R基於2個其他列的一列中的聚合數據

Question

因此，我在下面給出了這些數據，我的目標是按列v1和v2聚合列v3併爲v1和v2的每個bin添加v3值。例如，第一行對應於時間間隔v1 = 21，v2 = 16，因此v3的值將在其（v1，v2）時間間隔內聚合。並對其餘的行重複此操作。我想用平均值作爲聚合函數！

> df 
     v1  v2  v3 
1 21.359 16.234 24.283 
2 47.340 9.184 21.328 
3 35.363 -13.258 14.556 
4 -29.888 14.154 17.718 
5 -10.109 -16.994 20.200 
6 -32.387 1.722 15.735 
7 49.240 -5.266 17.601 
8 -38.933 2.558 16.377 
9 41.213 5.937 21.654 
10 -33.287 -4.028 19.525 
11 -10.223 11.961 16.756 
12 -48.652 16.558 20.800 
13 44.778 27.741 17.793 
14 -38.546 29.708 13.948 
15 -45.622 4.729 17.793 
16 -36.290 12.383 18.014 
17 -19.626 19.767 18.182 
18 -32.248 29.480 15.108 
19 -41.859 35.502 8.490 
20 -36.058 21.191 16.714 
21 -23.588 0.524 21.471 
22 -24.423 39.963 18.257 
23 -0.042 -45.899 17.654 
24 -35.479 32.049 9.294 
25 -24.632 20.603 17.757 
26 -26.591 25.882 18.968 
27 -34.364 43.959 13.905 
28 -19.334 29.728 20.102 
29 12.304 -39.997 17.002 
30 0.958 37.162 20.779 
31 -35.475 -40.611 14.719 
32 -39.268 44.382 11.247 
33 -10.154 39.053 19.458 
34 -12.612 32.056 17.759 
35 2.730 -1.473 20.228 
36 -45.326 -52.299 9.305 
37 -1.996 -15.551 13.295 
38 -26.655 -37.319 19.148 
39 -18.509 -30.047 18.889 
40 -22.705 -25.577 19.007 
41 -15.705 -15.397 19.112 
42 -2.637 9.790 10.548 
43 -14.107 -3.145 19.654 
44 -29.272 -19.906 18.503 
45 -9.569 -4.632 11.334 
46 2.114 18.048 14.744 
47 -4.241 16.073 15.420 
48 31.869 -3.394 21.559 
49 20.425 35.205 22.250 
50 -18.605 -8.866 20.082 
51 -26.677 -7.690 21.850 
52 -5.240 4.805 11.399 
53 -6.766 2.538 6.292 
54 4.567 22.554 19.682 
55 -20.701 6.430 20.996 
56 -23.972 16.141 17.976 
57 -6.651 24.048 18.082 
58 -32.243 -6.100 19.517 
59 2.236 29.736 19.667 
60 18.830 15.586 15.969 
61 -9.598 28.414 17.806 
62 -30.825 12.194 22.346 
63 -17.415 15.795 18.135 
64 -14.823 5.931 17.915 
65 -14.234 12.882 13.001 
66 9.937 18.368 20.421 
67 -38.766 9.590 21.648 
68 -30.896 27.047 16.453 
69 -4.432 -10.562 10.061 
70 -4.290 33.170 22.942 
71 7.285 41.416 23.906 
72 24.411 40.531 23.584 
73 45.409 -32.420 20.831 
74 49.341 -34.047 15.269 
75 -7.730 -47.724 21.692 
76 -10.563 -29.082 17.984 
77 4.412 -41.182 16.845 
78 31.822 -37.297 19.665 
79 -43.355 31.093 17.688 
80 -44.353 -44.723 13.832 
81 -16.961 38.438 20.715 
82 -21.225 -39.244 18.156 
83 -42.022 -8.686 20.362 
84 -42.904 -25.498 18.394 
85 43.822 -25.990 21.287 
86 43.013 -9.071 19.285 
87 -36.901 -24.185 21.938 
88 -28.251 -36.583 19.330 
89 -19.830 -22.412 21.677 
90 -3.789 -15.663 17.439 
91 40.453 -21.796 17.432 
92 -40.778 -31.188 18.762 
93 -27.072 -48.609 18.913 
94 -18.035 -1.791 19.909 
95 -20.781 -7.912 22.563 
96 47.307 -15.432 19.101 
97 30.700 5.097 22.801 
98 46.453 0.171 17.810 
