使用匯總平滑數據集的多列

Question

我試圖通過舍入變量“深度”來平滑數據，然后在給定的數據集上應用 function summarize 。

mean_safely <- possibly(.f = mean, otherwise = NA)
SdesGG <- SdesGG %>% filter(., depth > 2) %>%
  mutate(depth = round(depth, 0)) %>%
  group_by(ctd_file) %>%
  summarize(across(temperature:salinity ~ round(list(mean_safely(.)),1))) %>% ungroup()

您將在示例下方找到：

SdesGG <- structure(list(temperature = c(0.9308, 1.4809, 1.9412, 1.9704, 
1.9441, 1.1894, 1.974, 0.455, 1.9655, 1.9502, 1.9506, 0.5185, 
1.9474, 1.9922, 2.0393, 0.9345, 0.6809, 1.2231, 1.9733, 1.9751, 
1.229, 1.9569, 2.034, 1.9767, 1.3208, 1.0682, 1.9452, 1.9461, 
1.8048, 1.1801, 1.9616, 1.9775, 1.9877, 0.8288, 1.9759, 1.9857, 
1.9831, 0.5541, 1.9875, 1.9825, 2.0005, 0.8818, 1.3144, 1.8218, 
1.2221, 0.5575, 0.8648, 1.9827, 1.7399, 1.9895, 0.5259, 2.0424, 
1.9526, 1.9882, 1.1759, 1.9853, 1.9847, 1.0108, 0.6056, 1.998, 
0.4447, 1.9707, 1.2876, 1.975, 1.9366, 1.9689, 0.5475, 1.938, 
1.9368, 1.9366, 1.9704, 1.1177, 1.9505, 1.3533, 1.813, 1.8302, 
1.9477, 1.9355, 1.9688, 1.9349, 1.9364, 1.9729, 1.9724, 2.0328, 
1.9761, 1.9465, 1.9744, 1.9367, 0.4231, 1.9361, 1.1732, 1.1402, 
0.9043, 0.7205, 0.3785, 0.3929, 0.4127, 0.4346, 0.3992, 1.1883, 
1.4211, 0.4132, 0.3572, 0.4144, 1.6264, 0.4566, 0.466, 0.209, 
1.3406, 1.9491, 1.0865, 0.9498, 1.9572, 0.836, 1.3802, 1.7071, 
0.3476, 1.9985, 1.9547, 1.2505, 0.9536, 1.0958, 0.0347, 0.7404, 
1.5834, 2.7523, 1.6212, 0.3825, 0.9406, 0.4867, 0.5643, 1.8807, 
0.8969, 1.6772, 1.8589, 0.6775, 0.6807, 0.051, 0.8666, 4.1077, 
0.9921, 1.5596, 1.6411, 4.5329, 1.3255, 1.1467, 1.1542, 1.5876, 
1.1037, 0.2636, 1.1306, 1.7967, 1.7743, 2.0192, 0.2678, 1.9754, 
1.8641, 0.3485, 0.3189, 0.8568, 1.7012, 1.3957, 2.0179, 0.6845, 
1.0104, 1.9718, 2.022, 1.9756, 1.9604, 1.958, 0.242, 1.6566, 
1.9771, 1.4425, 1.1437, 0.5678, 1.9822, 1.7978, 1.964, 0.313, 
1.425, 1.932, 0.4268, 0.8861, 0.6902, 1.9409, 1.9519, 2.0557, 
0.6445, 1.9409, 1.9489, 1.9453, 0.9755, 1.9599, 0.8472, 0.0834, 
1.6046, 1.9318, 1.9498, 1.9317), fluorescence = c(1.2416, 0.059356, 
0.043751, 0.036227, 0.045816, 0.058391, 0.034131, 0.054932, 0.036311, 
0.038989, 0.05338, 0.059174, 0.035708, 0.060092, 0.060673, 0.058095, 
0.055442, 0.048986, 0.034719, 0.031841, 0.053571, 0.0404, 0.05484, 
0.038205, 0.053787, 1.3745, 0.043484, 0.038612, 0.061635, 0.047504, 
0.052877, 0.032757, 0.026687, 0.051545, 0.030342, 0.033858, 0.031262, 
0.046113, 0.029848, 0.035317, 0.056674, 0.76054, 0.054171, 0.049573, 
0.048061, 0.062181, 0.068336, 0.032807, 0.05209, 0.037087, 0.042379, 
0.051727, 0.047473, 0.038959, 0.056963, 0.050888, 0.033068, 0.05053, 
0.34197, 0.050204, 0.039011, 0.038919, 0.062745, 0.033352, 0.040496, 
0.039149, 0.060463, 0.045803, 0.040281, 0.04064, 0.039728, 0.049628, 
0.041484, 0.054378, 0.044619, 0.048705, 0.041199, 0.10722, 0.039876, 
