I would like to create a calculated column or measure that shows the time elapsed in any given month. Preferably as a percentage.
I need to be able to compare productivity (rolling total) over a month's period between different months.So creating a percentage of time passed in a month would put every month on a level playing field.
Is there a way to do this?
Or is there a better way to compare productivity between 2 months on a rolling basis?
EDIT
I am graphing sales on a cumulative basis. Here is a picture of my graph to demonstrate.[][
Ideally I would like to be able to graph another person's sales on the same graph for a different month to compare.
The problem is each month is different and I don't think power bi allows much customization of the axes.
So I figured a potential solution would be to convert months to percentages of time passed, create two separate graphs and place them on top of each other to show the comparison of sales.
Using percentages doesn't sound right here: one person's "productivity" in February will appear lower than another person's productivity in March just because February has 3 less days.
Just use [Date].[Day].
To answer the original question (even though it shouldn't be used for this), month progress percentage calculated column:
MonthProgress% =
var DaysinMonth = DAY(
IF(
MONTH(MyTable[date]) = 12,
DATE(YEAR(MyTable[date]) + 1,1,1),
DATE(YEAR(MyTable[date]), MONTH(MyTable[date]) + 1, 1)
) - 1
)
return MyTable[date].[Day]/DaysinMonth*100
Also check DAX functions PARALLELPERIOD and DATEADD.
This is the solution I settled on.
I customized the ranges for the x and y axes so they match.
For the y-axis, I simply put the range from 0 to 50+ our highest month.
For the x-axis, I created a column with the DAY function so I got a number assigned to each day of the month which allowed me to manually set the chart range from 0 to 31. I have asked another question on how to only get workdays.
Related
I am trying to create a % of sales measure in power bi. I currently have a visual that is filtered on sales for select items by day and another visual that just has the total sales by day and then I export and do the math in excel. I know there is a way to have just one visual give me the % of sales for the items I have selected, but can't figure out the DAX formula. I am looking for the formula that will take sales for item 1 on Monday of $3,461 and divide by total sales for Monday of $163,534 to get a 2.1% of sales (for all items). Thanks
Power Bi Visuals
I tried a couple formulas but was unsuccessful..
The December release of PBI has been pushed out to all users, and it comes with a brand-new WINDOW function. This allows you to create calculations that would be relative to data being displayed in the visualization rather than applying across an entire table.
Some things you can do with this type of DAX calculation:
Moving averages
Can also combine with parameters for additional functionality!
Dynamic reference lines
Cross row calculations
Finding best and worst performers (with ABS references)
Calculate contributions to the whole
Relevant links:
https://www.youtube.com/watch?v=eib5X5xRlz8
Introducing DAX Window Functions (Part 1) – pbidax (wordpress.com)
WINDOW – DAX Guide
I am trying to create a power BI calculation as an average per day of how many times a code was tripped. The dax calculcation that I have
Count Trips average per Day =
AVERAGEX(
KEEPFILTERS(VALUES('ruledata (2)'[Date].[Day])),
CALCULATE([Count Trips])
)
works fine when the average is being calculated over a couple days. I double checked this by hand and can confirm that it is accurate until at least 2 weeks. However once the time range increases to include months the average starts getting ridiculous and begins displaying average trips /day values that are much higher than the highest number of trips on a single day. I have confirmed that the data in the graph is correct
So I know that the values should reflect what is in the graph. In this two month example the DAX formula calculated the average to be 149.03 but the actual average/day should have been 82.8.
In general is there some sort of error in the DAX formula that I am using that could cause this?
I guess that 'ruledata (2)'[Date].[Day] is the day of the month. So if you take the average it will be wrong because when you take the average of e.g. March and April you will divide the total trips by 31, and not by 61 (30+31). So use 'ruledata (2)'[Date].[Date] instead.
I am using a slicer to determine a certain periode of time (e.g. 01.10.19 - 31.10.19) and now I want Power Bi to calculate how many days are included (in this case it would be: 31). Of course the calculation needs to be updated every time I use the slicer. Is there any possibility to do so? I have literally no idea...
Create a measure to calculate the difference between the max and min dates in your date table, which is filtered by this slicer. You can use DATEDIFF function for that. In this case the number of days will be calculated as:
Number of days = DATEDIFF(MIN('Calendar'[Date]); MAX('Calendar'[Date]); DAY) + 1
Maybe this is an easy one but since I’m very new in DAX and PowerBI I can’t figure it out. My database has daily data ranging from MAY/17 to JUN/17 (and it’ll still going in the future). It has information of DATE, DAY, YRMTH (year-month), QT_APRV (approved customers) and QT_TOTAL (total consumers). Sample below (using Excel just to be quicker):
I wanted to create in PowerBI a bar chart with QT_TOTAL per day and a line chart with approved rate of consumer. For the rate, I used:
APPRV_RT = SUM(database[QT_APRV]/SUM(database[QT_TOTAL])
And then, selecting only a month by time in the chart (just like I want), I have:
Perfect, but now I want to create a new line chart, showing the approved rate in each respective day of the last month. Using my example, when june data are select, the first line chart has to show the daily approved rate of june AND the other the approved rate of may, in order to make it comparable (june1 -> may1; june12 -> may12 and so on). Here’s what I want:
How to make this automatically, in order to make each month comparable with the previous? I thought about some DAX formula involving a sum with filtering current month minus 1, I don’t know how to do it.