99 -27.439 -5.860 22.626 
100 -30.526 -18.007 23.219 
101 -18.280 -15.187 25.302 
102 -18.367 6.044 18.864 
103 41.265 -1.686 22.743 
104 29.227 -14.814 19.196 
105 -36.080 -32.715 18.930 
106 7.475 7.061 25.002 
107 -18.586 -45.207 21.864 
108 35.227 11.148 21.388 
109 -7.581 38.773 22.048 
110 -43.685 14.083 22.037 
111 -29.533 39.735 17.613 
112 8.760 -39.400 22.421 
113 -14.962 24.624 12.030 
114 18.627 -32.888 23.036 
115 -31.300 33.612 15.608 
116 -38.024 45.839 16.567 
117 -15.104 36.893 18.162 
118 -12.809 -23.029 21.589 
119 -21.614 36.264 16.680 
120 42.917 -36.838 18.738 
121 6.104 -14.961 14.468 
122 44.032 -41.556 17.618 
123 -24.493 21.886 17.366 
124 -24.361 29.941 14.374 
125 -25.060 43.383 16.437 
126 -6.017 -24.640 19.207 
127 -32.617 -40.549 18.059 
128 -43.285 -43.364 18.827 
129 -29.856 -46.089 16.881 
130 -16.547 -43.619 22.547 
131 -16.257 42.814 18.932 
132 -9.236 -11.694 14.455 
133 13.488 -35.422 24.436 
134 -47.456 -32.714 18.123 
135 39.476 -28.008 16.087 
136 -21.933 -43.522 15.390 
137 -17.347 -38.250 16.738 
138 -4.948 -39.747 21.598 
139 -31.018 -28.912 21.332 
140 -36.364 30.461 17.542 
141 -39.639 18.272 23.663 
142 -24.162 -13.582 19.136 
143 -8.935 -32.699 22.108 
144 0.001 -19.219 17.888 
145 -6.912 -24.885 20.683 
146 7.785 -31.229 15.972 
147 22.176 -7.478 21.335 
148 8.755 -13.323 20.831 
149 44.081 41.160 11.938 
150 -8.451 -37.721 17.465 
151 18.671 -2.776 23.374 
152 12.668 -26.749 18.071 
153 1.582 -21.252 20.750 
154 20.832 -27.718 16.190 
155 44.220 -45.690 12.598 
156 -0.226 -37.737 17.634 
157 -25.130 -19.197 23.170 
158 2.086 -31.271 18.180 
159 -20.445 -33.083 19.984 
160 23.801 1.116 24.230 
161 18.283 -17.922 20.256 
162 -38.985 -13.770 20.702 
163 -26.264 -27.413 20.276 
164 10.396 -19.375 20.415 
165 -16.343 -22.847 16.516 
166 29.992 -8.215 21.661 
167 35.052 -19.475 16.953 
168 3.052 -6.800 22.509 
169 -10.350 -5.413 19.222 
170 14.371 -10.383 23.471 
171 11.896 -4.191 21.773 
172 18.152 8.741 23.669 
173 25.748 -47.786 18.578 
174 31.613 -0.735 23.898 
175 12.660 25.645 23.549 
176 2.933 29.345 25.170 
177 9.369 18.791 26.817 
178 15.805 4.798 27.866 
179 27.556 -25.571 14.796 
180 -5.112 -7.835 21.201 
181 -30.571 3.471 20.496 
182 19.816 -22.114 21.210 
183 2.826 47.437 22.911 
184 25.488 -33.064 21.442 
185 44.826 42.162 22.994 
186 25.208 -48.487 25.325 
187 14.635 -17.430 17.083 
188 -1.901 -33.370 22.163 
189 12.306 -47.265 20.052 
190 42.552 35.750 23.213 
191 37.318 -46.069 22.599 
192 4.725 -22.289 21.600 
193 -40.815 -37.793 17.371 
194 11.890 -12.862 14.286 
195 35.251 -31.746 17.816 
196 27.121 -27.638 19.677 
197 36.024 -39.105 20.202 
198 -47.119 41.940 17.526 
