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很抱歉,如果这是一个重复的问题,但我找不到问题的答案。
我有一个当前的数据框:
深度 Year Counts Depth.1 Year.1 Counts.1 Depth.2 Year.2 Counts.2
等等
我想创建一个数据框,它只是深度年份和 3 个单独列中的计数。
我认为以下内容会起作用,但事实并非如此。有谁知道我哪里出错了?
library(data.table)
A <- melt(df, id.vars="Depth","Year","Counts")
structure(list(Depth = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5), Year = c(2001.539328,
2001.57432, 2001.609313, 2001.644306, 2001.679298, 2001.714291
), Counts = c(2.87e-06, 3.56e-06, 4.38e-06, 5.36e-06, 6.52e-06,
7.94e-06), Depth.1 = c(1.5, 1.5, 1.5, 1.5, 1.5, 1.5), Year.1 = c(1984.293532,
1984.364339, 1984.435146, 1984.505954, 1984.576761, 1984.647568
), Counts.1 = c(1.46e-06, 1.81e-06, 2.22e-06, 2.73e-06, 3.34e-06,
4.07e-06), Depth.2 = c(2.5, 2.5, 2.5, 2.5, 2.5, 2.5), Year.2 = c(1981.470822,
1981.544366, 1981.61791, 1981.691454, 1981.764998, 1981.838542
), Counts.2 = c(1.59e-06, 1.98e-06, 2.45e-06, 3.01e-06, 3.7e-06,
4.53e-06), Depth.3 = c(3.5, 3.5, 3.5, 3.5, 3.5, 3.5), Year.3 = c(1977.871611,
1977.945227, 1978.018842, 1978.092458, 1978.166074, 1978.239689
), Counts.3 = c(1.52e-06, 1.9e-06, 2.34e-06, 2.89e-06, 3.56e-06,
4.35e-06), Depth.4 = c(4.5, 4.5, 4.5, 4.5, 4.5, 4.5), Year.4 = c(1973.91751,
1973.996106, 1974.074703, 1974.1533, 1974.231896, 1974.310493
), Counts.4 = c(2.68e-06, 3.35e-06, 4.17e-06, 5.2e-06, 6.44e-06,
7.93e-06), Depth.5 = c(5.5, 5.5, 5.5, 5.5, 5.5, 5.5), Year.5 = c(1968.953544,
1969.036898, 1969.120252, 1969.203607, 1969.286961, 1969.370316
), Counts.5 = c(1.17e-06, 1.47e-06, 1.84e-06, 2.28e-06, 2.81e-06,
3.47e-06), Depth.6 = c(6.5, 6.5, 6.5, 6.5, 6.5, 6.5), Year.6 = c(1962.314375,
1962.408079, 1962.501784, 1962.595488, 1962.689193, 1962.782897
), Counts.6 = c(1.5e-06, 1.95e-06, 2.5e-06, 3.18e-06, 4.02e-06,
5.09e-06), Depth.7 = c(7.5, 7.5, 7.5, 7.5, 7.5, 7.5), Year.7 = c(1958.713624,
1958.805065, 1958.896505, 1958.987945, 1959.079385, 1959.170826
), Counts.7 = c(1.12e-06, 1.43e-06, 1.8e-06, 2.25e-06, 2.8e-06,
3.49e-06), Depth.8 = c(8.5, 8.5, 8.5, 8.5, 8.5, 8.5), Year.8 = c(1951.664415,
1951.763029, 1951.861644, 1951.960258, 1952.058872, 1952.157487
), Counts.8 = c(1.03e-06, 1.31e-06, 1.66e-06, 2.09e-06, 2.61e-06,
3.23e-06), Depth.9 = c(9.5, 9.5, 9.5, 9.5, 9.5, 9.5), Year.9 = c(1945.090332,
1945.195825, 1945.301319, 1945.406813, 1945.512306, 1945.6178
