I am pulling data from multiple spreadsheets into a table using power query, generating a table of the following format:
Date
Description
Revenue
1
a
£1,000
2
b
£2,000
3
c
£3,000
I want to manually enter data into a fourth 'fee' column (as set out below) each month. When I come to refresh the query in the following month I want to ensure that the 'Fee' data will still correspond with the relevant month.
Date
Description
Revenue
Fee
1
a
£1,000
£1,500
2
b
£2,000
£2,500
3
c
£3,000
£3,000
Related
I'm creating a pivot table that looks at per person analysis vs group average. Trying to create a pivot table, to do a comparison analysis (each person vs the group average) on a month over month analysis. As you can see i have a 4th column titled average, as im not sure how to get the average for the group though per month seeing how the data is spread out.
my test data;
http://www.mediafire.com/file/3yyriggqduw6ldw/file
You can do a sumif/countif on the range for only the year & month
(if would be year=row year and month=row month)
You basically need 2 measure as below-
1.
person_wise_average = AVERAGE(your_table_name[sale])
overall_average =
AVERAGEX(
ALL(your_table_name),
your_table_name[sale]
)
Now just add three column to your table visual - "person name", "person_wise_average" and "overall_average". You should now have all your values in the presentation.
My Data is in weekly buckets. I want to split the number into a monthly number but, since there is an overlap in days falling in both the months, I want a weighted average of the data in terms of days that fall in each of the months. For example:
Now, in the above picture, I want to split that 200 (5/7*200 in Jan, 2/7 in Feb). How can I do that using Excel/ Power Pivot/ Dax Functions? Any help here is much appreciated.
Thank you!
Assuming your fact table looks something like below. Values are associated with the starting date of the week it occurred.
Although it may actually be a more granular data, having multiple rows for each week with additional attributes (such as identifiers of a person, a store, depending on the business), what being shown below will work the same.
What we need to do first is to create a date table. We can do that in "Design" tab, by clicking "Date Table", then "New".
In this date table, we need to add a column for starting date of the week which the date of each row is in. Set the cursor to "Add Column" area, and input following formula. Then rename this column to "Week Start Date".
= [Date] - [Day Of Week Number] + 1
Now, we can define the measure to calculate the number allocated to each month with following formula. What this measure is doing is:
Iterating over each row of the fact table
Count the number of days for the week visible in the filter context
Add the value portion for the visible days
Value Allocation := SUMX (
MyData,
VAR WeekStartDate = MyData[Week]
VAR NumDaysInSelection = COUNTROWS (
FILTER (
'Calendar',
'Calendar'[Week Start Date] = WeekStartDate
)
)
VAR AllocationRate = DIVIDE ( NumDaysInSelection, 7 )
RETURN AllocationRate * MyData[Value]
)
Result in the pivot table will be looking like this.
I have 2 large tables in power pivot and I am trying to reconcile stockpile build grades to crushed stockpile grades. Please see example. I can create pivot table that contains the crushed grades but I am unable to find the right way to bring the stockpile grades though for the reconciliation high lighted in green in the attached example.
Thanks for any help or direction on where to look
In Power Query, create your lookup tables.
1) unique crushers, ID
2) Dates, ID
Here is a function to create a dates table, if you need one. After you invoke the function to get the column of dates, add another column for the ID.
/*--------------------------------------------------------------------------------------------------------------------
PQ Create a Dates Table, returning a single column of dates.
Inputs:
Start Date | Enter the year as yyyy, month as mm, day as dd
End Date | Enter the year as yyyy, month as mm, day as dd
Increments | One row will be returned per increment.
Author: Jenn Ratten
Edits:
07/16/18 | Modified query copied from the internet.
10/01/19 | Converted to a function.