199 0.837 -40.694 23.063 
200 23.797 -39.795 20.198 
201 -42.859 -21.372 23.554 
202 39.407 -20.211 21.246 
203 25.782 -18.892 20.423 
204 34.529 -9.576 20.411 
205 44.397 -13.247 23.180 
206 5.534 6.856 14.248 
207 31.598 -18.085 22.350 
208 7.250 -0.481 15.453 
209 -43.458 -15.204 23.193 
210 -38.296 -31.524 21.776 
211 4.276 -3.483 12.145 
212 25.757 -11.708 22.360 
213 15.634 37.478 24.624 
214 -43.669 -3.197 20.742 
215 45.381 6.365 21.351 
216 -38.755 -6.877 20.879 
217 -6.925 3.994 21.120 
218 8.059 12.831 26.032 
219 3.572 22.105 26.920 
220 16.042 30.267 21.039 
221 26.629 13.042 23.633 
222 -12.126 -0.151 21.261 
223 -11.981 24.600 19.236 
224 29.480 28.362 21.838 
225 -2.500 22.858 23.177 
226 -41.163 19.863 20.059 
227 35.953 27.401 19.101 
228 -16.641 13.248 17.984 
229 -3.778 14.090 18.943 
230 11.643 34.817 21.621 
231 34.921 38.666 17.359 
232 25.621 22.451 22.866 
233 34.936 17.384 19.836 
234 40.017 37.599 13.987 
235 19.547 33.838 22.575 
236 11.197 39.977 19.347 
237 16.972 -33.927 14.205 
238 22.938 38.064 20.351 
239 40.234 18.672 23.030 
240 -0.846 42.320 18.383 
241 -11.437 18.284 16.502 
242 19.552 43.222 21.370 
243 13.925 -46.486 18.917 
244 41.709 -39.559 16.143 
245 19.014 -44.563 17.796 
246 32.260 33.114 18.402 
247 -4.693 29.228 18.622 
248 21.765 -38.452 15.147 
249 39.157 -31.135 19.800 
250 32.638 46.241 18.943 
251 2.797 10.089 21.330 
252 8.256 46.910 18.834 
253 38.634 -2.429 20.413 
254 28.642 2.763 19.580 
255 0.456 1.422 7.452 
256 3.050 11.792 14.196 
257 24.736 14.532 17.886 
258 16.787 -10.155 18.607 
259 12.676 11.651 18.656 
260 13.184 1.081 15.385 
261 27.365 26.576 25.486 
262 -7.878 -18.191 14.547 
263 -42.112 32.576 20.865 
264 15.069 21.684 17.986 
265 33.045 27.166 25.252 
266 21.810 -0.186 19.477 
267 18.227 26.690 20.415 
268 33.759 18.366 21.255 
269 39.491 13.272 23.036 
270 30.662 9.368 20.192 
271 5.470 35.303 22.685 
272 21.663 -44.343 20.999 
273 31.261 33.178 24.335 
274 21.854 22.665 20.876 
275 21.853 7.932 18.588 
276 -40.168 3.682 19.642 
277 -42.292 23.997 22.199 
278 10.233 28.731 21.263 
279 17.745 41.831 19.536 
280 38.406 25.165 26.534 
281 -49.329 -0.465 20.887 
282 40.398 -8.120 21.362 
283 -2.531 46.118 22.933 
284 7.959 -30.856 20.497 
285 -34.467 -23.724 22.206 
286 30.541 44.284 25.878 
287 45.682 29.897 21.964 
288 -22.251 -0.089 20.756 
289 21.484 16.532 23.513 
290 46.912 10.195 21.908 
291 35.320 -13.352 16.102 
292 -30.431 14.048 17.362 
293 -8.976 -17.325 21.645 
294 -32.661 2.301 16.805 
295 49.317 -5.509 17.711 
296 -37.756 4.459 16.054 
297 41.445 6.158 21.442 
298 -33.148 -3.499 19.543 
299 -10.065 12.238 16.649 
300 -48.323 17.153 20.974 
