Anyone have any idea what these strange gaps in a line graph of revenue for the fiscal by week would be? Dark blue is the current fiscal year, and I can’t figure out why it’s not just stopping with the current OR has a straight line through the end of the fiscal.
Thanks!
Hi Emily,
You don't have data for weeks 32 & 33 for 2023 so it's blank (you did for 2022). If you want to join that gap the script for that is in the analytic Coffee! wiki HERE
This is from David Judd (and Ragan Rhodes) here
Edit the widget, and from the upper-right (...) menu, select Edit Widget Code. This will open a new tab. Paste this code in: widget.on("beforeviewloaded",function(scope, args){ args.options.plotOptions.series.connectNulls = true; });
Edit the widget, and from the upper-right (...) menu, select Edit Widget Code. This will open a new tab.
Paste this code in:
widget.on("beforeviewloaded",function(scope, args){ args.options.plotOptions.series.connectNulls = true; });
That helped some! The points are connected now, but it's still showing some data points for weeks 37-onward. I used the expanded https://community.tessituranetwork.com/topical_groups/analytics-coffee/w/wiki/793/removing-data-markers-for-isolated-single-data-points code, and I'm still seeing the points. I did a pivot table to double-check, and there aren't any future-dated gifts coming up that should be getting pulled.
Yep 100% on that one
It's contributions right? So for dates 37 weeks + that look sketchy the mission here is to find out who they are (which annoying ly I find fun). There are a couple of ways to do that and a couple of hypothesis as to why they are there.
My first guess looking at the dash board is that ...
eg: a dot point 37+ weeks might be for 2023 Individual Giving (FYear 2023). But if the Contribution date is 18 September 2022 then it's both in the 37th week of the year it was labeled but also in the 2023 Campaign fiscal year bucket.
To test firstly I'd make a copy of the widget so you don't undo the good work in playing. Now you can try to click on an errant data point and drill down to find the Constituent ID or display name. You can also change the widget filter to equals 37 weeks (or between 36 and 38), then change the line graph into a pivot table and add in categorites like Name and Constituent ID etc until you can reliably go into a persons account and find the reason behind it.
Just a couple of thoughts. Unfortunately I'm don't have analytics over here yet (I miss it) but I think that's in the right direction.
Thanks so much Heath, I'll dive in! I did already try the pivot table trick, and alas that it didn't find the secret.
Let me know if you want to do a quick walk through