--------------------------------------------------------------------------------------------------------------------*/
let
fDatesTable = (StartYear as number, StartMonth as number, StartDay as number, EndYear as number, EndMonth as number, EndDay as number, IncrementDays as number, IncrementHours as number, IncrementMin as number, IncrementSec as number) as table =>
let
StartDate = #date(StartYear,StartMonth,StartDay),
EndDate = #date(EndYear,EndMonth,EndDay),
Increments = #duration(IncrementDays,IncrementHours,IncrementMin,IncrementSec),
DatesTable = Table.FromColumns({List.Dates(StartDate, Number.From(EndDate) - Number.From(StartDate), Increments)}, type table[Date]),
ChangeType = Table.TransformColumnTypes(DatesTable,{{"Date", type date}})
in
ChangeType
in
fDatesTable
Load all of the tables to the data model.
Go to Power Pivot, diagram view, and create your relationships.
Lookup Crusher to data tables 1 and 2
Lookup Date to data tables 1 and 2
Go to Data View on data tables 1 and 2, add 2 new columns for the lookup IDs. You can specify the column header and the formula at one time by clicking in first cell and using this syntax, then either press enter or click the check mark in the formula bar.
Dates Lookup ID:=RELATED(lookup_dates[ID])
Crusher Lookup ID:=RELATED(lookup_crusher[ID])
Optional, but a good practice....
Right-click the new fields you just created and select "hide from client tools". Also hide the date and crusher fields on both data tables, and the ID field on both lookup tables. When you are creating pivots to summarize data from more than one table, the text fields that you place on your pivot table should be the fields that are shared (aka the lookup tables). This helps to minimize pivots in which the grand totals don't match the sum that you actually see on the table. If you hide the fields, it reminds you of that. There are exceptions of course, but this is a good rule of thumb.
Now create measures to sum the tons and any other math calculations you'd like. With the measures, start simple and let the pivot do the slicing. Put the measures in the values section of the pivot table.
Sum of Source Tons:=sum(Table1[Tons])
Sum of Destination Tons:=sum(Table2[Tons])
When displaying prior month sales, I noticed that items with no sales in current month are missing in the Pivot Table output of the data model. However, the grand total sales includes sales of those missing items.
I created a small data model to replicate the issue: 2 tables (1 sales table and 1 calendar table) and it has 1 single DAX formula:
Previous Month Sales:=CALCULATE(sum([Sales]),PREVIOUSMONTH(Sales[Date]))
In the output table, I would have expected 1 more item row for Potatoes, with 0 sales in current month and 31 in previous month.
Is there a way to force-show Potatoes item in the pivot table above when selecting date 24/03/2019? Can this be achieved with DAX formulas?
You need to use the Date field from your Calendar (Date) table, for Time Intelligence to work as you intend:
So change your Previous Month Sales measure to:
Sales Previous Month:=CALCULATE (
SUM ( Sales[Sales] ),
PREVIOUSMONTH ( Calendar[Date] )
)
I'd also recommend creating an Explicit Measure for Sales:
Sales Total:=SUM ( Sales[Sales] )
Now you can recreate your pivot output, using Date field(s) from Calendar in your slicer / filter, and you should get the output you require:
I have a table in SSAS tabular mode that shows how individual pieces of products moved through different sections of a production line:
Product_ID, section_ID, Category_id (product category), time_in (when a product entered the section), time_out (when the product exited the section)
This is how the input table looks like:
I would like to write a measure in DAX that can show me the stock of each section and product category day-by-day as shown below by counting the number of distinct product ids which were in a particular section on that day.
I'm using SQL Server 2017 Analysis Services in Tabular Mode and Excel Pivot Table for representation.
Create a new table that has all of the dates that you want to use for your columns. Here's one possibility:
Dates = CALENDAR(MIN(ProductInOut[time_in]), MAX(ProductInOut[time_out]))
Now create a measure that counts rows in your input table satisfying a condition.
ProductCount =
VAR DateColumn = MAX(Dates[Date])
RETURN COUNTROWS(FILTER(ProductInOut,
ProductInOut[time_in] <= DateColumn &&
ProductInOut[time_out] >= DateColumn)) + 0
Now you should be able to set up a pivot table with Category_id on the rows and Dates[Date] on the columns and ProductCount as the values.