0.04514, 0.045093, 0.0329, 0.037108, 0.052406, 0.031364, 0.049695, 
0.029335, 0.041752, 0.095417, 0.037819, 0.053198, 0.049533, 0.05071, 
0.051106, 0.51342, 1.4482, 0.50474, 0.053666, 0.054703, 0.060486, 
0.055064, 0.05313, 0.12354, 0.051955, NA, 0.062835, 0.62916, 
0.3623, 0.053007, 0.042539, 0.050775, 0.052358, 0.049075, 0.056145, 
0.056917, 0.061122, 0.12266, 0.058804, 0.039958, 0.050389, 1.1909, 
0.085306, 0.25516, 0.10338, 0.085282, 0.21009, 0.086941, 0.12483, 
1.074, 0.12672, 0.11372, 0.081023, 0.093762, 0.07527, 0.066563, 
0.56037, 0.57393, 0.201, 0.10016, 0.16318, 0.087019, 0.078642, 
0.072709, 0.20222, 0.080648, 0.088892, 0.078775, 0.084689, 0.087081, 
0.16937, 0.053087, 0.055444, 0.050884, 0.047286, 1.7016, 0.036868, 
0.062344, 0.14358, 0.17529, 0.045806, 0.055564, 0.05658, 0.062737, 
0.34175, 0.059237, 0.034714, 0.054471, 0.038374, 0.034411, 0.047332, 
0.77096, 0.050224, 0.037368, 0.063016, 0.061832, 0.068767, 0.052314, 
0.049284, 0.039258, 0.060133, 0.048861, 0.04979, 0.054226, 0.056378, 
0.74172, 0.052244, 0.048553, 0.067182, 0.049219, 0.047817, 0.040588, 
0.040217, 0.055254, 0.047947, 0.056354, 0.30906, 0.064546, 0.042934, 
0.043631, NA), par = c(1.6974, 5.5346e-05, 0.00013858, 7.3361e-05, 
5.1657e-05, 3.0496e-05, 6.3502e-05, 5.335e-05, 5.0685e-05, 0.00012404, 
2.361e-05, 2.9159e-05, 1.9192e-05, 6.0756e-05, 1.9105e-05, 5.7069e-05, 
9.5946e-05, 8.8133e-05, 0.00010426, 5.3174e-05, 1.4931e-05, 5.2996e-05, 
4.9576e-05, 4.5506e-05, 6.0607e-06, 2.209, 6.5072e-05, 3.2411e-05, 
9.0745e-05, 9.4845e-06, 0.00011921, 3.5271e-05, -7.72e-07, 1.3421e-05, 
2.4226e-05, 7.4273e-05, 2.5845e-05, 0.0001111, 1.3496e-05, 8.7783e-05, 
0.00011209, 0.40803, 6.8998e-05, 2.6666e-05, -1.011e-06, 3.9958e-05, 
4.2753e-05, 1.9249e-06, 5.8514e-05, 7.0402e-05, 4.3381e-05, 5.5188e-05, 
6.29e-06, 3.4205e-06, 8.9512e-06, 3.5569e-05, 0.00010206, 2.4146e-05, 
0.042612, 5.2609e-05, 7.0174e-05, 3.5633e-06, 5.5222e-05, 5.7656e-05, 
4.2268e-05, 3.6032e-05, 1.8879e-05, 1.4931e-05, 2.795e-05, 2.811e-05, 
1.9217e-05, 2.2953e-05, 6.8208e-06, 4.4007e-05, 2.915e-05, 6.1766e-05, 
3.4101e-05, 2.0051e-05, 3.657e-05, 0.00011654, 6.2764e-05, 8.3353e-05, 
1.2452e-06, 8.0727e-05, 7.9778e-05, 6.7241e-05, 9.0843e-05, 3.5208e-05, 
1.5974e-05, 7.7922e-05, 7.4332e-05, 3.867e-05, 3.4518e-05, 4.0664e-05, 
3.1511, 13.346, 1.5865, 3.8304e-05, 7.0197e-06, 6.2889e-05, 5.2305e-05, 
6.3554e-05, 0.16325, 3.5129e-05, 5.1483e-05, 5.1007e-05, 4.5315, 
0.25318, 1.0616e-06, 1.8125e-05, 3.5275e-05, 7.5935e-06, 2.7635e-05, 
5.3401e-05, 4.8189e-05, 1.579e-05, 4.4328e-05, 1.9467e-05, 4.2492e-05, 
6.6007e-05, 16.809, 2.2957e-05, 1.487e-05, 2.1135e-05, 8.5334e-05, 
69.19, 9.4669e-07, 4.8723e-05, 11.806, 2.6083e-05, 1.8565e-06, 
3.1858e-05, 4.6153e-05, 3.1247e-05, 8.9936e-05, 1.0418, 1.286, 
