R table（）输出到csv文件

我使用R函数，table（）和write.table（），分别计算单元格数并保存到本地方向作为.csv文件。 但有两个问题：

生成的表的标题是一组月份，但排名根据首字母，而不是日历月份顺序。
我知道一个解决方案是将月份分解，但是，数据包括40多个月。
那么，有没有其他解决办法

生成的表格标题长度比表格宽度小一个，因此，在.csv文件中，标题不适合其列，而适合下一列

---

TabCDY在这种情况下，您可能会发现使用
data.frame
（或类似于
data.table
）更容易

由于排序应该是自动完成的，所以月数对于因子分解来说并不重要

样本数据：

library(data.table)
NN = 1e5
set.seed(39439)
DT = data.table(
  CounterID = sample(LETTERS, NN, TRUE),
  # integer values of 2019-01-01 -> 2019-12-31
  date = format(.Date(sample(17897:18261, NN, TRUE)), '%Y %b')
)

您可以尝试：

# old approach
table(DT$CounterID, DT$date)

# suggested approach
levels = unique(DT$date)
# %Y %b is not enough for as.Date, we have to manually supply the day too
levels_date = as.Date(paste(levels, '01'), format = '%Y %b %d')
# sort by the order as a Date (i.e. chronologically)
levels = levels[order(levels_date)]
# levels determines the sorting order
DT[ , date := factor(date, levels = levels)]
# dcast automatically uses this sorting order
TabCDY = DT[ , dcast(.SD, CounterID ~ date, fun.aggregate = length)]
#output to file
fwrite(TabCDY, 'Tab_CounterDayNumber_Year.csv')

# old approach
table(DT$CounterID, DT$date)

# suggested approach
levels = unique(DT$date)
# %Y %b is not enough for as.Date, we have to manually supply the day too
levels_date = as.Date(paste(levels, '01'), format = '%Y %b %d')
# sort by the order as a Date (i.e. chronologically)
levels = levels[order(levels_date)]
# levels determines the sorting order
DT[ , date := factor(date, levels = levels)]
# dcast automatically uses this sorting order
TabCDY = DT[ , dcast(.SD, CounterID ~ date, fun.aggregate = length)]
#output to file
fwrite(TabCDY, 'Tab_CounterDayNumber_Year.csv')