32489fab-defb-4c1f-948d-819027f32462 4 4 5 decimal

&[DATE] &[TIME] - &[FILENAME]

Money 11182520001030780000117900500094208600015621700074328000920370009760700083857000964390003044580003146380007240490001243407000124763600023026000002442157000237976400024214830002498100000244190000019397000001709200000231 mat :

Data for Wendy's net earnings: 1118252000 1030780000 1179005000 942086000 156217000 74328000 92037000 97607000 83857000 96439000 304458000 314638000 724049000 1243407000 1247636000 2302600000 2442157000 2379764000 2421483000 2498100000 2441900000 1939700000 1709200000

idx 1 Money rows range :

Wendy idx Money 1000000 / augment :

Stem construction over a data set data Stem stemX 1 data rows range : i 1 stemX rows range stem i el data i 1 el data i 2 el data i 1 el 022 mat : for i 1 stem rows 1 - range stem i el stem i el stem i 1 + (1 el 1 el 012 mat stack : for V stem 1 el : j 2 stem rows 1 - range V V stem j el stack : for V V data data rows row stack : 71 line :

Wendy Stem 0 2 1 sys

On the last 3 earnings, you can linearly interpolate/extrapolate. Wise not to extrapolate > 3 predict