我有一点 data.frame （现在是 xts 的时间戳，我希望这不是问题），像这样：
> head(testData)
Year Day Hour Min Sec. E1.S1 E1.S2 E1.S3 E1.S4 E1.S5 E1.S6
2000-05-01 10:25:59 2000 122 10 25.0 35.144 3.572000 2.912000 2.512 6.352 10.604000 8.078
2000-05-01 10:26:48 2000 122 10 26.0 31.570 2.203333 2.423333 6.160 13.000 9.463333 3.970
2000-05-01 10:27:48 2000 122 10 26.8 35.964 2.118000 3.044000 4.232 11.770 12.696000 6.088
E1.S7 E1.S8 E2.S1 E2.S2 E2.S3 E2.S4 E2.S5 E2.S6 E2.S7
2000-05-01 10:25:59 3.0444 3.574000 0.9244 1.5868 1.3224 1.852800 2.646000 2.910 2.382000
2000-05-01 10:26:48 3.3100 3.083333 1.1000 1.5440 1.9800 2.646667 2.646667 3.310 1.763333
2000-05-01 10:27:48 2.6440 2.646000 1.8528 1.8524 2.9120 2.648000 3.970000 5.292 1.850000
E2.S8 E3.S1 E3.S2 E3.S3 E3.S4 E3.S5 E3.S6 E3.S7
2000-05-01 10:25:59 1.586000 0.7920000 1.0568000 1.7184 1.720400 2.116400 0.9248 2.1180
2000-05-01 10:26:48 1.983333 0.4413333 0.2206667 1.5400 1.100667 2.646667 0.8800 0.8800
2000-05-01 10:27:48 1.452000 0.9264000 1.1908000 2.5140 1.718400 2.250400 2.2504 1.8504
E3.S8 E4.S1 E4.S2 E4.S3 E4.S4 E4.S5 E4.S6 E4.S7
2000-05-01 10:25:59 1.1880 0.9252000 0.1324000 0.6612 0.6604 0.5288000 0.132400 0.6612000
2000-05-01 10:26:48 2.2040 0.2206667 0.2206667 0.4400 0.4400 0.8813333 1.100667 0.8813333
2000-05-01 10:27:48 0.9240 0.7936000 0.7928000 0.9244 1.3208 0.6612000 0.132400 0.5288000
E4.S8 FP5.S1 FP5.S2 FP5.S3 FP5.S4 FP5.S5 FP5.S6 FP5.S7
2000-05-01 10:25:59 1.0560 0.0662000 0.3310 0.3968000 0.0662000 0.0000000 0.2648000 0.19860
2000-05-01 10:26:48 1.1000 0.1103333 0.3310 0.2206667 0.1103333 0.4413333 0.2206667 0.33100
2000-05-01 10:27:48 0.5288 0.2648000 0.4632 0.0000000 0.4632000 0.2648000 0.2648000 0.72660
FP5.S8 FP6.S1 FP6.S2 FP6.S3 FP6.S4 FP6.S5 FP6.S6 FP6.S7 FP6.S8
2000-05-01 10:25:59 0.2648000 0.1324 0.1986000 0.2648 0.00000 0.1324000 0.1324 0.1324 0.0662000
2000-05-01 10:26:48 0.2206667 0.0000 0.1103333 0.0000 0.00000 0.2206667 0.0000 0.0000 0.1103333
2000-05-01 10:27:48 0.1324000 0.0000 0.0000000 0.0000 0.00000 0.1986000 0.1324 0.1324 0.0662000
FP7.S1 FP7.S2 FP7.S3 FP7.S4 FP7.S5 FP7.S6 FP7.S7 FP7.S8 PA.LEFS60S1
2000-05-01 10:25:59 0.1324 0.0000 0.00000 0.0000 0.1324000 0.3310000 0.0000 0.39680 79.46
2000-05-01 10:26:48 0.0000 0.0000 0.00000 0.0000 0.4413333 0.1103333 0.0000 0.00000 78.50
2000-05-01 10:27:48 0.0000 0.3972 0.00000 0.1324 0.1324000 0.1986000 0.1324 0.00000 84.10
PA.LEFS60S2 PA.LEFS60S3 PA.LEFS60S4 PA.LEFS60S5 PA.LEFS60S6 PA.LEFS60S7
2000-05-01 10:25:59 83.26000 103.48 131.6000 157.6000 148.6000 120.60000
2000-05-01 10:26:48 99.93333 130.00 160.6667 153.6667 121.6667 92.96667
2000-05-01 10:27:48 95.68000 118.60 144.6000 155.0000 134.6000 109.10000
PA.LEFS60S8 BX BY BZ Bmag....nT.