), Counts.9 = c(9.86e-07, 1.26e-06, 1.6e-06, 2.01e-06, 2.51e-06,
3.13e-06), Depth.10 = c(10.5, 10.5, 10.5, 10.5, 10.5, 10.5),
Year.10 = c(1935.501068, 1935.619252, 1935.737435, 1935.855618,
1935.973801, 1936.091984), Counts.10 = c(1.65e-06, 2.1e-06,
2.65e-06, 3.32e-06, 4.15e-06, 5.17e-06), Depth.11 = c(11.5,
11.5, 11.5, 11.5, 11.5, 11.5), Year.11 = c(1925.293378, 1925.407495,
1925.521611, 1925.635728, 1925.749844, 1925.863961), Counts.11 = c(9.04e-07,
1.13e-06, 1.4e-06, 1.72e-06, 2.1e-06, 2.58e-06), Depth.12 = c(12.5,
12.5, 12.5, 12.5, 12.5, 12.5), Year.12 = c(1915.470281, 1915.590233,
1915.710185, 1915.830138, 1915.95009, 1916.070042), Counts.12 = c(1.18e-06,
1.45e-06, 1.78e-06, 2.17e-06, 2.65e-06, 3.23e-06), Depth.13 = c(13.5,
13.5, 13.5, 13.5, 13.5, 13.5), Year.13 = c(1907.029774, 1907.144991,
1907.260209, 1907.375426, 1907.490644, 1907.605861), Counts.13 = c(1.33e-06,
1.68e-06, 2.11e-06, 2.62e-06, 3.24e-06, 4.02e-06), Depth.14 = c(14.5,
14.5, 14.5, 14.5, 14.5, 14.5), Year.14 = c(1896.291234, 1896.410534,
1896.529835, 1896.649135, 1896.768436, 1896.887736), Counts.14 = c(8.64e-07,
1.1e-06, 1.39e-06, 1.75e-06, 2.2e-06, 2.74e-06), Depth.15 = c(15.5,
15.5, 15.5, 15.5, 15.5, 15.5), Year.15 = c(1889.864627, 1889.969479,
1890.074332, 1890.179184, 1890.284037, 1890.388889), Counts.15 = c(1.05e-06,
1.36e-06, 1.75e-06, 2.22e-06, 2.81e-06, 3.55e-06), Depth.16 = c(16.5,
16.5, 16.5, 16.5, 16.5, 16.5), Year.16 = c(1886.325239, 1886.425704,
1886.526169, 1886.626634, 1886.727099, 1886.827564), Counts.16 = c(1.27e-06,
1.68e-06, 2.21e-06, 2.89e-06, 3.73e-06, 4.77e-06), Depth.17 = c(17.5,
17.5, 17.5, 17.5, 17.5, 17.5), Year.17 = c(1882.108412, 1882.108412,
1882.108412, 1882.108412, 1882.108412, 1882.108412), Counts.17 = c(1.38e-06,
1.86e-06, 2.47e-06, 3.24e-06, 4.22e-06, 5.45e-06), Depth.18 = c(18.5,
18.5, 18.5, 18.5, 18.5, 18.5), Year.18 = c(1864.178957, 1864.300768,
1864.422579, 1864.544389, 1864.6662, 1864.788011), Counts.18 = c(1.1e-06,
1.52e-06, 2.08e-06, 2.81e-06, 3.73e-06, 4.9e-06), Depth.19 = c(19.5,
19.5, 19.5, 19.5, 19.5, 19.5), Year.19 = c(1844.224683, 1844.373854,
1844.523025, 1844.672196, 1844.821367, 1844.970538), Counts.19 = c(1.05e-06,
1.52e-06, 2.18e-06, 3.07e-06, 4.25e-06, 5.78e-06), Depth.20 = c(20.5,
20.5, 20.5, 20.5, 20.5, 20.5), Year.20 = c(1826.063901, 1826.239023,
1826.414145, 1826.589268, 1826.76439, 1826.939512), Counts.20 = c(7.96e-07,