4.3819e-05, 6.8601e-05, 72.817, 9.5971e-05, 3.8041e-06, 7.507e-05, 
68.365, 1.6492e-05, 1.6143e-06, 2.9006e-05, 1.4072e-05, 2.6006e-05, 
-6.96e-06, 9.3415e-05, 3.1039e-05, 4.0213e-05, 5.1291e-05, 41.211, 
5.8782e-05, -4.023e-07, 0.049406, 0.11159, 2.2583e-06, -1.409e-06, 
5.232e-05, 8.0308e-05, 83.871, 2.0754e-05, 1.255e-05, 3.2088e-05, 
2.5955e-05, 2.8808e-05, 3.8295e-05, 1.0499, 2.4432e-05, 4.5624e-05, 
2.8149e-05, 9.8288e-05, 5.158e-05, 6.4363e-05, 1.2171e-05, -1.655e-07, 
6.457e-05, 6.9252e-05, 1.8027e-06, 1.6697e-06, 3.9826e-05, 2.2247, 
5.485e-05, 4.2182e-05, 4.1616e-05, 1.6252e-06, 3.247e-05, 5.5941e-05, 
2.6743e-05, 2.1318e-05, 3.3666e-05, 2.0362e-05, 0.071072, 5.3865e-05, 
4.6206e-05, 3.4668e-06, 2.5886e-05), turbidity = c(0.675, 0.663, 
0.407, 0.41, 0.368, 0.562, 0.841, 0.637, 0.371, 0.246, 0.166, 
0.438, 0.472, 0.384, 0.419, 0.607, 0.473, 0.706, 0.668, 0.782, 
0.533, 0.541, 0.434, 0.418, 0.425, 0.64, 0.343, 0.42, 0.474, 
0.66, 0.565, 0.414, 1.502, 2.393, 0.673, 1.425, 0.315, 1.957, 
1.335, 1.411, 0.834, 0.597, 0.661, 0.802, 0.596, 1.994, 1.52, 
1.277, 0.699, 0.36, 2.873, 0.881, 0.194, 0.453, 0.9, 0.238, 1.54, 
0.704, 0.619, 0.461, 0.73, 0.187, 0.425, 0.839, 0.289, 0.301, 
0.663, 0.375, 0.404, 0.359, 0.523, 0.678, 0.287, 0.32, 0.46, 
0.619, 0.292, 0.277, 0.587, 0.318, 0.239, 0.454, 0.72, 0.475, 
0.824, 0.401, 0.82, 0.462, 0.83, 0.37, 0.497, 0.549, 0.611, 0.531, 
0.537, 0.45, 0.626, 0.7, 0.714, 0.632, 0.833, 0.636, 0.739, 0.579, 
0.574, 0.807, 0.453, 0.582, 0.35, 0.501, 0.563, 0.685, 0.377, 
0.472, 0.556, 0.684, 0.763, 0.613, 0.292, 0.635, 0.903, 0.536, 
0.364, 0.444, 0.328, 0.419, 0.352, 0.268, 0.826, 0.462, 0.243, 
0.467, 0.403, 0.317, 0.458, 0.848, 0.535, 0.1, 0.41, 0.734, 0.29, 
0.329, 0.274, 0.495, 0.594, 0.269, 0.473, 0.449, 0.307, 0.281, 
0.356, 0.729, 0.553, 0.459, 0.537, 0.593, 0.599, 0.792, 0.734, 
0.875, 0.494, 0.509, 0.371, 0.411, 0.621, 0.63, 0.535, 0.65, 
0.359, 0.531, 0.262, 0.418, 0.52, 0.395, 0.56, 0.39, 0.342, 0.6, 
0.487, 0.542, 0.411, 0.238, 0.605, 0.834, 0.686, 0.488, 0.43, 
0.335, 0.687, 0.33, 0.391, 0.473, 0.634, 0.301, 0.999, 0.514, 
0.392, 0.175, 0.541, 0.303), conductivity = c(28.23714, 29.910402, 
30.622812, 30.706634, 30.616424, 29.52304, 30.792231, 28.484894, 
30.698706, 30.597782, 30.596844, 28.666107, 30.667508, 30.595813, 
30.592171, 29.1949, 28.867085, 29.58463, 30.7565, 30.773269, 
29.594035, 30.686339, 30.593779, 30.743757, 29.70588, 28.355997, 
30.612647, 30.6708, 30.320538, 29.510332, 30.507848, 30.684579, 
30.821767, 29.046728, 30.713939, 30.805514, 30.691897, 28.376236, 
30.820744, 30.834285, 30.552498, 28.273608, 29.703324, 30.350477, 
29.579133, 28.381509, 29.089567, 30.77867, 30.245481, 30.704692, 
28.576339, 30.604829, 30.590527, 30.708136, 29.517695, 30.58685, 
30.798369, 29.295525, 28.177456, 30.591354, 28.430024, 30.726116, 
