00 | 180 | 201,33 | 63,94 |
20/05/2022 23:00 | 169,27 | 201,33 | 63,94 |
Hi @BeaBF , thanks again for your patiente.
This is my formula
Hi @BeaBF ,
Here's a screenshot. I've overlayed in red the expected result.
I'm scratching my head. I don't understand.
When done in a small dataset, your formula works OK 🙂
Buen when I apply it to the 65k rows model, it doesn't.
Mystery!
Yes.
Totally lost here...
Hi @BeaBF, I've sent you a Wetransfer link via private message.
Thanks for your help!!!
@edejuan Soooorry, a huge mistake!!
The correct formula:
Sure!
Sorry! There you have.
Thanks!!
Date | Price | Daily average |
19/05/2022 0:00 | 179,94 | 192,12 |
19/05/2022 1:00 | 176,27 | 192,12 |
19/05/2022 2:00 | 177,98 | 192,12 |
19/05/2022 3:00 | 185,06 | 192,12 |
19/05/2022 4:00 | 222,33 | 192,12 |
19/05/2022 5:00 | 235,7 | 192,12 |
19/05/2022 6:00 | 230,01 | 192,12 |
19/05/2022 7:00 | 215,94 | 192,12 |
19/05/2022 8:00 | 198,22 | 192,12 |
19/05/2022 9:00 | 171,59 | 192,12 |
19/05/2022 10:00 | 167,02 | 192,12 |
19/05/2022 11:00 | 163,7 | 192,12 |
19/05/2022 12:00 | 161,18 | 192,12 |
19/05/2022 13:00 | 157,14 | 192,12 |
19/05/2022 14:00 | 157,14 | 192,12 |
19/05/2022 15:00 | 162,1 | 192,12 |
19/05/2022 16:00 | 164,54 | 192,12 |
19/05/2022 17:00 | 182 | 192,12 |
19/05/2022 18:00 | 220,43 | 192,12 |
19/05/2022 19:00 | 236,21 | 192,12 |
19/05/2022 20:00 | 226,03 | 192,12 |
19/05/2022 21:00 | 213,31 | 192,12 |
19/05/2022 22:00 | 211,1 | 192,12 |
19/05/2022 23:00 | 195,98 | 192,12 |
20/05/2022 0:00 | 189,56 | 201,33 |
20/05/2022 1:00 | 188 | 201,33 |
20/05/2022 2:00 | 189,56 | 201,33 |
20/05/2022 3:00 | 208,62 | 201,33 |
20/05/2022 4:00 | 226,51 | 201,33 |
20/05/2022 5:00 | 230,05 | 201,33 |
20/05/2022 6:00 | 230,72 | 201,33 |
20/05/2022 7:00 | 224 | 201,33 |
20/05/2022 8:00 | 204,97 | 201,33 |
20/05/2022 9:00 | 200,28 | 201,33 |
20/05/2022 10:00 | 195 | 201,33 |
20/05/2022 11:00 | 190,07 | 201,33 |
20/05/2022 12:00 | 180,18 | 201,33 |
20/05/2022 13:00 | 174 | 201,33 |
20/05/2022 14:00 | 180,18 | 201,33 |
20/05/2022 15:00 | 190 | 201,33 |
20/05/2022 16:00 | 214,92 | 201,33 |
20/05/2022 17:00 | 225,63 | 201,33 |
20/05/2022 18:00 | 226,87 | 201,33 |
20/05/2022 19:00 | 218,03 | 201,33 |
20/05/2022 20:00 | 205,27 | 201,33 |
20/05/2022 21:00 | 190,17 | 201,33 |
20/05/2022 22:00 | 180 | 201,33 |
20/05/2022 23:00 | 169,27 | 201,33 |
Sure @BeaBF !
There you have.
Thanks!!
Date | Price | Daily average |
19/05/2022 0:00 | 179,94 | 192,12 |
19/05/2022 1:00 | 176,27 | 192,12 |
19/05/2022 2:00 | 177,98 | 192,12 |
19/05/2022 3:00 | 185,06 | 192,12 |
19/05/2022 4:00 | 222,33 | 192,12 |
19/05/2022 5:00 | 235,7 | 192,12 |
19/05/2022 6:00 | 230,01 | 192,12 |
19/05/2022 7:00 | 215,94 | 192,12 |
19/05/2022 8:00 | 198,22 | 192,12 |
19/05/2022 9:00 | 171,59 | 192,12 |
19/05/2022 10:00 | 167,02 | 192,12 |
19/05/2022 11:00 | 163,7 | 192,12 |
19/05/2022 12:00 | 161,18 | 192,12 |
19/05/2022 13:00 | 157,14 | 192,12 |
19/05/2022 14:00 | 157,14 | 192,12 |
19/05/2022 15:00 | 162,1 | 192,12 |
19/05/2022 16:00 | 164,54 | 192,12 |
19/05/2022 17:00 | 182 | 192,12 |
19/05/2022 18:00 | 220,43 | 192,12 |
19/05/2022 19:00 | 236,21 | 192,12 |
19/05/2022 20:00 | 226,03 | 192,12 |
19/05/2022 21:00 | 213,31 | 192,12 |
19/05/2022 22:00 | 211,1 | 192,12 |
19/05/2022 23:00 | 195,98 | 192,12 |
20/05/2022 0:00 | 189,56 | 201,33 |
20/05/2022 1:00 | 188 | 201,33 |
20/05/2022 2:00 | 189,56 | 201,33 |
20/05/2022 3:00 | 208,62 | 201,33 |
20/05/2022 4:00 | 226,51 | 201,33 |
20/05/2022 5:00 | 230,05 | 201,33 |
20/05/2022 6:00 | 230,72 | 201,33 |
20/05/2022 7:00 | 224 | 201,33 |
20/05/2022 8:00 | 204,97 | 201,33 |
20/05/2022 9:00 | 200,28 | 201,33 |
20/05/2022 10:00 | 195 | 201,33 |
20/05/2022 11:00 | 190,07 | 201,33 |
20/05/2022 12:00 | 180,18 | 201,33 |
20/05/2022 13:00 | 174 | 201,33 |
20/05/2022 14:00 | 180,18 | 201,33 |
20/05/2022 15:00 | 190 | 201,33 |
20/05/2022 16:00 | 214,92 | 201,33 |
20/05/2022 17:00 | 225,63 | 201,33 |
20/05/2022 18:00 | 226,87 | 201,33 |
20/05/2022 19:00 | 218,03 | 201,33 |
20/05/2022 20:00 | 205,27 | 201,33 |
20/05/2022 21:00 | 190,17 | 201,33 |
20/05/2022 22:00 | 180 | 201,33 |
20/05/2022 23:00 | 169,27 | 201,33 |
Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
42 | |
26 | |
22 | |
11 | |
8 |
User | Count |
---|---|
75 | |
50 | |
47 | |
17 | |
17 |