I have a set of data containing dates that have been sorted out say from 25th June 2016 till 24th August 2016. I have to add a 'Week' column that numbers the starting week from 1 and incrementing by 1 every time a new week comes in that start on a Sunday. I know a little coding but I have no experience with SAS so I am having a lot of trouble with this. The first week would be a little struggle since it could be that the date does not start with a Sunday and I can't simply reiterate the code 7 times. But the week after would not be too hard since it's only doing a loop everytime the date meets with a new Sunday.
I have a lot of things in my mind, I have been googling and tried coding but to no avail. If anyone could explain to me, that would be really helpful.
Try this
data out;
set in;
Week = 1;
if weekday(date) = 1 then Week + 1;
run;
Consider using the built in WEEK function. Find the first week as your base number and then subtract that to get the increment needed. ie if your first week is 5, then
Week_want = week(date) - 5;
Related
So, strange one to explain...
I have a table with the start dates of each person in project (each start day is the first Monday of the week)
I want to know how many people were in the project on any given week.
If I select two weeks in a slicer, for example
Week1
Week3
And there were 10 people in week 1 and 30 in week 3 the total should be 40.
How do I build a measure to do this.
Essentially I'm asking it to count the number of rows(project members) where the start date is >= each selected date and sum each individual result.
I hope this has made sense unable to share much due to work red tape
Thanks
Lloyd
I would do this in the following way:
Create a bin for the work week
Create a measure to count the bin from step 1.
Run into a problem.
I need to have a yearly reset on an entitlement value but the reset point is a different date for each person. A person gets entitlement 6 months after their start date, so that +6months date is when they should have a reset. Here is the +6months column i made:
+6m = DATE(YEAR('Employee List'[Emp. Dates]),
MONTH('Employee List'[Emp. Dates])+6,
DAY('Employee List'[Emp. Dates]))
I ran into this problem when i saw that the excess was taking away a persons entitlement by the amount of days took throughout their entire time at the company. Here is the measure for Excess:
Excess Days = CALCULATE(SUM('Employee List'[Entitlement]) -
SUM('Leave combined'[Duration1]))
This is taking away all recorded days even from a few years ago.
Can i make a measure that pretty much says if we are past the +6months date (DD/MM(Year doesnt matter i just need the same time every year)), then it will take away their entitlement from that +6months date and will not pick up any days from before the +6months reset?
e.g. if the +6months is March 1 2015, currently it is taking all the days took from their start to today, i want it to reset at every year on March 1 so it would only take data from March 1 2019 - today and will reset once we past March 1 2020. If a person has took 25 days a year on average and they only have 20 days entitlement, it should show they 5 excess days but for me now it is taking the total days took away from their entitlement.
I understand this is hard to explain and you may not get it but i am happy enough to explain.
Dummy Sheet
It is easier to create a calculated column to do this. Perhaps something like:
Calc =
VAR Person = TableA[Person]
VAR Date1 = EDATE(Entitlement[Start Date],6)
RETURN IF(TableA[Start]<Date1,0,TableA[Duration])
This column will make the duration 0, wherever the start date is lesser than the +6m date from entitlement. Once this column is created you can simply sum up the field at whatever level required, to get the desired output. Hope this helps.
I'm currently working on inventory reconciliation, and I've struggling to fill all days of the calendar with the cumulative sum of product we're currently storing:
Inventory level ($). = CALCULATE(SUM(ledger[cost]),FILTER(ALL(DimDate[Date]),DimDate[Date]<=MAX(ledger[Document Date])))
As you guys might notice it has at least 90% of all dates filled, however if we look closely to the graph, we can appreaciate March 5th of 2016 is missing just due to the fact there was no transaction during that day resulting on a blank value. However I'm trying to accomplish retrieving the previous day balance for those days with no transactions. e.g: for March 5th should have $17,038,462.32 (balance for the previous day March 4th).
I'm trying to work on another clause into the measure with functions such as EARLIER or LASTDATE, however I haven't been succesful.
Any insight or solutions works well thank you. Have a nice day.
You are using a wrong date field in your measure. Change it to the field from the Date table:
Inventory level. =
CALCULATE(
SUM(ledger[cost]),
FILTER(ALL(DimDate[Date]),DimDate[Date]<=MAX(DimDate[Date])))
I have a line graph in PowerBI and in my date dimension I have the Week Number for every date (note that this is a custom week number with the week starting on Friday).
Whenever I put it on a the x-axis, PowerBI groups all the weeks together, regarless of year... so Week 1 of year 2015 will be grouped together with Week 1 of 2016...
I think to myself: "Ok, no problem, I'll just add the Year after every week number so I'll have 1-2016, 2-2016, and so on."
Well PowerBI sees this concatenation as a string value so when I put that on the graph, it goes
1-2016, 1-2017, 2-2016, 2-2017, 3-2016, 4-2016, and so on....
I've tried sorting the new column by the old week number column, but it does the same thing. Any suggestions on how to accomplish this?
You're on the right track. I recommend a separate (hidden) sort column that sorts alphabetically (i.e. year first, then 2 digit week). In other words, 1-2016 = 201601.
This way, all the weeks for 2016 sort before the weeks for 2017, and the weeks sort in the right order too. (A 1 digit week would mean 20161 will be followed by 201610, which you don't want either.)
I am currently trying to solve some problems from the USACO training website in preparation for an unrelated C++ programming competition.
However, I am stuck on this problem:
Does the 13th of the month land on a Friday less often than on any other day of the week? To answer this question, write a program that will compute the frequency that the 13th of each month lands on Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, and Saturday over a given period of N years. The time period to test will be from January 1, 1900 to December 31, 1900+N-1 for a given number of years, N. N is non-negative and will not exceed 400.
The number N is provided in an input file and the output is to be a file with seven numbers in it, each representing the number of 13th's falling on a particular day of the week.
I was wondering how you guys would approach this problem. I am not looking for code or anything since that would just defeat the purpose of me doing this, instead just a starting point or an algorithm would be helpful.
So far the only thing I could think of is using the Doomsday Algorithm, however I am unsure about how I would implement that in code.
Any help would be greatly appreciated.
As Denny says, N is so small that you can easily iterate through the months using a table of days-in-a-month and a simple is-a-leap-year predicate to handle February. Just find out what day the 13th of Jan was in 1900 and then add up the elapsed days until 13th Feb, then 13th March etc.. Use a % operator to wrap the # of elapsed days back into a day-of-week value.
N is less than 400? well you just need to go over 365.25*400=146100 days at max. sounds easy to enumerate all of them, convert dates into year/month/date (with your favorite date conversion routine), testing for day of week is trivial.
I would precalculate the table though.
Just use brute force. Like this pseudocode example:
from datetime import date
day_names = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday',
'Saturday', 'Sunday']
counts = [0] * 7
for year in range(1900, 2300):
for month in range(1, 13):
counts[date(year, month, 13).weekday()] += 1
for day, count in zip(day_names, counts):
print('%s: %d' % (day, count))
The "hard" part is calculating the day of the week a date falls on. In C(++), you can use the mktime and localtime library functions if you know that your platform handles a large enough date range.