29.642267, 30.779516, 30.607466, 30.725932, 28.71855, 30.593906, 
30.606068, 30.627645, 30.724299, 29.421668, 30.664992, 29.750923, 
30.335061, 30.35529, 30.657722, 30.638996, 30.737009, 30.636689, 
30.624061, 30.708252, 30.757804, 30.595311, 30.787748, 30.656019, 
30.775381, 30.605799, 28.566359, 30.640589, 29.489052, 29.441922, 
29.126241, 28.881733, 27.855657, 27.704399, 27.971728, 28.487233, 
28.519601, 29.500078, 29.840773, 28.513265, 28.134678, 28.512372, 
30.104072, 28.392852, 27.898279, 28.002616, 29.718086, 30.597578, 
29.372442, 29.192671, 30.589607, 29.033438, 29.781067, 30.203899, 
28.261392, 30.582846, 30.591536, 29.58124, 28.300356, 29.324194, 
27.902178, 28.90821, 29.927125, 29.235341, 29.975774, 28.512712, 
28.298321, 28.641755, 28.713441, 30.329415, 29.096137, 30.046253, 
30.30579, 28.182583, 28.16897, 28.056641, 29.061755, 29.525821, 
29.203431, 29.895765, 29.998191, 30.27088, 29.598588, 29.384924, 
29.391768, 29.93265, 29.336125, 28.365763, 29.420454, 30.285358, 
30.257527, 30.596912, 27.177419, 30.751539, 30.369123, 28.145723, 
28.080918, 29.057925, 30.170211, 29.796191, 30.595906, 26.871015, 
29.265041, 30.763363, 30.556041, 30.752652, 30.682216, 30.587728, 
27.801895, 30.105547, 30.737439, 29.847531, 29.442942, 28.717221, 
30.587277, 30.303892, 30.690668, 28.433097, 29.785645, 30.611885, 
28.443451, 29.088942, 28.127101, 30.59362, 30.708708, 30.58822, 
28.761219, 30.646587, 30.686117, 30.671561, 29.213426, 30.579616, 
29.040487, 27.906425, 30.077206, 30.598468, 30.702566, 30.598577
), oxygen = c(95.30836, 61.30839, 61.72527, 61.38044, 61.78904, 
62.32286, 60.51705, 64.10607, 61.40687, 61.93106, 61.96531, 64.52459, 
61.52386, 62.423, 63.13287, 62.46788, 64.01251, 61.82749, 60.78189, 
60.71662, 61.92392, 61.37, 63.07995, 61.09333, 61.73046, 98.79564, 
61.8274, 61.41733, 61.49582, 62.16286, 61.88601, 61.48436, 60.43031, 
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33.7185, 33.7916, 34.1368, 34.2664, 33.7709, 33.3755, 33.769, 
34.3473, 33.5843, 32.9661, 33.3651, 34.2165, 34.5116, 34.0931, 
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32.2883, 34.237, 33.8036, 32.9798, 33.8522, 33.8586, 34.3628, 
33.9743, 34.2577, 34.3585, 33.1015, 33.0813, 33.5882, 33.9637, 
31.3096, 34.0019, 34.211, 34.2414, 31.7699, 34.1155, 34.0516, 
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34.485, 32.2456, 34.5286, 34.411, 33.3979, 33.3478, 33.9673, 
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33.856, 34.4993, 34.4042, 34.5269, 33.772, 34.2165, 34.5163, 
33.68, 33.9745, 33.0217, 34.5128, 34.5247, 34.4597, 33.8415, 
34.5224, 34.524, 34.5235, 34.0252, 34.5041, 33.9592, 33.3707, 
34.3403, 34.5142, 34.5245, 34.5142), depth = c(26.5, 333.5, 617, 
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Answer 1

