I have an identified date within a fact table and I need to create a new table that's formatted "MMM-YY" (JAN-01) and sorted in month order.
I entered the data manually from a Excel Spreadsheet with dates ranging from Jan-15 to Dec-30 and sorted by an id num but ideally I want it to update monthly based on a identified date column within the fact table in BI. So for now id want dates upto Sep-19 which would update when the identified dates are refreshed within the fact table.
For now I've used the below to format the column which was inserted manually however id like to change the monthref.date to be based off of an identified date within my fact table.
ID Date = FORMAT('Month Ref'[Date],"MMM-YY")
Id want my date within the fact table to be lookedup/refrenced in another table formatted "mmm-yy" and to be in order of calendar month.
I can use
CALENDAR(MIN(FactEfficiencies[identified_date].[Date]) AND MAX(FactEfficiencies[identified_date].[Date])) to get every date then format but it will bring back the month multiple times when I just need one.
You are already on the good direction with the calendar table. One thing that could help you achieve your result could be including a SUMMARIZE or GROUPBY function. Have a look at this example.
Calendar =
var _fullCalendar =
ADDCOLUMNS (
CALENDAR ( MIN ( 'Table'[Date] ) ; MAX ( 'Table'[Date] ) ) ;
"MonthYear" ; FORMAT ( [Date] ; "MMM-YY" )
)
RETURN
SUMMARIZE ( _fullCalendar ; [MonthYear] )
Related
i have two tables in power bi that i am trying to join or lookup.
the period table has the days, months, and month id.
the data table has the days and data.
i need to pull the month id from the period table into the data table so that i have a table like the final result picture where the month id is now included.
final result
i tried using lookup and crossjoin but they dont work.
Month = EVALUATE
ADDCOLUMNS (
Sales,
"month", RELATED ( 'period'[day] )
)
I think that the following formula summarize pretty well what I want to achieve:
date diff =
ABS (
DATEDIFF (
data_table[login_date],
SELECTEDVALUE ( 'Date'[Date] ),
DAY
)
)
but it returns me the following error
A single value for column 'login_date' in table 'data_table' cannot be determined. This can happen when a measure formula refers to a column that contains many values without specifying an aggregation such as min, max, count, or sum to get a single result.
In other word I want have a column in my data_table with date diff calculated dynamically based on min slicer date selection.
My final goal is to filter out dynamically users that has not been logged for the last 3 months based on the slicer date range.
Here is the dataset
user_id, login_date
111, 01/02/2021
222, 02/15/2021
444, 03/15/2021
555, 01/15/2021
I want user ID to be filtered out when the number of days between the max date of the date range and the day of the last connection is higher than 90 days.
Edit
I'm adding a different formula I'm working on but having few issues to make it work
active users = CALCULATE( DISTINCTCOUNT(data_table[id]), ( FILTER ( VALUES ( data_table[id] ), DATEDIFF(IF( ISBLANK(SELECTEDVALUE(data_table[login_date])),[Min range date],SELECTEDVALUE(data_table[login_date])),[Max range date],DAY) < 90 ) ))
You can't have a dynamically calculated column, but you can use a measure to do this. The issue that you have with your calculation is that it needed to do a row by row evaluation, rather than over a column. That is why you get an 'A single value for column 'login_date' in table 'data_table' cannot be determined' error.
In this case you can use SUMX, as this is a iterator and it will do row by row. So using the following measures:
Selected Date = SELECTEDVALUE('Calendar'[Date])
This reads the date selected. You can wrap it with a MIN/MAX if needed depending on how your slicer is set up. You can change the slicer to single select, it you just want one value.
Date Calc = SUMX('Table', DATEDIFF('Table'[Login_date], [Selected Date], DAY))
This uses SUMX to calculate on a row by row level.
You can then use this measure to drive your visual. In this example I've filtered out those over 30 days since the login
If you choose a new date, it will recalculate straight away. This should set you on the right path for your use case.
My intention is to populate days of the month to simulate a data warehouse periodic snapshot table using DAX measures. My goal is to show non-additive values for the quantity.
Consider the following transactions:
The granularity of my snapshot table is day. So it should show the following:
Take note that a day may have multiple entries but I am only interested in the latest entry for the day. If I am looking at the figures using a week period it should show the latest entry for the week. It all depends on the context fixter.
However after applying the measure I end up with:
There are three transactions. Two on day 2 and the other on day 4. Instead of calculating a running total I want to show the latest Qty for the days which have no transactions without running accumulating totals. So, day 4 should show 4 instead of summing up day 3 and day 4 which gives me 10. I've been experimenting with LASTNONBLANK without much success.