2000-05-01 10:25:59 94.44000 3.608000 2.6620000 5.032000 6.8840
2000-05-01 10:26:48 75.63333 4.943333 -0.5133333 4.816667 6.9300
2000-05-01 10:27:48 89.44000 3.908000 0.9634000 5.490000 6.8460
> dput(head(testData))
structure(c(2000, 2000, 2000, 2000, 2000, 2000, 122, 122, 122,
122, 122, 122, 10, 10, 10, 10, 10, 10, 25, 26, 26.8, 28, 29,
30, 35.144, 31.57, 35.964, 21.4, 24.892, 25.354, 3.572, 2.20333333333333,
2.118, 3.8025, 4.628, 5.292, 2.912, 2.42333333333333, 3.044,
1.488, 3.97, 5.428, 2.512, 6.16, 4.232, 4.465, 3.836, 7.54, 6.352,
13, 11.77, 7.775, 8.604, 14.16, 10.604, 9.46333333333333, 12.696,
10.93, 16.68, 23.96, 8.078, 3.97, 6.088, 10.425, 15.612, 29.1,
3.0444, 3.31, 2.644, 5.135, 10.32, 20.612, 3.574, 3.08333333333333,
2.646, 3.1425, 3.966, 9.918, 0.9244, 1.1, 1.8528, 2.645, 4.368,
8.476, 1.5868, 1.544, 1.8524, 2.315, 3.572, 6.218, 1.3224, 1.98,
2.912, 3.4725, 6.34, 12.832, 1.8528, 2.64666666666667, 2.648,
6.4475, 8.86, 24.74, 2.646, 2.64666666666667, 3.97, 7.275, 12.948,
30.7, 2.91, 3.31, 5.292, 7.44, 12.988, 30.42, 2.382, 1.76333333333333,
1.85, 3.315, 12.174, 32.28, 1.586, 1.98333333333333, 1.452, 2.81,
7.286, 17.72, 0.792, 0.441333333333333, 0.9264, 1.655, 4.234,
10.194, 1.0568, 0.220666666666667, 1.1908, 1.1555, 3.8388, 7.016,
1.7184, 1.54, 2.514, 3.3105, 8.192, 14.004, 1.7204, 1.10066666666667,
1.7184, 4.1375, 11.504, 37.44, 2.1164, 2.64666666666667, 2.2504,
4.135, 17.876, 51.74, 0.9248, 0.88, 2.2504, 4.4675, 18.28, 52.38,
2.118, 0.88, 1.8504, 5.465, 14.696, 52.12, 1.188, 2.204, 0.924,
3.1425, 10.73, 30.82, 0.9252, 0.220666666666667, 0.7936, 0.331,
5.03, 14.152, 0.1324, 0.220666666666667, 0.7928, 1.983, 3.97,
10.714, 0.6612, 0.44, 0.9244, 1.653, 10.196, 20.1, 0.6604, 0.44,
1.3208, 3.9675, 20.76, 54.78, 0.5288, 0.881333333333333, 0.6612,
4.47, 20.52, 68, 0.1324, 1.10066666666667, 0.1324, 5.7925, 21.44,
78.42, 0.6612, 0.881333333333333, 0.5288, 3.4775, 24.604, 76.12,
1.056, 1.1, 0.5288, 2.313, 15.082, 42.86, 0.0662, 0.110333333333333,
0.2648, 0.579, 1.6552, 3.838, 0.331, 0.331, 0.4632, 1.1565, 2.446,
2.054, 0.3968, 0.220666666666667, 0, 0.41375, 1.7862, 3.97, 0.0662,
0.110333333333333, 0.4632, 0.9935, 2.976, 9.792, 0, 0.441333333333333,
0.2648, 0.6605, 2.78, 9.672, 0.2648, 0.220666666666667, 0.2648,
0.74425, 2.9782, 10.592, 0.1986, 0.331, 0.7266, 1.32375, 4.036,
9.136, 0.2648, 0.220666666666667, 0.1324, 0.908, 2.7144, 5.292,
0.1324, 0, 0, 0, 0, 0.1986, 0.1986, 0.110333333333333, 0, 0.1655,
0, 0, 0.2648, 0, 0, 0.1655, 0, 0, 0, 0, 0, 0.08275, 0.331, 0.1324,
0.1324, 0.220666666666667, 0.1986, 0.24825, 0.2648, 0.0662, 0.1324,
