删除r中数据框中大于和小于字符数和小数位数

时间:2018-04-20 13:50:39

标签: r dataframe

我的数据框有2个变量

structure(list(X1 = structure(c(17L, 27L, 6L, 1L, 28L, 1L, 1L,4L, 17L, 28L, 28L, 12L, 21L, 28L, 28L, 8L, 28L, 1L, 1L, 10L, 4L, 21L, 30L, 1L, 8L, 28L, 1L, 1L, 1L, 1L, 8L, 1L, 17L, 1L, 1L, 28L, 8L, 23L, 15L, 23L, 25L, 13L, 8L, 4L, 28L, 10L, 1L, 30L, 13L, 4L, 1L, 1L, 17L, 13L, 13L, 8L, 4L, 4L, 4L, 28L, 28L, 13L,1L, 4L, 28L, 1L, 1L, 1L, 1L, 1L, 12L, 2L, 6L, 1L, 8L, 1L, 21L, 1L, 21L, 1L, 30L,13L, 25L, 17L, 1L, 28L, 13L, 1L, 1L, 1L, 1L,8L, 30L, 25L, 28L, 4L, 1L, 13L, 17L, 4L,1L, 1L, 28L, 1L, 1L, 8L, 1L, 8L, 1L, 13L, 1L, 1L, 1L, 4L, 6L, 1L, 1L, 30L,1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 6L, 1L, 15L, 21L, 10L, 21L, 1L, 10L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 28L, 28L, 1L, 30L, 15L, 25L, 6L, 17L, 25L, 15L, 8L, 18L, 22L, 14L, 22L, 28L, 30L, 3L, 30L, 14L, 18L, 22L, 24L, 10L, 26L, 26L, 18L, 26L, 30L, 29L, 18L, 14L, 9L, 9L, 16L, 16L, 29L, 18L, 16L, 27L, 24L, 14L, 26L, 5L, 22L, 28L, 22L, 11L, 9L, 26L, 30L, 18L, 28L, 16L, 26L, 7L, 30L, 7L, 28L, 5L, 18L, 9L, 26L, 24L, 27L, 16L, 16L, 14L, 26L, 29L, 5L, 22L, 24L, 26L, 18L, 27L, 9L, 18L, 11L, 14L, 18L, 22L, 29L, 26L, 22L, 26L, 20L, 24L, 14L, 7L, 16L, 24L, 26L, 29L, 24L, 24L, 24L, 20L, 20L, 24L, 11L, 20L, 29L, 16L, 18L, 24L, 24L, 7L, 24L, 18L, 11L, 11L, 24L, 24L, 7L, 11L, 18L, 24L, 24L, 16L, 29L, 7L, 30L, 24L, 22L, 24L, 18L, 26L, 9L, 9L, 24L, 29L, 9L, 24L, 30L, 11L, 24L, 16L, 26L, 26L, 26L, 30L, 26L, 16L, 26L, 24L, 29L, 20L, 24L, 14L, 9L, 7L, 29L, 29L, 15L, 6L, 15L, 2L, 6L, 6L, 3L, 2L, 17L, 30L, 27L, 23L, 2L, 15L, 8L, 13L, 21L, 28L, 23L, 25L, 1L, 25L, 19L, 27L, 23L, 15L, 19L, 19L, 23L, 2L, 27L, 27L, 15L, 2L, 2L, 3L, 23L, 2L, 23L, 6L, 2L, 15L, 13L,1L, 1L, 13L, 28L, 1L, 1L, 28L, 21L, 1L, 28L, 4L, 1L, 17L, 17L, 13L, 21L, 1L, 1L, 1L, 17L, 1L, 1L, 17L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 13L, 1L, 1L, 1L, 1L, 8L,25L, 1L, 28L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 8L, 4L, 1L, 25L, 28L, 13L, 1L, 1L, 28L, 1L, 4L, 1L, 1L, 8L, 1L, 8L, 13L, 4L, 28L, 21L, 28L, 28L, 28L, 28L, 28L, 8L, 1L, 1L, 1L, 1L, 13L, 21L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 28L, 4L, 1L, 17L, 17L, 28L, 1L, 13L, 8L, 17L, 1L, 13L, 13L, 8L, 4L, 1L, 17L, 25L, 1L, 1L, 8L, 8L, 1L, 4L, 17L, 21L),
                              .Label = c("<8", ">1024", "1024", "11", "11.000000000000007", "128", "128.00000000000009", "16", "16.000000000000007", "181", "181.00000000000006", "22", "23", "23.000000000000011", "256", "256.00000000000017", "32", "32.000000000000014", "362", "362.00000000000017", "45", "45.000000000000014", "512", "512.00000000000045", "64", "64.000000000000028", "724", "8", "8.0000000000000018", "90"),
