First, don't use a string array to hold the numeric data -- you don't show us how you got to the above, but if it's coming from a file, use readtable to import it instead of whatever you did...
Given that, then use
tD=array2table(data,"VariableNames",{'Date Range','Lat','Lon'});
tD.("Date Range")=categorical(tD.("Date Range"));
tD.Lat=str2double(tD.Lat);
tD.Lon=str2double(tD.Lon);
tD.SomeVariable=randi(100,size(tD.Lat))
tGrpMean=groupsummary(tD,{'Lat','Lon'},'mean','SomeVariable')
tD =
7×4 table
Date Range Lat Lon SomeVariable
___________________ ___ ___ ____________
20101024 _ 20101031 416 826 38
20101024 _ 20101031 416 826 60
20101024 _ 20101031 415 826 6
20101024 _ 20101031 415 827 44
20101024 _ 20101031 415 827 16
20101024 _ 20101031 415 827 84
20101024 _ 20101031 415 827 55
tGrpMean =
3×4 table
Lat Lon GroupCount mean_SomeVariable
___ ___ __________ _________________
415 826 1 6
415 827 4 49.75
416 826 2 49
>>
using the data above and working around the unfortunate choice of using string array...