This is the measure I'm using:
Snapshot =
CALCULATE(
SUM('Inventory'[Quantity]),
FILTER(
ALL ( 'Date'[Date] ),
'Date'[Date] <= MAX( 'Date'[Date] )
)
)
There are two tables involved:
Table # 1: Inventory table containing the transactions. It includes the product id, the date/time the transaction was recorded and the quantity.
Table # 2: A date table 'Date' which has been marked as a date table in Power BI. There is a relationship between the Inventory and the Date table based on a date key. So, in the measure, 'Date'[Date] refers to the Date column in the Date table.
You can use the LASTNONBLANKVALUE function, that returns the last value of the expression specified as second parameter sorted by the column specified as first parameter.
Since LASTNONBLANKVALUE implicitly wraps the second parameter into a CALCULATE, a context transition happens and therefore the row context is transformed into the corresponding filter context. So we also need to use VALUES to apply the filter context to the T[Qty] column. The returned table is a single row column and DAX can automatically convert a single column, single row table to a scalar value.
Then, since we don't have a dimension table we have to get rid of cross-filtering, therefore we must use REMOVEFILTERS over the whole table.
the filter expression T[Day] < MaxDay is needed because LASTNONBLANKVALUE must be called in a filter context containing all the rows preceding and including the current one.
So, assuming that the table name is T with fields Day and Qty like in your sample data, this code should work
Edit: changed in order to support multiple rows with same day, assuming the desired result is the sum of the last day quantities
Measure =
VAR MaxDay =
MAX ( T[Day] )
RETURN
CALCULATE (
LASTNONBLANKVALUE (
T[Day],
SUM ( T[Qty] )
),
T[Day] <= MaxDay,
REMOVEFILTERS ( T )
) + 0
Edit: after reading the comments, this might work on your model (untested)
Measure =
VAR MaxDay =
MAX ( 'Date'[Date] )
RETURN
CALCULATE (
LASTNONBLANKVALUE (
Inventory[RecordedDate],
SUM ( Inventory[Quantity] )
),
'Date'[Date] <= MaxDay
) + 0
I have two tables:
A calendar table with both dates and hours.
And a table that contains incidents, with start time and end time in addition to set of attributes (only one, incident_code, in the example table).
For a specific date range, I want to show how many incidents occurred each hour.
The following measure works, but struggles when the incident table becomes large and there is several slicers
incidentCnt =
CALCULATE(
COUNTROWS(incidents);
FILTER(
incidents;
incidents[start_datetime] < MAX(date_hour[datetime]) &&
incidents[end_datetime] > MAX(date_hour[datetime])
)
)
What would be a more efficient way to calculate this with DAX in Power BI?
EDIT: This expression will work with the data presented above (minor edits to the accepted answer).
Expanded_Incidents =
GENERATE(
incidents;
SELECTCOLUMNS(
GENERATESERIES(
DATE(
YEAR(incidents[start_datetime]);
MONTH(incidents[start_datetime]);
DAY(incidents[start_datetime])
) + TIME(HOUR(incidents[start_datetime]);0;0);
incidents[end_datetime];
TIME(1;0;0)
);
"Expanded_incident_time"; [Value]
)
)
A more effectiv way would be to expand the incidents table so that each incident occurs for each time between the start and end datetime. This you can do with a calculated table like this:
Expanded_Incidents =
GENERATE(
incidents;
SELECTCOLUMNS(
GENERATESERIES(
incidents[start_date];
incidents[end_date];
TIME(h;m;s)
);
"Expanded_incident_time"; [Value]
)
)
Change the TIME(h;m;s) to the time resolution of your choosing.
Then make a relationship between your dateTime dim table and the [Expanded_incident_time] column (this should be a 1:*). Then you only have to make a measure which counts the number of rows in the new table. This will give you the number of active incidents during a specific time and I believe it will be faster than reitterating over the table each time.
I'm building a PowerBI report from a dataset that contains start and end dates. I'd like to filter the dataset based on rows that would encompass a selected date in another table.
The screenshot here shows a sample. I want to click a date in the table on the right and have the table on the left filtered where the selected date is between the start & end date.
I've attempted several different things using columns and measures, but I haven't been able to nail it down. I also attempted to create a new table from a DAX expression that references the selected date, but that caused errors.
How can I dynamically filter the dataset based on the selected date being between the start and end date values?
Create a measure to check whether a row overlaps the selected date range:
Date Included =
IF (
FIRSTNONBLANK ( Table1[Start Date], 1 ) <= MAX ( 'Calendar'[Date] ) &&
FIRSTNONBLANK( Table1[End Date], 1 ) >= MIN ( 'Calendar'[Date] ),
"Include",
"Exclude"
)
Add this Measure as a filter on your visualisation, where Date Included is Include
Now you can filter your Calendar table ( to single value, or range), and only overlapping rows from your fact table will be displayed.
See https://pwrbi.com/so_55925954/ for worked example PBIX file