0, 0.1324, 0.331, 0.3972, 0.662, 0.1324, 0, 0.1324, 0, 0.1324,
0.1324, 0.0662, 0.110333333333333, 0.0662, 0.1655, 0.0662, 0.1324,
0.1324, 0, 0, 0, 0, 0.1324, 0, 0, 0.3972, 0.1655, 0.3968, 0,
0, 0, 0, 0.08275, 0.0662, 0.0662, 0, 0, 0.1324, 0.1655, 0, 0.2648,
0.1324, 0.441333333333333, 0.1324, 0, 0.1324, 0.0662, 0.331,
0.110333333333333, 0.1986, 0.331, 0.1986, 0.1986, 0, 0, 0.1324,
0, 0.2648, 0.1986, 0.3968, 0, 0, 0.08275, 0.1986, 0, 79.46, 78.5,
84.1, 89.2, 90.06, 93.8, 83.26, 99.9333333333333, 95.68, 92.4,
90.08, 87.88, 103.48, 130, 118.6, 108.75, 104.42, 97.36, 131.6,
160.666666666667, 144.6, 131.75, 127, 118, 157.6, 153.666666666667,
155, 149.75, 147.6, 141.2, 148.6, 121.666666666667, 134.6, 144,
147.6, 151.8, 120.6, 92.9666666666667, 109.1, 122, 127, 136,
94.44, 75.6333333333333, 89.44, 100.775, 104.4, 112.2, 3.608,
4.94333333333333, 3.908, 2.885, 2.548, 1.708, 2.662, -0.513333333333333,
0.9634, 2.0675, 2.544, 3.208, 5.032, 4.81666666666667, 5.49,
5.7875, 5.776, 5.768, 6.884, 6.93, 6.846, 6.8025, 6.838, 6.824
), .indexCLASS = c("POSIXlt", "POSIXt"), .indexTZ = "", tclass = c("POSIXlt",
"POSIXt"), tzone = "", class = c("xts", "zoo"), index = structure(c(957173159,
957173208, 957173268, 957173329, 957173389, 957173450), tzone = "", tclass = c("POSIXlt",
"POSIXt")), .Dim = c(6L, 73L), .Dimnames = list(NULL, c("Year",
"Day", "Hour", "Min", "Sec.", "E1.S1", "E1.S2", "E1.S3", "E1.S4",
"E1.S5", "E1.S6", "E1.S7", "E1.S8", "E2.S1", "E2.S2", "E2.S3",
"E2.S4", "E2.S5", "E2.S6", "E2.S7", "E2.S8", "E3.S1", "E3.S2",
"E3.S3", "E3.S4", "E3.S5", "E3.S6", "E3.S7", "E3.S8", "E4.S1",
"E4.S2", "E4.S3", "E4.S4", "E4.S5", "E4.S6", "E4.S7", "E4.S8",
"FP5.S1", "FP5.S2", "FP5.S3", "FP5.S4", "FP5.S5", "FP5.S6", "FP5.S7",
"FP5.S8", "FP6.S1", "FP6.S2", "FP6.S3", "FP6.S4", "FP6.S5", "FP6.S6",
"FP6.S7", "FP6.S8", "FP7.S1", "FP7.S2", "FP7.S3", "FP7.S4", "FP7.S5",
"FP7.S6", "FP7.S7", "FP7.S8", "PA.LEFS60S1", "PA.LEFS60S2", "PA.LEFS60S3",
"PA.LEFS60S4", "PA.LEFS60S5", "PA.LEFS60S6", "PA.LEFS60S7", "PA.LEFS60S8",
"BX", "BY", "BZ", "Bmag....nT.")))
对于每个时间戳，我需要绘制（并获取一些统计信息）E1.S* 值与 PA.LEFS60S* 值的 cos。例如，对于时间戳 2000-05-01 10:25:59：
# These are the values from PA.LEFS60S1 to PA.LEFS60S8
x = c(79.46, 83.26000, 103.48, 131.6000, 157.6000, 148.6000, 120.60000, 94.44000)
# These are the values from E1.S1 to E1.S8
y = c(3.572000, 2.912000, 2.512, 6.352, 10.604000, 8.078,3.0444, 3.574000)
plot(cos(x),y)
然后我需要在一段时间内绘制平均值（y）与时间戳之类的东西......我只能在我获得一种自动化过程的方法之后才能做到这一点。
到目前为止，我只能手动完成。尽管我可以想出一种方法来使用 for 循环并检查表中的每个名称。但这似乎在计算上太慢太复杂，根本不像 R。
我尝试了使用rshape2包中的melt功能 -但输出只是来自多行以 timeStamp 作为索引且没有列信息的行。melt(testData)