                              class = "factor"),
               X2 = structure(c(7L, 2L, 2L, 8L, 18L, 4L, 13L, 18L, 8L, 13L, 8L, 18L, 12L, 13L, 18L, 16L, 7L, 5L, 1L, 16L, 18L, 18L, 18L, 12L, 7L, 1L, 4L, 4L, 2L,16L, 12L, 12L, 2L, 2L, 13L, 13L, 18L, 2L, 16L, 2L, 16L, 16L, 2L, 12L, 16L, 2L, 12L,2L, 2L, 16L, 16L, 2L, 2L, 2L, 2L, 2L, 7L, 18L, 18L, 18L, 13L, 18L, 13L, 18L, 9L, 13L, 8L, 4L, 1L, 13L, 8L, 2L, 16L, 12L, 7L, 7L, 18L, 18L, 18L, 12L, 16L, 7L, 16L, 7L, 12L, 12L, 16L, 12L, 13L, 13L, 12L, 16L, 12L, 12L, 7L, 7L, 13L,16L, 7L, 18L, 16L, 13L, 18L, 4L, 12L, 7L, 4L, 18L, 18L, 18L, 9L, 17L, 13L, 7L, 12L, 7L, 18L, 12L, 18L, 13L, 9L, 1L, 18L, 1L, 13L, 13L, 13L, 1L, 1L, 13L, 12L, 4L, 1L,1L, 4L, 12L, 9L, 1L, 1L, 1L, 2L, 12L, 9L, 2L, 18L, 2L, 18L, 7L, 12L, 1L, 9L, 9L, 7L, 18L, 9L, 18L, 1L, 12L, 13L, 12L, 16L, 7L, 12L, 7L, 16L, 2L, 12L,7L, 16L, 12L, 16L, 2L, 12L, 2L, 15L, 7L, 7L, 2L, 7L, 3L, 12L, 16L, 1L, 17L, 2L, 18L, 5L, 7L, 1L, 16L, 7L, 10L, 1L, 12L, 18L, 16L, 16L, 13L, 12L, 7L, 2L, 1L, 9L, 18L, 12L, 13L, 2L, 2L, 12L, 2L, 2L, 2L, 16L, 2L, 1L, 18L, 12L, 7L, 2L, 2L, 12L, 7L, 12L, 4L, 2L, 18L, 13L, 2L, 16L, 7L, 2L, 2L, 12L, 2L, 14L, 12L, 12L, 16L, 1L, 2L, 4L, 2L, 2L, 2L, 17L, 2L, 2L, 2L, 18L, 16L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 12L, 2L, 2L, 1L, 2L, 12L, 18L, 2L, 15L, 16L, 16L, 2L, 2L, 2L, 2L, 11L, 12L, 14L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 16L, 16L, 12L, 2L, 12L, 2L, 2L, 2L, 12L, 2L,16L, 2L, 12L, 14L, 7L, 2L, 4L, 14L, 2L, 16L, 15L, 7L, 16L, 18L, 2L, 16L, 2L, 2L, 12L, 12L, 2L, 2L, 4L, 2L, 2L, 2L, 16L, 2L, 12L,18L, 3L, 16L, 2L, 2L, 13L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 16L, 16L, 2L, 2L, 4L, 4L, 11L, 13L, 4L, 4L, 8L, 4L, 13L, 1L, 4L, 1L, 1L, 2L, 2L, 11L, 18L, 8L, 8L, 4L, 7L, 8L, 4L, 8L, 4L, 4L, 8L, 8L, 1L, 4L, 8L, 4L, 13L, 1L, 6L, 1L, 17L, 2L, 2L, 8L, 18L, 8L, 8L, 4L, 7L, 8L, 17L, 8L, 4L, 1L, 4L, 13L, 1L, 2L, 4L, 16L, 13L, 4L, 4L, 17L, 4L, 7L, 4L, 4L, 1L, 1L, 4L, 1L, 17L, 8L, 1L, 8L, 1L, 4L, 1L, 8L, 8L, 8L, 1L, 13L, 16L, 16L, 17L, 8L, 13L, 1L, 4L, 7L, 1L, 1L, 4L, 4L, 8L, 6L, 4L, 1L, 12L, 13L, 8L, 4L, 4L, 18L, 2L, 4L, 8L, 13L, 17L,13L, 18L, 7L, 16L, 7L, 1L, 13L, 8L, 13L, 4L, 1L, 7L),
                              .Label = c("<8", ">1024", "1024", "11", "128", "16", "181", "22", "23", "256", "32", "362", "45", "512", "64", "724", "8", "90"), class = "factor")),
                              .Names = c("X1", "X2"), 
                              row.names = c(NA, -471L),
                              class = "data.frame")