round期待一個vector 。 根據?round

x - 一個數值向量。 或者，對於 round 和 signif，一個復向量。

通過用list包裝，它會導致問題。

library(purrr)
library(dplyr)
SdesGG %>% 
  filter( depth > 2) %>%
  mutate(depth = round(depth, 0)) %>%
  group_by(ctd_file) %>%
  summarize(across(temperature:salinity , 
  ~ round(mean_safely(.x, na.rm = TRUE), 1)), .groups= 'drop')

-輸出

# A tibble: 7 × 8
  ctd_file temperature fluorescence   par turbidity conductivity oxygen salinity
  <chr>          <dbl>        <dbl> <dbl>     <dbl>        <dbl>  <dbl>    <dbl>
1 BA16001          1.6          0.1   0.1       0.5         30     64.3     34.3
2 BA16002          1.6          0.1   0         1           30     63.5     34.2
3 BA16003          1.7          0     0         0.5         30.3   61.6     34.4
4 BA16004          1            0.2   0.8       0.6         29.1   66.7     33.9
5 BA16005          1.3          0.2   8         0.4         29.2   75.7     33.7
6 BA16006          1.4          0.1   4.2       0.5         29.7   67.5     34.1
7 BA16007          1.5          0.1   0.1       0.5         29.9   64.1     34.2