Weighted AVG Calculation

[pbi_wannabe_exp]

Hey all,

I have the following data table with many names but I only copied the table with 2 names now: setup.py and path.xyz. (date, name, loc_i, loc_d columns are originally in the table, and AGE, Weight, Weighted AVG are calculated.

date	name	loc_i	loc_d	AGE	Weight	Weighted AVG
24/01/22 13:20:06	setup.py	41	0	129.44	33	4271.664375
27/01/22 11:31:23	setup.py	1	1	126.52	1	126.5198727
28/01/22 08:54:20	setup.py	1	1	125.63	1	125.6289352
09/03/22 08:22:06	setup.py	2	2	85.65	2	171.3026389
05/04/22 07:57:04	setup.py	1	0	58.67	1	58.6687037
05/04/22 07:54:23	setup.py	1	0	58.67	1	58.67056713
27/01/22 09:45:36	setup.py	2	2	126.59	2	253.1866667
28/01/22 08:46:19	setup.py	2	2	125.63	2	251.2690046	123.6491
24/01/22 13:20:06	path.xyz	35	0	129.44	26	3365.55375
27/01/22 11:31:23	path.xyz	2	1	126.52	2	253.0397454
28/01/22 08:54:20	path.xyz	1	0	125.63	1	125.6289352
09/03/22 08:22:06	path.xyz	1	0	85.65	1	85.65131944
05/04/22 07:57:04	path.xyz	1	0	58.67	1	58.6687037
05/04/22 07:54:23	path.xyz	1	1	58.67	1	58.67056713
27/01/22 09:45:36	path.xyz	1	1	126.59	1	126.5933333
28/01/22 08:46:19	path.xyz	1	1	125.63	1	125.6345023
24/01/22 13:30:06	path.xyz	1	1	129.44	1	129.4374306
28/01/22 11:31:23	path.xyz	2	2	125.52	2	251.0397454
28/01/22 08:55:20	path.xyz	2	2	125.63	2	251.2564815	123.8763

Here you can see the formulas behind the calculated columns:

I would like to create the final calculation in PBI somehow (please note that my data table consists of more than 2 names - thousands).

Many thanks in advance!

[lbendlin · Accepted solution]

Wavg = divide(sumx('Table','Table'[AGE]*'Table'[Weight]),sumx('Table','Table'[Weight]))

see attached

[pbi_wannabe_exp]

Many thanks for your reply!! One thing I dont know is that how I can add weight calculation to the pbi. Only date, name, loc_i, loc_d is in the model. I understand how to add a calculated column measure in case of AGE and Weighted AVG, but what about Weight?

[lbendlin]

see attached