301 45.010 28.147 17.838 
302 -39.630 29.183 13.254 
303 -45.191 5.065 18.214 
304 -35.936 11.953 16.540 
305 -19.816 19.624 18.279 
306 -32.055 29.757 15.358 
307 -41.533 36.169 10.005 
308 -35.448 20.960 16.720 
309 -23.384 0.511 20.005 
310 -25.101 40.569 18.180 
311 -0.547 -45.779 17.603 
312 -35.291 32.643 9.548 
313 -25.109 20.826 17.494 
314 -26.202 27.012 18.678 
315 -34.805 43.850 14.006 
316 -18.819 30.611 20.309 
317 13.019 -40.248 16.874 
318 -0.655 37.112 20.924 
319 -34.142 -41.553 15.237 
320 -39.509 43.886 12.464 
321 -9.491 38.639 18.839 
322 -12.164 31.977 17.598 
323 3.437 -1.596 20.318 
324 -45.713 -52.599 9.918 
325 -2.062 -15.946 12.847 
326 -27.435 -37.600 18.257 
327 -18.094 -29.624 18.791 
328 -22.647 -26.123 18.746 
329 -16.775 -15.505 19.204 
330 -2.628 9.599 11.219 
331 -15.718 -1.797 19.491 
332 -29.476 -20.107 17.485 
333 -10.618 -4.938 12.227 
334 1.423 17.458 14.706 
335 -4.503 16.630 14.718 
336 32.450 -2.029 21.591 
337 20.529 35.464 21.630 
338 -19.348 -7.844 19.464 
339 -26.760 -6.856 21.422 
340 -4.539 4.393 11.819 
341 -5.741 1.934 7.121 
342 4.781 21.919 18.908 
343 -19.797 6.928 20.928 
344 -24.555 16.834 19.796 
345 -5.664 24.465 18.432 
346 -32.891 -6.571 18.691 
347 2.354 28.462 19.825 
348 18.058 16.251 16.335 
349 -9.603 28.582 17.743 
350 -31.282 11.454 22.342 
351 -17.580 16.428 18.401 
352 -13.884 6.206 17.270 
353 -13.631 13.767 11.761 
354 9.712 18.008 18.896 
355 -37.987 9.024 21.309 
356 -29.969 27.506 16.964 
357 -4.248 -10.813 9.284 
358 -5.755 32.673 22.541 
359 6.675 41.952 24.227 
360 24.564 41.173 23.241 
361 45.314 -32.299 20.778 
362 -45.890 -33.510 16.314 
363 -8.277 -47.943 21.573 
364 -11.044 -29.464 17.708 
365 3.972 -41.396 17.411 
366 31.776 -36.643 19.998 
367 -43.072 31.311 17.828 
368 -45.805 -43.071 14.477 
369 -15.628 39.837 19.709 
370 -21.129 -39.101 18.814 
371 -41.628 -8.980 19.850 
372 -42.244 -23.659 18.856 
373 44.149 -25.710 21.099 
374 42.623 -9.185 20.147 
375 -35.949 -23.979 22.255 
376 -28.512 -36.367 19.378 
377 -19.827 -21.781 21.621 
378 -3.429 -15.706 18.677 
379 39.741 -20.721 18.670 
380 -41.663 -29.499 19.260 
381 -26.931 -48.467 18.185 
382 -17.571 -1.467 19.770 
383 -20.039 -7.591 22.737 
384 46.370 -14.790 19.922 
385 30.710 4.167 22.987 
386 46.755 0.417 18.088 
387 -27.293 -4.398 22.168 
388 -30.364 -17.573 23.869 
389 -16.870 -14.893 25.817 
390 -18.152 6.546 18.392 
391 40.134 0.160 23.661 
392 28.179 -14.323 19.301 
393 -35.907 -32.647 19.306 
394 8.486 7.101 24.551 
395 -17.155 -45.435 22.745 
396 34.226 10.748 19.773 
397 -7.760 38.754 22.211 
398 -42.899 13.804 22.628 
399 -29.972 40.435 17.784 
400 8.764 -39.195 22.070 