1.1e-06, 1.5e-06, 2.02e-06, 2.68e-06, 3.53e-06), Depth.21 = c(21.5,
21.5, 21.5, 21.5, 21.5, 21.5), Year.21 = c(1794.869238, 1795.097941,
1795.326644, 1795.555348, 1795.784051, 1796.012754), Counts.21 = c(5.72e-07,
7.74e-07, 1.03e-06, 1.37e-06, 1.81e-06, 2.36e-06), Depth.22 = c(22.5,
22.5, 22.5, 22.5, 22.5, 22.5), Year.22 = c(1776.381101, 1776.645157,
1776.909213, 1777.173268, 1777.437324, 1777.70138), Counts.22 = c(4.57e-07,
6.08e-07, 7.98e-07, 1.04e-06, 1.34e-06, 1.72e-06), Depth.23 = c(23.5,
23.5, 23.5, 23.5, 23.5, 23.5), Year.23 = c(1766.787508, 1767.066229,
1767.344949, 1767.62367, 1767.90239, 1768.181111), Counts.23 = c(4.28e-07,
5.65e-07, 7.39e-07, 9.57e-07, 1.23e-06, 1.57e-06), Depth.24 = c(24.5,
24.5, 24.5, 24.5, 24.5, 24.5), Year.24 = c(1724.904818, 1725.249971,
1725.595125, 1725.940278, 1726.285432, 1726.630586), Counts.24 = c(3.85e-07,
5.28e-07, 7.13e-07, 9.51e-07, 1.25e-06, 1.63e-06), Depth.25 = c(25.5,
25.5, 25.5, 25.5, 25.5, 25.5), Year.25 = c(1666.304304, 1666.747587,
1667.19087, 1667.634153, 1668.077436, 1668.520719), Counts.25 = c(3.14e-07,
4.35e-07, 5.93e-07, 7.99e-07, 1.07e-06, 1.42e-06), Depth.26 = c(26.5,
26.5, 26.5, 26.5, 26.5, 26.5), Year.26 = c(1646.315863, 1646.752634,
1647.189405, 1647.626176, 1648.062946, 1648.499717), Counts.26 = c(2.97e-07,
4.01e-07, 5.43e-07, 7.26e-07, 9.58e-07, 1.25e-06), Depth.27 = c(27.5,
27.5, 27.5, 27.5, 27.5, 27.5), Year.27 = c(1631.425358, 1631.862129,
1632.298899, 1632.73567, 1633.172441, 1633.609212), Counts.27 = c(3.01e-07,
4.02e-07, 5.39e-07, 7.13e-07, 9.33e-07, 1.21e-06), Depth.28 = c(28.5,
28.5, 28.5, 28.5, 28.5, 28.5), Year.28 = c(1623.821174, 1624.214018,
1624.606862, 1624.999706, 1625.39255, 1625.785393), Counts.28 = c(3.08e-07,
4.09e-07, 5.38e-07, 7.01e-07, 9.11e-07, 1.17e-06), Depth.29 = c(29.5,
29.5, 29.5, 29.5, 29.5, 29.5), Year.29 = c(1612.475829, 1612.864893,
1613.253957, 1613.643021, 1614.032085, 1614.421149), Counts.29 = c(3.4e-07,
4.66e-07, 6.3e-07, 8.4e-07, 1.11e-06, 1.44e-06), Depth.30 = c(30.5,
30.5, 30.5, 30.5, 30.5, 30.5), Year.30 = c(1600.26273, 1600.609876,
1600.957023, 1601.304169, 1601.651316, 1601.998462), Counts.30 = c(4.18e-07,
5.85e-07, 8.07e-07, 1.1e-06, 1.49e-06, 1.99e-06), Depth.31 = c(31.5,
31.5, 31.5, 31.5, 31.5, 31.5), Year.31 = c(1549.137398, 1549.553381,
