![]() The high peak and the week being outlier now isn't that surprising because between December and February are the busiest weeks for this organisation. But I can't throw the sales of this week because it is relevant and true data. The 53th of December 2015, which is December 28th until January 3th is grouped with week 1, skewing my data graph. Bug JRASERVER-20014 - JIRA calendar has a first day of the week bug. It was then that I noticed December of 2015 had a week 53. Bug JRASERVER-59423 - Week number in date picker is wrong, from Jan 2016. Find more info on our main week number page. Today, I would like to show you how to retrieve. Please note that there are multiple systems for week numbering, this is the ISO week date standard (ISO-8601), other systems use weeks starting on Sunday (US) or Saturday (Islamic). I agree with DavidK that the formula to convert Weeknrs into dates works for 2015, but not for 2016 (as week 1 starts on 4th of January). Tutorial by Stefan Trost Last update on Created on. When I went back to the limit of December 28th until January 10th, all data was classified as week 1. All weeks are starting on Monday and ending on Sunday. It was then that I noticed that week 52 of 2015 only appeared as soon as I included December 27th. When I took a few more dates before and after this week, I noticed that week 1 was growing the more days I added before week 1 as stated by the calendars (January 4th until January 10th). You get dates like 2014-52 for week -52 where it was week 1 before. So then there must've been some other error. I first tried changing the date format in the Access Query to this: OrderWeek: Format ( OrderDate,'yyyy-ww',1,3) <- But it did not do the trick. Week 52 (2016) Sunday 19th June - Saturday 25th June. Surprisingly, when I explored this week ordered by day, no outlier or total amount was equal to that given the graph. So this would give you the right result for: Week 1 (2017) Sunday 26th June - Saturday 2nd July. I immediately classified this graph point as an outlier so I started investigating this particular week by narrowing the graph down to this week. The total amount was a little more than double of the second highest week and thus a huge peak compared to the others in the graph. When I plotted the totals by week, there was one week that sorely stood out of all the other weeks in 4 years of time, which was week 1 of 2016. The total number of weeks in the year 2016 is 52 weeks. I was plotting some data of a webhop sales order dataset. ![]()
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