401 -15.624 25.585 12.291 
402 18.620 -33.314 23.282 
403 -30.436 34.219 15.102 
404 -37.665 44.955 15.257 
405 -15.861 37.488 18.956 
406 -13.375 -22.408 20.312 
407 -20.972 36.906 17.387 
408 43.162 -35.948 19.695 
409 6.639 -15.783 14.608 
410 44.186 -41.037 17.398 
411 -23.917 22.236 18.702 
412 -23.957 30.033 14.725 
413 -25.056 43.824 15.489 
414 -6.795 -24.375 18.537 
415 -33.485 -40.651 17.538 
416 -43.186 -43.071 17.481 
417 -30.325 -46.122 16.440 
418 -17.489 -43.551 22.006 
419 -16.376 43.928 18.992 
420 -9.076 -10.921 14.131 
421 13.704 -36.352 23.812 
422 -47.302 -31.918 18.719 
423 39.459 -27.814 15.558 
424 -22.509 -42.660 14.366 
425 -17.920 -37.614 16.572 
426 -5.780 -39.212 21.667 
427 -30.519 -28.942 21.931 
428 -35.937 31.435 17.106 
429 -38.680 18.435 23.342 
430 -24.796 -13.279 18.543 
431 -9.283 -32.388 21.895 
432 0.493 -19.505 17.276 
433 -7.046 -25.243 20.741 
434 7.884 -32.006 16.727 
435 22.451 -7.834 21.082 
436 8.379 -13.690 22.002 
437 43.730 41.697 11.894 
438 -9.040 -38.086 17.500 
439 18.831 -2.759 23.252 
440 12.732 -27.410 18.948 
441 0.739 -21.091 21.354 
442 20.339 -27.959 16.514 
443 44.688 -46.449 12.356 
444 -0.402 -36.951 17.891 
445 -24.790 -18.139 23.337 
446 2.173 -30.577 18.023 
447 -18.995 -33.799 20.730 
448 23.372 0.223 24.855 
449 17.835 -17.372 19.878 
450 -38.915 -13.815 20.923 
451 -26.241 -27.800 19.877 
452 11.074 -18.156 19.249 
453 -16.478 -22.928 16.386 
454 29.646 -8.349 21.115 
455 33.910 -20.809 16.629 
456 3.306 -6.830 22.059 
457 -10.512 -5.322 19.876 
458 14.024 -10.406 23.456 
459 12.365 -3.699 21.818 
460 18.186 8.532 23.951 
461 25.140 -47.653 18.592 
462 32.288 -2.117 23.423 
463 10.836 24.937 23.310 
464 4.531 28.913 25.238 
465 9.944 18.397 26.661 
466 16.274 4.852 27.837 
467 27.316 -26.007 15.934 
468 -4.508 -8.010 20.906 
469 -29.858 2.412 19.958 
470 20.376 -21.957 21.306 
471 2.077 47.431 23.248 
472 25.777 -33.367 21.695 
473 44.854 42.801 22.904 
474 25.356 -48.833 25.402 
475 15.322 -16.926 17.318 
476 -2.656 -33.400 20.365 
477 11.950 -47.390 20.328 
478 42.961 36.955 22.919 
479 35.726 -45.402 24.272 
480 4.675 -21.758 21.780 
481 -40.568 -36.931 16.934 
482 11.758 -12.859 14.206 
483 35.483 -31.760 16.975 
484 27.336 -27.577 19.429 
485 36.689 -39.218 19.668 
486 -46.357 41.618 17.456 
487 0.002 -40.589 22.558 
488 23.525 -39.918 21.247 
489 -43.269 -21.304 22.699 
490 40.191 -20.594 21.145 
491 25.728 -18.024 20.298 
492 34.964 -10.441 20.189 
493 43.627 -13.279 23.038 
494 5.766 6.876 14.077 
495 32.432 -18.172 21.848 
496 7.087 -1.122 15.098 
497 -44.110 -14.034 23.080 
498 -39.474 -31.289 22.312 
499 4.118 -4.077 11.067 
500 26.597 -11.667 22.641 