1549.969364, 1550.385346, 1550.801329, 1551.217311), Counts.31 = c(3.27e-07,
4.48e-07, 6.06e-07, 8.1e-07, 1.07e-06, 1.41e-06), Depth.32 = c(32.5,
32.5, 32.5, 32.5, 32.5, 32.5), Year.32 = c(1379.9456, 1380.656236,
1381.366871, 1382.077507, 1382.788142, 1383.498778), Counts.32 = c(3.71e-07,
5.02e-07, 6.71e-07, 8.88e-07, 1.16e-06, 1.5e-06), Depth.33 = c(33.5,
33.5, 33.5, 33.5, 33.5, 33.5), Year.33 = c(1176.400716, 1177.495517,
1178.590318, 1179.685119, 1180.77992, 1181.874721), Counts.33 = c(1.21e-07,
1.66e-07, 2.24e-07, 2.99e-07, 3.94e-07, 5.13e-07), Depth.34 = c(34.5,
34.5, 34.5, 34.5, 34.5, 34.5), Year.34 = c(984.8733315, 986.2808571,
987.6883826, 989.0959082, 990.5034338, 991.9109593), Counts.34 = c(9.87e-08,
1.37e-07, 1.86e-07, 2.51e-07, 3.34e-07, 4.43e-07), Depth.35 = c(35.5,
35.5, 35.5, 35.5, 35.5, 35.5), Year.35 = c(931.6673674, 933.0776679,
934.4879684, 935.8982688, 937.3085693, 938.7188698), Counts.35 = c(8.67e-08,
1.15e-07, 1.53e-07, 2.01e-07, 2.61e-07, 3.34e-07), Depth.36 = c(36.5,
36.5, 36.5, 36.5, 36.5, 36.5), Year.36 = c(894.7139257, 896.1463371,
897.5787485, 899.01116, 900.4435714, 901.8759828), Counts.36 = c(7.95e-08,
1.04e-07, 1.34e-07, 1.71e-07, 2.19e-07, 2.78e-07), Depth.37 = c(37.5,
37.5, 37.5, 37.5, 37.5, 37.5), Year.37 = c(867.2347826, 868.6591119,
870.0834411, 871.5077704, 872.9320996, 874.3564289), Counts.37 = c(7.45e-08,
9.58e-08, 1.22e-07, 1.54e-07, 1.95e-07, 2.44e-07), Depth.38 = c(38.5,
38.5, 38.5, 38.5, 38.5, 38.5), Year.38 = c(822.8193907, 824.2840456,
825.7487006, 827.2133555, 828.6780105, 830.1426654), Counts.38 = c(7.25e-08,
9.32e-08, 1.19e-07, 1.5e-07, 1.89e-07, 2.37e-07), Depth.39 = c(39.5,
39.5, 39.5, 39.5, 39.5, 39.5), Year.39 = c(780.7261404, 782.1666312,
783.6071219, 785.0476127, 786.4881034, 787.9285942), Counts.39 = c(7.24e-08,
9.24e-08, 1.17e-07, 1.48e-07, 1.86e-07, 2.31e-07), Depth.40 = c(40.5,
40.5, 40.5, 40.5, 40.5, 40.5), Year.40 = c(743.4256597, 744.8411919,
746.2567241, 747.6722563, 749.0877885, 750.5033208), Counts.40 = c(1.09e-07,
1.41e-07, 1.8e-07, 2.29e-07, 2.89e-07, 3.64e-07), Depth.41 = c(41.5,
41.5, 41.5, 41.5, 41.5, 41.5), Year.41 = c(673.4489487, 674.8279538,
676.2069588, 677.5859639, 678.964969, 680.3439741), Counts.41 = c(1.06e-07,
1.36e-07, 1.73e-07, 2.19e-07, 2.77e-07, 3.48e-07), Depth.42 = c(42.5,
42.5, 42.5, 42.5, 42.5, 42.5), Year.42 = c(624.182451, 625.532222,