我有两个问题

1)每个都有一些大于值,一些小于值。我想从数据框中删除><字符,并仅保留数据框中的数字。我可以在excel中完成它,但我想学习在R中学习它的代码。

2)我想将小数位数减少为整数/整数,因为有些小数位数更多。

这可能是一个小问题,但我正在努力做到这一点。我非常感谢你的帮助。

2 个答案:

答案 0 :(得分:2)

  1. 您可以使用dplyr::mutate_allstringr::str_replace_all
  2. 小数由as.numeric直接近似,因为它的大小为10^(-13)

  3. your_df <- structure(list(X1 = structure(c(17L, 27L, 6L, 1L, 28L, 1L, 1L,4L, 17L, 28L, 28L, 12L, 21L, 28L, 28L, 8L, 28L, 1L, 1L, 10L, 4L, 21L, 30L, 1L, 8L, 28L, 1L, 1L, 1L, 1L, 8L, 1L, 17L, 1L, 1L, 28L, 8L, 23L, 15L, 23L, 25L, 13L, 8L, 4L, 28L, 10L, 1L, 30L, 13L, 4L, 1L, 1L, 17L, 13L, 13L, 8L, 4L, 4L, 4L, 28L, 28L, 13L,1L, 4L, 28L, 1L, 1L, 1L, 1L, 1L, 12L, 2L, 6L, 1L, 8L, 1L, 21L, 1L, 21L, 1L, 30L,13L, 25L, 17L, 1L, 28L, 13L, 1L, 1L, 1L, 1L,8L, 30L, 25L, 28L, 4L, 1L, 13L, 17L, 4L,1L, 1L, 28L, 1L, 1L, 8L, 1L, 8L, 1L, 13L, 1L, 1L, 1L, 4L, 6L, 1L, 1L, 30L,1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 6L, 1L, 15L, 21L, 10L, 21L, 1L, 10L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 28L, 28L, 1L, 30L, 15L, 25L, 6L, 17L, 25L, 15L, 8L, 18L, 22L, 14L, 22L, 28L, 30L, 3L, 30L, 14L, 18L, 22L, 24L, 10L, 26L, 26L, 18L, 26L, 30L, 29L, 18L, 14L, 9L, 9L, 16L, 16L, 29L, 18L, 16L, 27L, 24L, 14L, 26L, 5L, 22L, 28L, 22L, 11L, 9L, 26L, 30L, 18L, 28L, 16L, 26L, 7L, 30L, 7L, 28L, 5L, 18L, 9L, 26L, 24L, 27L, 16L, 16L, 14L, 26L, 29L, 5L, 22L, 24L, 26L, 18L, 27L, 9L, 18L, 11L, 14L, 18L, 22L, 29L, 26L, 22L, 26L, 20L, 24L, 14L, 7L, 16L, 24L, 26L, 29L, 24L, 24L, 24L, 20L, 20L, 24L, 11L, 20L, 29L, 16L, 18L, 24L, 24L, 7L, 24L, 18L, 11L, 11L, 24L, 24L, 7L, 11L, 18L, 24L, 24L, 16L, 29L, 7L, 30L, 24L, 22L, 24L, 18L, 26L, 9L, 9L, 24L, 29L, 9L, 24L, 30L, 11L, 24L, 16L, 26L, 26L, 26L, 30L, 26L, 16L, 26L, 24L, 29L, 20L, 24L, 14L, 9L, 7L, 29L, 29L, 15L, 6L, 15L, 2L, 6L, 6L, 3L, 2L, 17L, 30L, 27L, 23L, 2L, 15L, 8L, 13L, 21L, 28L, 23L, 25L, 1L, 25L, 19L, 27L, 23L, 15L, 19L, 19L, 23L, 2L, 27L, 27L, 15L, 2L, 2L, 3L, 23L, 2L, 23L, 6L, 2L, 15L, 13L,1L, 1L, 13L, 28L, 1L, 1L, 28L, 21L, 1L, 28L, 4L, 1L, 17L, 17L, 13L, 21L, 1L, 1L, 1L, 17L, 1L, 1L, 17L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 13L, 1L, 1L, 1L, 1L, 8L,25L, 1L, 28L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 8L, 4L, 1L, 25L, 28L, 13L, 1L, 1L, 28L, 1L, 4L, 1L, 1L, 8L, 1L, 8L, 13L, 4L, 28L, 21L, 28L, 28L, 28L, 28L, 28L, 8L, 1L, 1L, 1L, 1L, 13L, 21L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 28L, 4L, 1L, 17L, 17L, 28L, 1L, 13L, 8L, 17L, 1L, 13L, 13L, 8L, 4L, 1L, 17L, 25L, 1L, 1L, 8L, 8L, 1L, 4L, 17L, 21L), .Label = c("<8", ">1024", "1024", "11", "11.000000000000007", "128", "128.00000000000009", "16", "16.000000000000007", "181", "181.00000000000006", "22", "23", "23.000000000000011", "256", "256.00000000000017", "32", "32.000000000000014", "362", "362.00000000000017", "45", "45.000000000000014", "512", "512.00000000000045", "64", "64.000000000000028", "724", "8", "8.0000000000000018", "90"), class = "factor"), X2 = structure(c(7L, 2L, 2L, 8L, 18L, 4L, 13L, 18L, 8L, 13L, 8L, 18L, 12L, 13L, 18L, 16L, 7L, 5L, 1L, 16L, 18L, 18L, 18L, 12L, 7L, 1L, 4L, 4L, 2L,16L, 12L, 12L, 2L, 2L, 13L, 13L, 18L, 2L, 16L, 2L, 16L, 16L, 2L, 12L, 16L, 2L, 12L,2L, 2L, 16L, 16L, 2L, 2L, 2L, 2L, 2L, 7L, 18L, 18L, 18L, 13L, 18L, 13L, 18L, 9L, 13L, 8L, 4L, 1L, 13L, 8L, 2L, 16L, 12L, 7L, 7L, 18L, 18L, 18L, 12L, 16L, 7L, 16L, 7L, 12L, 12L, 16L, 12L, 13L, 13L, 12L, 16L, 12L, 12L, 7L, 7L, 13L,16L, 7L, 18L, 16L, 13L, 18L, 4L, 12L, 7L, 4L, 18L, 18L, 18L, 9L, 17L, 13L, 7L, 12L, 7L, 18L, 12L, 18L, 13L, 9L, 1L, 18L, 1L, 13L, 13L, 13L, 1L, 1L, 13L, 12L, 4L, 1L,1L, 4L, 12L, 9L, 1L, 1L, 1L, 2L, 12L, 9L, 2L, 18L, 2L, 18L, 7L, 12L, 1L, 9L, 9L, 7L, 18L, 9L, 18L, 1L, 12L, 13L, 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    12L, 16L, 7L, 12L, 7L, 16L, 2L, 12L,7L, 16L, 12L, 16L, 2L, 12L, 2L, 15L, 7L, 7L, 2L, 7L, 3L, 12L, 16L, 1L, 17L, 2L, 18L, 5L, 7L, 1L, 16L, 7L, 10L, 1L, 12L, 18L, 16L, 16L, 13L, 12L, 7L, 2L, 1L, 9L, 18L, 12L, 13L, 2L, 2L, 12L, 2L, 2L, 2L, 16L, 2L, 1L, 18L, 12L, 7L, 2L, 2L, 12L, 7L, 12L, 4L, 2L, 18L, 13L, 2L, 16L, 7L, 2L, 2L, 12L, 2L, 14L, 12L, 12L, 16L, 1L, 2L, 4L, 2L, 2L, 2L, 17L, 2L, 2L, 2L, 18L, 16L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 12L, 2L, 2L, 1L, 2L, 12L, 18L, 2L, 15L, 16L, 16L, 2L, 2L, 2L, 2L, 11L, 12L, 14L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 16L, 16L, 12L, 2L, 12L, 2L, 2L, 2L, 12L, 2L,16L, 2L, 12L, 14L, 7L, 2L, 4L, 14L, 2L, 16L, 15L, 7L, 16L, 18L, 2L, 16L, 2L, 2L, 12L, 12L, 2L, 2L, 4L, 2L, 2L, 2L, 16L, 2L, 12L,18L, 3L, 16L, 2L, 2L, 13L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 16L, 16L, 2L, 2L, 4L, 4L, 11L, 13L, 4L, 4L, 8L, 4L, 13L, 1L, 4L, 1L, 1L, 2L, 2L, 11L, 18L, 8L, 8L, 4L, 7L, 8L, 4L, 8L, 4L, 4L, 8L, 8L, 1L, 4L, 8L, 4L, 13L, 1L, 6L, 1L, 17L, 2L, 2L, 8L, 18L, 8L, 8L, 4L, 7L, 8L, 17L, 8L, 4L, 1L, 4L, 13L, 1L, 2L, 4L, 16L, 13L, 4L, 4L, 17L, 4L, 7L, 4L, 4L, 1L, 1L, 4L, 1L, 17L, 8L, 1L, 8L, 1L, 4L, 1L, 8L, 8L, 8L, 1L, 13L, 16L, 16L, 17L, 8L, 13L, 1L, 4L, 7L, 1L, 1L, 4L, 4L, 8L, 6L, 4L, 1L, 12L, 13L, 8L, 4L, 4L, 18L, 2L, 4L, 8L, 13L, 17L,13L, 18L, 7L, 16L, 7L, 1L, 13L, 8L, 13L, 4L, 1L, 7L), 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  .Label = c("<8", ">1024", "1024", "11", "128", "16", "181", "22", "23", "256", "32", "362", "45", "512", "64", "724", "8", "90"), class = "factor")), .Names = c("X1", "X2"), row.names = c(NA, -471L), class = "data.frame")
    
