我有一个包含几个水质指标的数据框架.对于每一项测量，我都有一个计算的平均值和SD.我有6个地点和4个赛季的价值.目前，我的数据框中有一列平均值为‘temp_1’，然后有一列标准差为‘temp_2’.我想用Mean(SD)格式 for each 水质测量导出一个列的文件.
电流输出
这是第一个水测量的示例，但我想对它进行编码，以便也对其余因素进行编码.
期望输出
数据帧头部
structure(list(season = structure(c(1L, 1L, 1L, 1L, 1L, 1L), levels = c("Winter",
"Spring", "Summer", "Autumn"), class = "factor"), Site = structure(1:6, levels = c("1",
"2", "3", "4", "5", "6"), class = "factor"), Temp_1 = c(7.2,
7.05, 6.3, 6.25, 6.2, 5.4), Temp_2 = c(1.55563491861041, 1.90918830920368,
1.69705627484771, 2.33345237791561, 2.40416305603426, 2.40416305603426
), pH_1 = c(7.435, 7.38, 7.52, 7.525, 7.38, 7.565), pH_2 = c(0.289913780286484,
0.282842712474619, 0.0989949493661164, 0.120208152801713, 0.0565685424949239,
0.261629509039023), DO_1 = c(9, 9.1, 8.25, 8.85, 9.25, 9), DO_2 = c(0,
0.424264068711928, 0.0707106781186558, 0.494974746830583, 0.636396103067892,
0.42426406871193), EC_1 = c(337.5, 333, 321.5, 322, 309, 300.5
), EC_2 = c(55.8614357137373, 41.0121933088198, 51.618795026618,
32.5269119345812, 25.4558441227157, 30.4055915910215), SS_1 = c(5.945,
3.65, 5.025, 2.535, 10.22, 4.595), SS_2 = c(0.728319984622144,
1.06066017177982, 2.93449314192417, 0.473761543394987, 8.23072293301141,
0.67175144212722), TP_1 = c(73.5, 75, 61.5, 66.5, 83, 87), TP_2 = c(3.53553390593274,
12.7279220613579, 9.19238815542512, 6.36396103067893, 26.8700576850888,
24.0416305603426), SRP_1 = c(19, 19, 10, 14, 13.5, 23.5), SRP_2 = c(2.82842712474619,
1.4142135623731, 2.82842712474619, 0, 0.707106781186548, 3.53553390593274
), PP_1 = c(54.5, 56, 51.5, 52.5, 69.5, 63.5), PP_2 = c(6.36396103067893,
11.3137084989848, 6.36396103067893, 6.36396103067893, 26.1629509039023,
20.5060966544099), DA_1 = c(0.083, 0.0775, 0.0775, 0.044, 0.059,
0.051), DA_2 = c(0.00282842712474619, 0.0120208152801713, 0.00919238815542513,
0.0014142135623731, 0.0127279220613579, 0.00848528137423857),
DNI_1 = c(0.048739437, 0.041015562, 0.0617723365, 0.0337441755,
0.041480944, 0.0143461675), DNI_2 = c(0.0345079125942686,
0.0223312453226695, 0.0187360224120165, 0.0162032493604065,
0.0258169069873252, 0.0202885446465761), DNA_1 = c(20.43507986,
20.438919615, 14.98692746, 19.953408625, 17.03060377, 8.5767502525
), DNA_2 = c(1.80288106961836, 1.2687128010491, 2.28839365291436,
1.03116172040732, 0.396528484042397, 1.72350828181138), DF_1 = c(0.0992379715,
0.0947268395, 0.094323125, 0.098064875, 0.0980304675, 0.085783911
), DF_2 = c(0.00372072305060515, 0.00724914346231915, 0.0142932471712976,
0.0116895470668939, 0.00255671780854136, 0.00830519117656529
), DC_1 = c(12.18685357, 12.73924378, 13.09550326, 13.417557825,
15.140975265, 21.429763715), DC_2 = c(0.57615880774946, 0.0430071960969884,
0.702539578486863, 0.134642528587041, 0.66786605299916, 0.17012889453292
), DS_1 = c(15.834380095, 15.69623116, 14.37636388, 15.444235935,
14.647596185, 11.9877372), DS_2 = c(1.67153135346354, 1.69978765863781,
2.47560570280853, 1.03831263471691, 1.24488755930594, 0.975483163720397
), DOC_1 = c(19.74, 20.08, 21.24, 20.34, 21.88, 24.92), DOC_2 = c(2.7435743110038,
1.69705627484772, 2.60215295476649, 1.04651803615609, 0.226274169979695,
0.452548339959388)), row.names = c(NA, 6L), class = "data.frame")