agridat: Agricultural Datasets

# shafi.tomato.uniformity.R

dat <- matrix(c(
6560,6642,6724,7298,8528,8774,8200,6560,6314,6150,
6396,6314,6478,6724,7872,7872,7052,6232,5822,5248,
6478,6396,6396,6724,7216,7544,6560,5822,5658,4756,
5986,6068,6150,6478,6970,7216,6560,6150,6396,5166,
5494,5904,6232,6314,6724,7134,6560,6560,6806,5412,
4838,5576,5986,5822,6396,6478,5986,5986,6068,6232,
4674,5248,5740,5658,5740,5904,5740,5822,6150,6314,
5166,5904,6478,6068,5412,5658,5986,6314,6396,5904,
5412,6068,6478,6150,5412,5576,6232,6888,6478,5822,
5166,5904,6396,6314,5576,5576,6232,6642,6642,5658,
4838,5658,6478,5904,5740,5166,5986,6396,6232,5740,
4756,4510,4346,5002,4100,4100,4428,4592,5166,5658,
4592,4018,3444,3936,3608,3526,3362,3034,4428,5494,
3608,3198,2952,3034,3362,3198,2378,2050,3690,4838,
3034,3116,3116,3362,3608,3198,2132,1558,3116,4674,
3526,4592,5166,5494,4510,3198,2542,2050,3116,4182,
3936,5986,6806,6642,4428,3280,2788,2296,3034,3772,
4674,6068,6314,5658,3526,2952,2460,2050,2214,2706,
2378,3690,3608,3444,2624,2706,2378,1968,2132,2542,
1066,1640,2056,1640,1804,2132,1886,1968,2132,2460), ncol=10, byrow=TRUE)/1000

dat <- reshape2::melt(dat)
names(dat) <- c("row","col","yield")

shafi.tomato.uniformity <- dat
kw::agex(shafi.tomato.uniformity, prompt=FALSE)