I would need a report that shows variances for the current period, next period, half-year and year-end.
There is a period filter from 1 to 12 representing the periods in a year.
I can build up a table that shows the difference:
for the current period (can be amended based on the period filter)
for full-year (using ALL function to ignore the period filter)
But I don't know how to write a dax that filter just for the first 6 periods as half-year.
Or add one to the current period filter to shows the next period-related variance.
Also, that should be dynamic. This means if I adjust the period filter it should show always be the next period. (If the filter is set for 1 to 4 it returns 1 to 5; set 2 to 7 returns 2 to 8).
Could you please help me with how to do that?
Thanks
So, let's say we have 2 databases.
The plan for the current year and the actuals:
Excel
And I would like to see the difference between them in one visualization.
If the period set is 1 to 2:
for the current period shows: sum plan (1-2) - sum Actual (1-2)
next period: sum plan (1-3) - sum Actual (1-3)
Half Year: sum plan (H1) - sum Actual (H1)
FY: sum plan (1-12) - sum Actual (1-12)
I am not able to understand exact query but it seems that as per your given examples it's more related to time intelligence formulas in PowerBi to given results based on specific time frames. (YTD, QTD etc)
Below is the link to address your query via time intelligence formula
https://www.analyticsvidhya.com/blog/2020/08/time-intelligence-power-bi/
Related
I have the following measure:
test = SWITCH(TRUE(),
MAX(test[month])>=9&&MAX(test[month])<=12,"fall",
MAX(test[month])>=1&&MAX(test[month])<=3,"winter",
MAX(test[month])>=4&&MAX(test[month])<=6,"spring",
MAX(test[month])>=7&&MAX(test[month])<=8,"summer")
Currently it looks at the month number (i.e. "3" for March and outputs "winter", what I'd like however is it to output is a count per season to show the distribution of the seasons in the dataset.
For example my desired output would be
Month Number
Count of occurrences of each season
fall
5
winter
7
spring
11
summer
2
I can't have a calculated column here either as I will want to make this measure dynamic later on with the use of a slicer, can someone tell me if this is possible?
The issue here is that you want to define your categories within the measure. Measures are not dynamic without some filter-context.
Take this for example:
Notice that the output of the calculation is identical between seasons.
There is no filter context to help the measure discern between the different seasons because these seasons are not defined in the model. (At least, I don't know how to make this work)
Switch returns the first true result. So, if you have values like in your sample, then start with the smallest, then bigger, and the largest at the end.
test =
SWITCH(
TRUE()
,MAX(test[month])<4,"winter" -- test <4
,MAX(test[month])<7,"spring" -- 3< test < 7
,MAX(test[month])<9,"summer" -- 6< test < 9 -- Is it ok that you have 2 months in
,"fall" -- 8< test -- summer and 4 in fall?
)
If you use MAX(test[month])<4,"winter" instead of MAX(test[month])<=3,"winter" then you avoid one calculation step and the code will be faster.
Then you need to use the result to find months numbers and get dates from the selected months. Then calculate your table filtered by months dates. If this answer is not enough to solve the case, then give more information about you table, it's columns, and what do you mean by 'Count of occurrences of each season', exactly what does 'occurrences' mean, is it a number of certain rows or some unique values.
I want to calculate the total number of invocation for all the lambdas in my AWS account for the last month. As shown in the picture there is the time period at top right where I specify the from and to time. As I understand that is the time period within which I calculate the number of invocations. There is also a Period column in the table below I don't understand its significance and changing it has a effect on the Invocation Count
Go to Graph Options tab you see on that screenshots and there you'll have 2 options for which value to display:
Latest value
This shows the value from the most recent period of your chosen time range.
For example, if you choose 'Statistic - Minimum' and 'Period - 5 Minutes', it shows the minimum value from the latest 5-minute period of your chosen time range.
Time range value
This shows the value from the entire time range.
For example, if you choose 'Statistic – Minimum', it shows the minimum value from your entire time range. The 'Period' setting has no effect on the value displayed.
If by the last month you mean last 30 days, then you would select option 1 above and change period of the metric to 30 days.
If you need the last calendar month (September 1st till September 30th), then you would select option 2 above and set the time range you need in the dashboard setting.
Graph the metric and timerange you want and add a Dynamic Label - "sum". The legend of the graph will then contain the sum of all datapoints for each metric you have graphed.
I need to find one way or another the following formula in Power BI:
Total Hours of Use of a Machine = Hours Function * Range of Functioning
where Hours Function is the hours of use of a certain machine. Take it at a cost that for each machine is a constant and Range of Functioning is the difference between the final date of the evaluation and the initial date, measured in hours.
For example, I want to measure the Total Hour Use of a Machine in between 15/10/2019 and 14/20/2019. So the math is the following:
Assume: 2 machines
Hours Function machine A: 6
Hours Function machine B: 9
Range of Functioning = 15/10/2019 - 14/10/2019 = 24 hours
The output:
Total Hours of Use of a Machine A: 144
Total Hours of Use of a Machine B: 216
I need to do that in Power BI in a way that any user moving a slicer of date, refresh the Total Hours of Use of a Machine.
I don't find any way that I can get the difference between the final date of the evaluation and the initial date and put in DAX or a new column.
You have to use measures if you want to recalculate the value when you change the date with a slicer.
The first step is to be sure to be able to calculate the number of day selected by your slicer.
It seems to be easy but if you use the function FirstDate on your calendar table directly integrated in PowerBI.
You'll never have what you expect.
The tricks here to get this number of day is to calculate the number of rows in your calendar table with the function countrows.
When you have this number day you just have to multiply this by 24 ( hours) and by the sum of your "Hours Function machine".( 6 for A 9 for B in your example )
( It's important to use the sum or another aggregate function like average because if you have multiple value the measure fall in error because it need only one value to multiply).
The dax formula looks like :
= COUNTROWS(('Calendar')) * Sum(Machine[Hours function])
You can then display this measure filtered by the Machine Name and a date slicer(based on your calendar table).
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.
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.