I am trying create a report that calcualtes the Overtime someone has worked in a week, my understanding of the calulation would be.
My Columns are :
Extra Hours Worked Per Week
Total Hour Worked Per Week
Calculation
Extra Hours Worked Per Week / (Extra Hours Worked Per Week + Total Hour Worked Per Week) * 100
If I represent All the columns as minutes sum them up and do the calculation I get one figure but if I sum up all the minutes in to hours and minutes and do the same calculation I get a different figure. What I want to know is, is the Calculation correct and if so, should I be doing the calculation just using minutes or using hours and minutes.
Hope someone can help.
Assuming you want to calculate the percentage of Extra hours, your calculation should be:
((TotalHours * 100)/(TotalHours - ExtraHours))-100
And my advise to you is to keep the calculation in minutes, and in the end convert it to hours (and minutes).
Related
Hi guys i want to calculate number of nights between two given date and times in flutter
for example
From date and time
"28-12-2021 16:00:00"
To date and time
"04-01-2022 23:59:00"
can any one help to achieve this in better way
Note:-
3hour consider as 1/4 night in between (6pm to 6am)
6hour consider as 1/2 night in between (6pm to 6am)
9hour consider as 1/3 night in between (6pm to 6am)
12 hour consider as 1 night (6pm to 6am)
You can get the number of hours between two date
final hourNumber = secondDate.difference(firstDate).inHours;
I'm trying to understand if it's possible to calculate a 1 month sum of revenue data in one of my measurements. For each day, I would like the sum of the previous 30 days.
Is this possible in InfluxDB or through Grafana's query interface?
A moving average is a moving sum, divided by the number of samples. So if you want a moving sum of the past 30 values:
select 30*moving_average(field_name, 30) from measurement
Edited to add:
As Peter Halicky points out in the comments, this is is not the past 30 days. It's the past 30 data points.
If you will always have data for every single day, it's not an issue.
If you're missing a day's data, you'll still get a 30-sample average, but it'll stretch over 31 days instead of 30.
If you don't actually care about the calendar, but want to know the past 30 days of activity, this is not a problem.
If it is a problem, there are a few work-arounds. One that's probably trickier than it sounds: ensure that there is always an entry for each day.
A more robust way is to have the reporting app do this in two steps. Something like this (haven't worked out all the details, but you get the idea):
find the number of data points in the past 30 days, using a query like select count(field_name) from measurement where time > now() - 30d.
Use this number (call it n) to form the query: select n*moving_average(field_name, n) from measurement where time > now - 30d.
Yes, definitely it's possible.
Just set this part of your query like this:
SELECT sum("value") FROM "YOUR_TAG_NAME"
WHERE $timeFilter GROUP BY time(30d) fill(null)
Just make sure that your dashboard time included Last 30 days (at least).
I'm in healthcare and we're trying to assess the number of discharges we have per hour of day, but we'd also like to be able to filter them down by day of week, or specific month, or even a particular day of week in a particular month (e.g. " what is the average number of discharges per hour on Mondays in January?")
I'm confident that Tableau can do this, but haven't been able to make the averages show up in my line graph... every time that I convert it from COUNT to AVG, the line simply goes straight. I got close when I did a table calculation to find the Average (dividing the count per hour by the number of days captured in the report), but when I add a filter for either the month or day of week, selecting one of the options of the filter reduces the total number that is being counted, rather than re-averaging the non-filtered items. (i.e. if the average of the 7 days of the week is "10" for a particular hour, and I deselect the first three days of the week, it's now saying that my average for that hour is roughly 6, despite the fact that all of the days are very close to 10 at that hour.)
Currently, my data table has the following columns:
Account#/MonthYear/HourOfDay/DayOfWeek
ex.12345678/ Jan-17 / 12 /Sunday
I would just create a few calculated fields to differentiate the parts of the calendar you might want to filter/aggregate on. Mixing the month and day of the week with filtering is pretty straight forward with the calculated fields. Then do standard summing to get what you are looking for because an average count of records is always one unless you are throwing some other calculation into the mix. I threw a quick example up on Tableau Public for you to get the idea.
I am trying to calculate an expression in Tableau 10.2 for a contact center use case.
I have calls at every hour all days of the week.
I need to calculate the average call per hour per day. For instance i need to calculate the average call every Sunday at 9 pm and use that in tool tip.
By this i am measuring how many average calls we get on a given Sunday or any other day of the week at a particular hour.
I had written an expression sadly that is not resulting in accurate number
AVG({ FIXED [Weekday Flagging],[Hour]:
AVG([Volume])})
Do suggest.
Very Recently I had a same requirement to see avg visitors on the hours of all the days of a week. My requirement was (Total No. Of Visitors on Sundays/No.Of Sundays) and then (Total No of Visitors #hour/No. Of Sundays).
1)create a calculated field : sum(volume)/countd(date) and name it 'Avg Volume'
2)drag date to 'Columns'. From the drop down click 'More' -> 'Weekday'
3)drag the calculated field to rows. This will give avg volume on each days of a week.
To get Avg Volume of hours
1)do the same procedure as above and instead of 'Weekday', drag Hour of the day to the column.
Link these 2 sheets using an action filter, so that if u click on sunday in the first sheet, it will show the avg volume of each hour of sunday in the second sheet.
I know there must be a simple way that I can learn to do this but I cannot imagine how to start. I am tasked with finding a top 10 matching daily wind power time series in a 30-day plus/minus window from the first day in the time series (Jan 1st) matching a single daily wind power time series and it is out of my level of experience in MATLAB. I have successfully done this matching a single time series of the current year with the exact calendar days from previous years, but I need a more robust searching method to find the best correlated time series in a +/- window of time. For example, I'm comparing a 120 day time series (without leap years) with 25 previous years during the same 120-day period (Jan-Apr). The end result will show me the top 10 time series with the years and Julian day or cumulative day listed and a correlation or RMSE value associated with it. My data looks like this arranged in a 365 (days) X 25 (years) array and I thank you very much for your help!
1182573 470528 1638232 2105034 1070466 478257 1096999
879997 715531 1111498 1004556 1894202 1372178 1707984
636173 937769 2119436 742710 1625931 1275567 1228515
967360 1103082 2218855 1643898 1822868 554769 1325642