I have two tables in Power BI - each has the exact same columns, however, one is from the past 7 days, and the other is from the 7 days before that. I simply want to be able to compare the data week-over-week, but am struggling to get it to work.
For example, a column used is "Source." It lists the source used for each row. I tried creating a clustered column chart and putting the "Count of Source" fields from each table in "Value" and then "Source" in "Axis." When I do this, it accurately displays the columns for one table, but the other tables' values are all messed up - it just shows the sum.
See image :
Related
I am trying to recreate a Tableau table view in Power BI where I can compare two customizable date ranges and show the percent differences across metrics as a calculated row.
Reference Screenshot from Tableau
In practice, my table will have 3 rows: 1 row for each time period selected and a row for the percent difference. The percent difference row is a nice to have, not a need. All my table metrics are coming from the same source.
I also need to set up two different date slicers that each row of my table will reference. I've played around a little with setting up a separate date table for the comparison period to be selected from, following this thread: Comparing Data Across Date Ranges
The challenge now is showing two separate periods in the same table.
Appreciate any guidance!
I am loading an Excel file, in which it has 43 rows, all the rows are identical. This is the only file I'm loading and there are no connections relationships in the model whatsoever.
When I plot my data into a table visual, and choose not to summarize any of my fields, Power BI still shows me one row. While if I change any of the field to do a count of it, it shows me correctly that I have 43 rows. I need to be able to see all the 43 rows in my table.
Why is Power BI summarizing my data even if I command it not to do so?
Am I missing something simple?
Input table as seen in Power BI data tab:
The visual I'm trying to create:
The table visual in Power BI behaves similar to a Pivot Table in Excel.
W/o an aggregation defined, the "Values" fields behave like "Rows" in a Pivot Table and you will only see distinct items or distinct item combinations. You have 43 identical records, hence it is represented as one row in the visual.
With an aggregation defined (Sum, Count, ...) the field behaves like "Values" in a Pivot Table, and you get the result of that aggregation, filtered by the distinct items/combinations to the left, which is again one row in your case.
If you just want to show all the records in a table visual, you'll have to make them unique. The easiest way to achieve that is by adding an index column in PowerQuery and then also showing that index in the table visual.
However, this is not exactly what Power BI is made for and you are probably better off by switching to something like PowerPoint instead.
And btw., newer show sceenshots in stackoverflow, always provide sample data instead.
I've got an oddly set up google sheet as my data source for a powerBI dashboard. Right now my main stress point is a 'last 7 days' filter that needs to be applied. The problem is that there are multiple columns containing dates that could be in the last 7 days, in this case representing multiple steps in an email chain.
If any one of those columns contains a date in the last 7 days, then I need to capture the row in most of my visualizations and tables, but if I just use standard filters, PowerBI assumes 'AND' and displays none of the rows, since there will almost never be a row where multiple date entries are in the last 7 days.
I'm almost certain there is a way to do this with either merged columns or calculated fields, or maybe there is even something as simple as an 'OR' filter, but thus far my googling has not turned up anything. Do you know a work around for this?
Thanks in advance!
In Power Query Editor, create a duplicate column for each of your date fields.
Make sure each of the duplicated columns is in Date format and then calculate the "Age". You will get a time value. In the Transform pane, use the "Duration" function and convert to "Days". Do this for each of the duplicated columns.
Now the last step: Create a "conditional column" in the "Add column" pane, and pull all of these new columns that should now have integer values and set the condition to show "Yes" if less than or equal to 7, "No" if more than 7.
Let me know if this helps.
I need a calculated column based on conditions in two columns (Business Unit Number in both tables and L1/Account Categories in 1st table and the second table) which sum and then repeat for several rows before the conditions change and a new sum is repeated for several rows and so on. The L1/Account Categories columns have different names because it's the raw data.
For example, any time ASSETS and 111 appear in the same row, I would want to use those as conditions and with the sum of all of the other matching rows in a new column and the sum would repeat each time both conditions appeared in the same row. Any time P/L and 111 appear in the same row, that would be a sum of all other P/L and 111 appearances in the dataset (about 1000 rows overall)... and so on.
I've tried formulas with DAX using FILTER, SUMX, nested IF statements and also tried the Power Query language among other attempts. Maybe I have to create one or more than one new table? If you need to take a look at a few of my attempts, just let me know.
The top image is how I imagine the output will look in the power query editor and the bottom image is a sample of the source data.
This last pic is from Tableau - I need to make a table in Power BI which essentially a duplicate of this image. The last 2 columns are pulling from different tables.
This should be very simple to achieve with relationships and measures - no need for calculated columns or power query merges. You need to build a relationship between these two tables. In fact, I would introduce a third table in your model for Business unit.
The limitation of Power BI model relationships is that they can only be based on a single column. So to build a relationship between these two tables you would have to add a calculated column in both of them that would contain both a BU and the financial statement line, for instance: JoinCol = CONCATENATE([Business_Unit_Number], [L1]). Then you could create a relationship and do what you want.
The better (one that I would recommend) approach would be to separate Business Unit into a separate table and have relationships built like this:
Then all you have to do in your visual is drag Business unit name from the BU table, L1 from the FS Lines table and a measure to sum the amounts Amount = SUM('Financial Data'[Rolled Up Detail]).
Here is a working sample: https://1drv.ms/u/s!AmqvMyRqhrBpgtUT5HKnZP1U3Gzc9w?e=en91dV
I hope I'm not missing an easy solution am still getting used to DAX and can't yet find an appropriate logic.
I have a large dataset, >10m rows which I want to test. An identifier column "DocumentNumber" might occur on multiple rows and I want to find where the sum of "Value" over these rows for a given "DocumentNumber" is non-zero.
Tried to use PowerQuery > removed all but these two columns > Group By > DocumentNumber > Sum of Value. However my 32 bit version of Excel appears to run out of memory performing this step Expression.Error: Evaluation ran out of memory and can't continue.
Wrote a DAX measure > Sum of Values and dropped into a pivot table with a view to filtering out the zero values but when I try to drag in the DocumentNumber to rows there are more than a million rows so the table won't render.
Is there a logic I should follow in DAX that would achieve step 2 before bringing it to the pivot table? Can DAX actually create a new table in the data model which is the aggregated and filtered data rather than using a pivot? I believe this is possible in PowerBI but not sure about Excel evironment.