    library(dplyr)
    library(stringr)
    
    mutate_all(your_df, function(x) as.numeric(str_replace_all(x, pattern = "<|>", replacement = "")))
    
    #>       X1   X2
    #> 1     32  181
    #> 2    724 1024
    #> 3    128 1024
    #> 4      8   22
    #> 5      8   90
    #> 6      8   11
    #> 7      8   45
    #> 8     11   90
    #> 9     32   22
    #> 10     8   45
    #> 11     8   22
    #> 12    22   90
    #> 13    45  362
    

答案 1 :(得分:1)

您可以使用基础R执行此操作:

my_df <- as.data.frame(sapply(my_df, gsub, pattern = "<|>", replacement = ""))
my_df <- as.data.frame(sapply(my_df, as.numeric))

my_df
#                    X1   X2
# 1                   8   23
# 2                   8   90
# 3                   8    8
# 4                   8  362
# 5                   8   45
# 6                  90  362
# 7                 256  724
# 8                  64  181
# 9                 128  362
# 10                 32  181
# 11                 64  724
# 12                256 1024
# 13                 16  362
# 14 32.000000000000014  181
# 15 45.000000000000014  724
# 16 23.000000000000011  362
# 17 45.000000000000014  724
# 18                  8 1024
# 19                 90  362
# 20               1024 1024
# 21                 90   64
# 22 23.000000000000011  181
# 23 32.000000000000014  181
# 24 45.000000000000014 1024
# 25 512.00000000000045  181

