我正在使用以下aprox 40.000.000行的data.frame：
structure(list(group = c(1003, 1003, 1003, 1003, 1003, 1003,
1003, 1003, 1003, 1003), t_year = c("2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014"), tmonth = c(3,
3, 3, 3, 3, 3, 3, 3, 3, 3), tday = c("02", "02", "02", "02",
"02", "02", "02", "02", "02", "02"), md = c(2507.416244074, 2507.416244074,
2507.416244074, 2507.416244074, 2507.416244074, 2507.416244074,
2507.416244074, 2507.416244074, 2507.416244074, 2507.416244074
), st = c(640722481.20599, 640722481.20599, 640722481.20599,
640722481.20599, 640722481.20599, 640722481.20599, 640722481.20599,
640722481.20599, 640722481.20599, 640722481.20599), bsc = c(255530.960493802,
255530.960493802, 255530.960493802, 255530.960493802, 255530.960493802,
255530.960493802, 255530.960493802, 255530.960493802, 255530.960493802,
255530.960493802), animal = c("HOUSA000062901617", "HOUSA000006684687",
"HO982000202967406", "HOUSA000057341913", "HOUSA000139926709",
"JEUSA000057281350", "HOUSA000056634042", "XXUSA000056639940",
"HOUSA000064279445", "HOUSA000066846844"), ln = c(6L, 2L, 1L,
2L, 4L, 2L, 3L, 2L, 5L, 1L), gluc = c(37892.914163, 100000, 606286.6266,
303143.3133, 303143.3133, 35355.339059, 37892.914163, 37892.914163,
214354.69251, 37892.914163), gluc_cat = c(1L, 1L, 6L, 5L, 5L,
1L, 1L, 1L, 4L, 1L), ol = structure(c(1L, 1L, 2L, 1L, 1L, 1L,
1L, 1L, 1L, 2L), .Label = c("mult", "prim"), class = "factor"),
group_size = c("<2000", "<2000", "<2000", "<2000", "<2000",
"<2000", "<2000", "<2000", "<2000", "<2000"), date = structure(c(16131,
16131, 16131, 16131, 16131, 16131, 16131, 16131, 16131, 16131
), class = "Date"), season = c("Spring", "Spring", "Spring",
"Spring", "Spring", "Spring", "Spring", "Spring", "Spring",
"Spring")), row.names = c(NA, 10L), class = "data.frame")
我想了解一年中每个类别中动物数量的行为。举个例子。在夏季，其中30％的动物的葡萄糖<200.000（Gluc_cat 1），2％的动物介于200.000至400.000（gluc_cat 2），15％的动物在400.000至600.000（gluc_cat 3）等，依此类推
尝试按tyear，ol和季节按频率标签显示每只gluc_cat内的动物数量，如下所示：
year 2018
ol "prim"
season
gluc_cat Fall Spring Summer Winter
1 16.387677 11.653786 11.719490 10.978675
2 8.307579 5.189070 4.725884 3.862277
3 9.730989 6.571146 3.427911 4.223216
4 3.991289 2.919394 2.877867 4.922916
5 9.224311 4.429528 7.717457 10.597084
6 52.358155 69.237076 69.531391 65.415832
year 2018
ol "mult"
season
gluc_cat Fall Spring Summer Winter
1 16.387677 11.653786 11.719490 10.978675
2 8.307579 5.189070 4.725884 3.862277
3 9.730989 6.571146 3.427911 4.223216
4 3.991289 2.919394 2.877867 4.922916
5 9.224311 4.429528 7.717457 10.597084
6 52.358155 69.237076 69.531391 65.415832
我尝试了以下代码：
freq <- prop.table(xtabs(glucose~gluc_cat+season+ord_lact,cabt2),2)*100
freq
但是我想我正在获取葡萄糖值的频率，对吧？实际上，我想知道每种葡萄糖（gluc_cat）类别中按年，ol和季节变化的动物数量的变化。