I have a large dataset of about 20,000 lines. I need to remove the duplicate rows while keeping the one row with the maximum value. For example, I have ten rows of Gordon with birthdays in every month, and ten rows of Jewel with birthdays in every month. A total of 24 lines. I want to remove 11 duplicate Gordons and 11 duplicate Jewels and only keep the ones with the highest birthday.
I tried using SUBTOTAL, COUNTIFS, and ADVANCED FILTER, all in failed efforts.
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I've been Googling around this problem for hours and haven't found a solution that suits my needs.
I have a large data set with agent activities and the total time in seconds each activity lasts. I'm pulling this together in a matrix, to display agent names on the left and the start date of each week across the top like so:
This is working as intended (I've used a measure to convert the seconds into hours) but I need the average of the displayed weeks as another column, or to replace the Total column.
I've tried solutions involving DAX measures but none are applicable, likely because I'm using a custom column (WeekStart) to roll up my numbers into weeks. Adding more complexity is I have 2 filters on the matrix; one to exclude any weeks older that 5 weeks in the past and another to exclude any future weeks.
In Excel I'd just add another column next to the table, averaging the 5 cells to the left of it. I could add it to the data table with a SUMIFS checking the Activity date is within the week range and dividing the result by 5. I can't do either of these in PowerBI and I'm new to the software so I'm at a loss as to how to do this.
I am trying to create a "meetingroom occupancy" matrix in Power BI. The raw data contains bookings per day per Room. The maximum daily available time per room is 12 hours. I have created a Date Dimension Table for the dates.
I have tried to change datatypes, added the available time column in the query editor, added the available time as DAX column and as calculated measure, but all with no success. I have changed the available time for Room B to 1, and the result of the Subtotal was 13, so it looks like subtotals is only summing unique values, but I do not know how to solve this.
Could someone please explain to me what is happening and how I could solve this?
The input data is as follows:
And my Date_Dimension is as follows:
This is the current and desired result:
This is my input file, having months of data.
Now I want to create this matrix in the PBIX, with 12 months of trailing data from a date slicer.
That is I will have a date slicer and I want to see the previous 12 months of data from the selected month.
For example, if I select Jan'21 in my slicer I want to have data from Jan'21 to Feb'20.
I watched some of the videos, but those videos focused on measures or rolling average or rolling total, in my case I want columns.
I have no idea how to implement this in Power BI. Thanks.
EDIT:- The Actual Exp and Actual Min column also have N/A for various months.
I'm looking to add a column to my PowerQuery data which will count how many of 5 cells in the row are greater than zero. Example data below with end result:
I could do this with lots of If statements but I need to be able to expand my number of columns in the future.
I think this should do it. Add a column with:
List.Count(List.RemoveMatchingItems(Record.FieldValues(_),{0}))
e.g.:
I have this dataset containing world bilateral trade data for a few years.
I would like to determine which goods were the most exported ones in the timespan considered by the dataset.
The dataset is composed by the following variables:
"year"
"hs2", containing a two-digit number that tells which good is exported
"exp_val", giving the value of the export in a certain year, for that good
"exp_qty", giving the exported quantity of the good in a certain year
Basically, I would like to get the total sum of the quantity exported for a certain good, so an output like
hs2 exp_qty
01 34892
02 54548
... ...
and so forth. Right now, the column "hs2" gives me a very large number of observations and, as you can understand, they repeat themselves multiple times (as the variables vary across both time and country of destination). So, the task would be to have every hs2 number just once, with the correspondent value of "total" exports.
Also (but that would be just a plus, I could just check the numbers by myself) it would be nice to get a result sorted by exp_qty, so to have a ranking of the most exported goods by quantity.
The following might be a start at what you need.
collapse (sum) exp_qty, by(hs2)
gsort -exp_qty
collapse summarizes the data in memory to one observation per value of hs2, summing the values of exp_qty. gsort then sorts the collapsed data by descending value of exp_qty so the first observation will be the largest. See help collapse and help gsort for further details.