如果您只想舍入小数,但保持&lt;和&gt;标志你可以做到以下(没有完成上述步骤):

sapply(my_df, 
       function(x) paste0(gsub(x, pattern = "\\d|\\.", replacement = ""), 
                          round(as.numeric(gsub(x, pattern = "<|>", replacement = "")))))

#      X1     X2     
# [1,] "<8"   "23"   
# [2,] "<8"   "90"   
# [3,] "8"    "<8"   
# [4,] "8"    "362"  
# [5,] "<8"   "45"   
# [6,] "90"   "362"  
# [7,] "256"  "724"  
# [8,] "64"   "181"  
# [9,] "128"  "362"  
# [10,] "32"   "181"  
# [11,] "64"   "724"  
# [12,] "256"  ">1024"
# [13,] "16"   "362"  
# [14,] "32"   "181"  
# [15,] "45"   "724"  
# [16,] "23"   "362"  
# [17,] "45"   "724"  
# [18,] "8"    ">1024"
# [19,] "90"   "362"  
# [20,] "1024" ">1024"
# [21,] "90"   "64"   
# [22,] "23"   "181"  
# [23,] "32"   "181"  
# [24,] "45"   ">1024"
# [25,] "512"  "181" 

工作原理

sapply获取data.frame并将逗号后指定的函数应用于data.frame的每一列。 gsub将模式替换为x中的替换(data.frame的一列)。在那里我使用了正则表达式,因此\\d表示所有数字(0-9)和\\.点和|将它们与OR逻辑组合在一起。

<强> stringr溶液

stringr有一个较短的解决方案:

library(stringr)
sapply(my_df, 
       function(x) str_c(str_extract(x, "[<>]?"), 
                         round(as.numeric(str_extract(x, "\\d+")))))

这里我们想要的模式被提取,然后在舍入小数后再次组合。

数据

my_df <- 
  structure(list(X1 = structure(c(1L, 1L, 28L, 28L, 1L, 30L, 15L, 
                                  25L, 6L, 17L, 25L, 15L, 8L, 18L, 
                                  22L, 14L, 22L, 28L, 30L, 3L, 30L, 
                                  14L, 18L, 22L, 24L), 
                                .Label = c("<8", ">1024", "1024", "11", 
                                           "11.000000000000007", "128", 
                                           "128.00000000000009", "16", 
                                           "16.000000000000007", "181", 
                                           "181.00000000000006", "22", 
                                           "23", "23.000000000000011", 
                                           "256", "256.00000000000017", 
                                           "32", "32.000000000000014", 
                                           "362", "362.00000000000017", 
                                           "45", "45.000000000000014", 
                                           "512", "512.00000000000045", 
                                           "64", "64.000000000000028", 
                                           "724", "8", 
                                           "8.0000000000000018", "90"), 
                                class = "factor"), 
                 X2 = structure(c(9L, 18L, 1L, 12L, 13L, 12L, 16L, 7L, 
                                  12L, 7L, 16L, 2L, 12L, 7L, 16L, 12L, 
                                  16L, 2L, 12L, 2L, 15L, 7L, 7L, 2L, 7L), 
                                .Label = c("<8", ">1024", "1024", "11", 
                                           "128", "16", "181", "22", "23", 
                                           "256", "32", "362", "45", "512", 
                                           "64", "724", "8", "90"), 
                                class = "factor")), 
            .Names = c("X1", "X2"), 
            row.names = c(NA, -25L), 
            class = "data.frame")

#                    X1    X2
# 1                  <8    23
# 2                  <8    90
# 3                   8    <8
# 4                   8   362
# 5                  <8    45
# 6                  90   362
# 7                 256   724
# 8                  64   181
# 9                 128   362
# 10                 32   181
# 11                 64   724
# 12                256 >1024
# 13                 16   362
# 14 32.000000000000014   181
# 15 45.000000000000014   724
# 16 23.000000000000011   362
# 17 45.000000000000014   724
# 18                  8 >1024
# 19                 90   362
# 20               1024 >1024
# 21                 90    64
# 22 23.000000000000011   181
# 23 32.000000000000014   181
# 24 45.000000000000014 >1024
# 25 512.00000000000045   181