Any ideas?
UPDATE (07/08/2017)
I tried what Rasmus Dybkjær suggested me, and I thing I'm in the right path.
APPROVED_RATE_PREVIOUS_MONTH = CALCULATE([APPROVED_RATE_CURRENT_MONTH];PARALLELPERIOD(dCalendario[DataBase];-1;MONTH))
However, it returned the approved rate from the previous month as a whole (67,0% in May), not each day as I wanted:
Any suggestions?
You should be able to use the DAX function called PARALLELPERIOD() for this purpose. The PARALLELPERIOD() function takes a date column and shifts it a number of periods back or forward.
For example, you could use it like this to calculate your approved rate shifted one month back:
ApprovedRateLM =
CALCULATE(
DIVIDE(
SUM(database[QT_APRV]),
SUM(database[QT_TOTAL])
),
PARALLELPERIOD(database[Date],-1,month)
)
Note that it is important that your [Date] column contains a date type. Otherwise the PARALLELPERIOD function will not work.
I am attempting to calculate the most recent 6-Month STDEVX.P (not including the current month; so in May 2017, I'd like to the STDEVX.P for periods Nov 2016 - Apr 2017) for sales by product in order to further calculate variation in sales orders.
The Sales Data is made up of daily transactions so it contains transaction date: iContractsChargebacks[TransactionDate] and units sold: iContractsChargebacks[ChargebackUnits], but if there are no sales in a given period, then there will be no data for that month.
So, for example, on July 1st, sales for the past 6 months were the following:
Jan 100
Feb 125
Apr 140
May 125
Jun 130
March is missing because there were no sales. So, when I calculate STDEVX.P on the data set, it is calculating it over 5 periods, when in fact there were 6, just one happens to be zero.
At the end of the day, I need to calculate STDEVX.P for the current six month period. If when pulling the monthly sales numbers, it only comes back with 3 periods(months), then it needs to assume the other 3 periods with a zero value.
I thought about manually calculating standard deviation instead of using the DAX STDEVX.P formula and found these 2 links as a reference on how to do so, the first being closest to my need:
https://community.powerbi.com/t5/Desktop/Problem-with-STDEV/td-p/19731
Calculating the standard deviation from columns of values and frequencies in Power BI...
I attempted to make a go of it, but still am not getting the correct calculation. My code is:
STDEVX2 =
var Averageprice=[6M Sales]
var months=6
return
SQRT(
DIVIDE(SUMX(
FILTER(ALL(DimDate),
DimDate[Month ID]<=(MAX(DimDate[Month ID])-1) &&
DimDate[Month ID]>=(MAX(DimDate[Month ID])-6)
),
(iContractsChargebacks[SumOfOrderQuantity]-Averageprice)^2),
months
)
)
*note: Instead of using date parameters in the code, I created a calculated column in the date table that gives each Month a unique ID, makes it easier for me.
Your question would definitely be easier to answer with more explanation regarding your model. E.g. how you defined [SumOfOrderQuantity] and [6M Sales], since a mistake there could definitely impact the final result. Also, knowing what the result you're seeing is vs. the result you expect would be helpful (using sample data).
My guess, however, is that your DimDate table is a standard date table (with one row per date), but you want standard deviation by month.
The FILTER statement in your formula limits the date range to the prior 6 full months correctly, but it will still have one row per date. You can confirm this in Power BI by going into the Data View, selecting 'New Table' under Modeling on the ribbon, and putting your FILTER statement in:
Table = FILTER(ALL(DimDate),
DimDate[MonthID]<=(MAX(DimDate[MonthID])-1) &&
DimDate[MonthID]>=(MAX(DimDate[MonthID])-6))
Assuming you have more than one day of sales for a given month, calculating the variance by day rather than by month is going to mess things up.
What I'd suggest trying:
Table = FILTER(SUMMARIZE(ALL(DimDate),[MonthID]),
DimDate[MonthID]<=(MAX(DimDate[MonthID])-1) &&
DimDate[MonthID]>=(MAX(DimDate[MonthID])-6))
The additional SUMMARIZE statement means that you only get one row for each MonthID, rather than 1 row for each date. If your [6M Sales] is the monthly average across all 6 months, and [SumOfOrderQuantity] is the monthly sum for each month, then you should be set to go calculating the variance, squaring, dividing by 6, and square rooting.
If you need to do further troubleshooting, remember you can put a table on your canvas with MonthID, SumOfOrderQuantity and [6M Sales] and compare the numbers you expect at each stage of the calculation with the numbers you're seeing.
Hope this helps.
I was facing a similar problem while trying to calculate the coefficient of variation (Std. /Mean) by SKUS from sales data. I could use the Pivot-Unpivot function in Power Query editor to to do away with the problem of months with missing sales:
1) Export the data with any calculated columns
2) Reimport the data so that the calculated columns are also available in the power query editor
3) Pivoted the data by months
4) Replaced null values with 0s
5) Unpivoted the data
6) Close and apply the query
7) Add a calculated column for the coefficient of variation using the formula
CV = CALCULATE(STDEV.P(Table1[Value]),ALLEXCEPT(Table1,Table1[Product]))/CALCULATE(AVERAGE(Table1[Value]),ALLEXCEPT(Table1,Table1[Product]))
Thus zero sales for the missing months will also be considered both for Standard Deviation and Mean.