626.881993, 628.231764, 629.581535, 630.931306), Counts.42 = c(8e-08,
1.03e-07, 1.32e-07, 1.67e-07, 2.1e-07, 2.63e-07), Depth.43 = c(43.5,
43.5, 43.5, 43.5, 43.5, 43.5), Year.43 = c(566.5185196, 567.8721804,
569.2258412, 570.579502, 571.9331628, 573.2868236), Counts.43 = c(8.43e-08,
1.1e-07, 1.42e-07, 1.83e-07, 2.34e-07, 2.97e-07), Depth.44 = c(44.5,
44.5, 44.5, 44.5, 44.5, 44.5), Year.44 = c(518.6933347, 520.014935,
521.3365354, 522.6581358, 523.9797362, 525.3013366), Counts.44 = c(9.23e-08,
1.24e-07, 1.65e-07, 2.16e-07, 2.8e-07, 3.6e-07), Depth.45 = c(45.5,
45.5, 45.5, 45.5, 45.5, 45.5), Year.45 = c(443.0346844, 444.2413453,
445.4480063, 446.6546672, 447.8613282, 449.0679891), Counts.45 = c(1.1e-07,
1.51e-07, 2.04e-07, 2.72e-07, 3.59e-07, 4.67e-07), Depth.46 = c(46.5,
46.5, 46.5, 46.5, 46.5, 46.5), Year.46 = c(368.5762277, 369.8150017,
371.0537756, 372.2925496, 373.5313236, 374.7700976), Counts.46 = c(1.54e-07,
2.24e-07, 3.19e-07, 4.49e-07, 6.21e-07, 8.47e-07)), class = c("data.table",
"data.frame"), row.names = c(NA, -6L))
最佳答案
您可以尝试下面的基本 R 代码(不需要 data.table
),使用 stack
+ unstack
res <- unstack(
transform(
stack(df),
ind = gsub("\\..*", "", ind)
)
)
给出
> head(res, 20)
Counts Depth Year
1 2.87e-06 0.5 2001.539
2 3.56e-06 0.5 2001.574
3 4.38e-06 0.5 2001.609
4 5.36e-06 0.5 2001.644
5 6.52e-06 0.5 2001.679
6 7.94e-06 0.5 2001.714
7 1.46e-06 1.5 1984.294
8 1.81e-06 1.5 1984.364
9 2.22e-06 1.5 1984.435
10 2.73e-06 1.5 1984.506
11 3.34e-06 1.5 1984.577
12 4.07e-06 1.5 1984.648
13 1.59e-06 2.5 1981.471
14 1.98e-06 2.5 1981.544
15 2.45e-06 2.5 1981.618
16 3.01e-06 2.5 1981.691
17 3.70e-06 2.5 1981.765
18 4.53e-06 2.5 1981.839
19 1.52e-06 3.5 1977.872
20 1.90e-06 3.5 1977.945```
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我必须编写一个程序来读取文件中的所有单词,并确定每个单词使用了多少次。我的任务是使用多线程来加快运行时间,但是单线程程序的运行速度比多线程程序快。我曾尝试研究此问题的解决方案,但很多解释只会让我更加困
假设我在给定的范围内有一个位置pos,这样: 0 = newRange*newRange : "Case not supported yet"; // Never happens in my code
我试图在 Java 中将 unix 时间四舍五入到该月的第一天,但没有成功。示例: 1314057600 (Tue, 23 Aug 2011 00:00:00 GMT) 至 1312156800
我们的项目有在 CVS 中从现有分支创建新分支的历史。几年后,这导致了每次发布时更改的文件上的这种情况: 新版本:1.145.4.11.2.20.2.6.2.20.2.1.2.11.2.3.2.4.4
我有以下数据框: DAYS7 <- c('Monday','Tuesday','Wednesday','Thursday','Friday', 'Saturday', 'Sunday') DAYS
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