Hi Roger,
no that's to part of DateListPlot. Your data after import has these dimensions:
data // Dimensions
(*{1, 21579, 5}*)
That means that it is a list of 21579 lists of five entries. The outer list (corresponding to the 1) comes from the excel spreadsheet. Sometimes these things have multiple pages, but yours doesn't. If I now print out a couple of days it looks like that:
data[[1, 1 ;; 10]] // TableForm
![enter image description here](http://community.wolfram.com//c/portal/getImageAttachment?filename=ScreenShot2016-03-26at19.06.29.png&userId=48754)
As you see the first two rows are just headers and I don't want to plot them. so I only choose the one from 3 to the end. So if I write:
data[[1,3;;]]
that mans take the fist (and only) page of the spreadsheet. Then use rows 3 to the end. If I knew that there are 21579 lines I could also write
data[[1,3;;21579]]
but you see that the the first choice is somewhat shorter and requires less knowledge. It just means take rows 3 to the end. The table also shows that per row there are five entries. I was interested in the first and the third. That is where the {1,3} comes from.
Ok. Once we have done this we can do:
ts = TimeSeries[data[[1, 3 ;;, {1, 3}]]];
rainperday = MovingMap[Total, ts, Quantity[1, "Days"]];
DateListPlot[rainperday]
to get
![enter image description here](http://community.wolfram.com//c/portal/getImageAttachment?filename=ScreenShot2016-03-26at19.11.04.png&userId=48754)
It is easy to see that Mathematica cuts off at about 3.5 so that most of the time series can easily be seen. But you can force it to plot everything:
DateListPlot[rainperday, PlotRange -> All]
![enter image description here](http://community.wolfram.com//c/portal/getImageAttachment?filename=ScreenShot2016-03-26at19.12.29.png&userId=48754)
There is obviously a very large peak at the beginning of 2008 (3rd January?). Given your geolocation, I assume that this is the January 2008 North American storm complex, but that's only a guess. An alternative explanation would be that somebody sprayed it with a watering hose.
It is a beautiful dataset. It could be a challenge for this community to find out where your rain gauge probably was - that can of course only be done with quite some error, but it would be fun...
Cheers,
Marco