所以，使用這些命令的我可以找到的間隔，如下面 x.bin < - SEQ（地板（分鐘（d [1]）），天花板（最大（DF [1]） ），由= 2） y.bin < - SEQ（地板（分鐘（d [2]）），天花板（最大（DF [1,2]）），由= 2）

> x.bin 
[1] -50 -48 -46 -44 -42 -40 -38 -36 -34 -32 -30 -28 -26 -24 -22 -20 -18 -16 -14 
[20] -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 
[39] 26 28 30 32 34 36 38 40 42 44 46 48 50 
> y.bin 
[1] -53 -51 -49 -47 -45 -43 -41 -39 -37 -35 -33 -31 -29 -27 -25 -23 -21 -19 -17 
[20] -15 -13 -11 -9 -7 -5 -3 -1 1 3 5 7 9 11 13 15 17 19 21 
[39] 23 25 27 29 31 33 35 37 39 41 43 45 47 

但，那麼我不知道如何將每行的原始數據（df）分配給每個x.bin和y.bin，並計算每個bin的總和（總和）。

Answer 1

library(plyr) 

＃我現在用cut功能與50個減免無論從plyr包v1和v2和ddply計算平均

newdata<-ddply(df,.(cut(v1,50),cut(v2,50)),summarise,mean.v3=mean(v3)) 
    > head(newdata) 
     cut(v1, 50) cut(v2, 50) mean.v3 
    1 (-49.4,-47.5] (-34.7,-32.7] 18.123 
    2 (-49.4,-47.5] (-0.576,1.43] 20.887 
    3 (-49.4,-47.5] (15.5,17.5] 20.887 
    4 (-47.5,-45.5] (-52.7,-50.7] 9.918 
    5 (-47.5,-45.5] (-44.7,-42.7] 14.477 
    6 (-47.5,-45.5] (-34.7,-32.7] 16.314 

更新爲每個評論：如果你想中間和中點，您可以使用以下function或使用細節如下（您需要使用sub函數來處理(和]）：

df$newv1<-with(df,cut(v1,50)) 
    df$newv2<-with(df,cut(v2,50)) 
    df$lowerv1<-with(df,as.numeric(sub("\\((.+),.*", "\\1", newv1))) #lower value 
    df$upperv1<-with(df,as.numeric(sub("[^,]*,([^]]*)\\]", "\\1", newv1))) # upper value 
    df$midv1<-with(df,(lowerv1+upperv1)/2) #mid value 
    df$lowerv2<-with(df,as.numeric(sub("\\((.+),.*", "\\1",newv2))) #lower value 
    df$upperv2<-with(df,as.numeric(sub("[^,]*,([^]]*)\\]", "\\1", newv2))) # upper value 
    df$midv2<-with(df,(lowerv2+upperv2)/2)#mid value 
    newdata<-ddply(df,.(newv1,newv2),transform,mean.v3=mean(v3)) 

    > head(newdata) 
     v1  v2  v3   newv1   newv2 lowerv1 upperv1 midv1 lowerv2 upperv2 midv2 mean.v3 
1 -47.456 -32.714 18.123 (-49.4,-47.5] (-34.7,-32.7] -49.4 -47.5 -48.45 -34.700 -32.70 -33.700 18.123 
2 -49.329 -0.465 20.887 (-49.4,-47.5] (-0.576,1.43] -49.4 -47.5 -48.45 -0.576 1.43 0.427 20.887 
3 -48.652 16.558 20.800 (-49.4,-47.5] (15.5,17.5] -49.4 -47.5 -48.45 15.500 17.50 16.500 20.887 
4 -48.323 17.153 20.974 (-49.4,-47.5] (15.5,17.5] -49.4 -47.5 -48.45 15.500 17.50 16.500 20.887 
5 -45.713 -52.599 9.918 (-47.5,-45.5] (-52.7,-50.7] -47.5 -45.5 -46.50 -52.700 -50.70 -51.700 9.918 
6 -45.805 -43.071 14.477 (-47.5,-45.5] (-44.7,-42.7] -47.5 -45.5 -46.50 -44.700 -42.70 -43.700 14.477