Hey, i want to define 3 ideal breaks (bin) for each variable one of those variables is attached in the previous email, i don't want to consider quartile method because quartile is not working ideally for that data set because data distribution is non normal. so i want you to suggest another method so that i can define 3 breaks with the ideal interval for Recency, frequency and monetary to calculate RFM score. i'm again attaching you some of the data set. please look into it and help me with the R code. Thanks *Data* user_id subtotal_amount created_at Recency Frequency Monetary 194849 6.99 8/22/2017 9 5 9.996 194978 14.78 8/28/2017 3 15 16.308 198614 18.44 7/31/2017 31 1 18.44 234569 34.99 8/20/2017 11 8 13.5075 252686 7.99 7/31/2017 31 2 7.99 291719 21.26 8/25/2017 6 2 15.67 291787 46.1 8/31/2017 0 2 32.57 292630 24.34 7/31/2017 31 1 24.34 295204 21.86 7/18/2017 44 1 21.86 295989 8.98 8/20/2017 11 2 14.095 298883 14.38 8/24/2017 7 2 11.185 308824 10.77 7/31/2017 31 1 10.77 308874 8.29 6/11/2017 81 1 8.29 309088 17.16 8/3/2017 28 1 17.16 309126 20.54 7/30/2017 32 1 20.54 309127 15.24 8/2/2017 29 4 13.3925 309159 10.78 8/28/2017 3 10 13.694 309170 8.66 8/29/2017 2 22 9.383636364 309190 7.19 8/31/2017 0 24 10.33791667 309218 8.49 6/22/2017 70 1 8.49 309250 18.27 7/30/2017 32 1 18.27 309358 8 8/31/2017 0 2 11.99 309418 43.21 8/13/2017 18 2 26.35 309421 6.49 8/26/2017 5 7 10.72428571 309440 20.37 6/24/2017 68 1 20.37 309468 11.37 6/10/2017 82 1 11.37 309538 9.08 7/30/2017 32 4 10.075 309548 7.06 8/30/2017 1 6 7.83 309564 9.57 6/10/2017 82 1 9.57 309616 7.37 6/27/2017 65 1 7.37 309751 8.87 8/5/2017 26 2 8.925 309788 11.21 8/4/2017 27 2 10.81 309842 10.68 8/31/2017 0 17 10.49647059 309938 17.77 8/20/2017 11 2 12.38 310017 8.06 8/31/2017 0 7 12.12 310125 8.47 8/4/2017 27 1 8.47 310126 23.66 8/5/2017 26 5 21.908 310294 12.57 8/13/2017 18 2 9.675 312589 18.34 8/29/2017 2 7 12.93 312591 11.96 8/16/2017 15 7 15.12571429 312593 8.98 7/2/2017 60 1 8.98 312595 19.37 8/18/2017 13 4 11.8025 312633 8.77 8/27/2017 4 13 7.446923077 312634 8.49 6/29/2017 63 4 8.49 312659 10.08 6/23/2017 69 1 10.08 313602 7.49 8/26/2017 5 9 8.704444444 313615 10.47 6/6/2017 86 1 10.47 313618 10.49 7/23/2017 39 1 10.49 313625 7.28 7/26/2017 36 1 7.28 313630 8.37 8/23/2017 8 3 23.95 313635 9.07 8/3/2017 28 2 8.025 313651 7.78 8/30/2017 1 1 7.78 313668 15.77 6/3/2017 89 1 15.77 313679 10.17 8/14/2017 17 2 10.17 313691 10.56 8/8/2017 23 4 12.03 313693 93.86 8/24/2017 7 5 38.108 313695 7.99 8/23/2017 8 8 7.615 313706 17.05 8/27/2017 4 4 16.355 313708 20.87 8/5/2017 26 14 12.20857143 313715 7.99 8/28/2017 3 18 10.63333333 313741 32.5 8/12/2017 19 4 17.245 313744 16.96 8/8/2017 23 1 16.96 313765 7.49 8/19/2017 12 1 7.49 313778 8.38 7/24/2017 38 1 8.38 313785 11.97 8/29/2017 2 7 10.25571429 313818 6.49 7/31/2017 31 1 6.49 313822 20.35 7/18/2017 44 1 20.35 313828 10.28 7/20/2017 42 1 10.28 313843 11.87 6/19/2017 73 1 11.87 313847 19.36 8/25/2017 6 10 9.525 313858 8.08 8/25/2017 6 6 9.076666667 313862 6 7/28/2017 34 4 11.3575 313866 11.16 8/31/2017 0 6 15.6 313868 9.27 8/26/2017 5 1 9.27 313879 10.08 7/3/2017 59 3 12.01 313889 7.97 8/18/2017 13 13 8.322307692 313890 19.86 8/6/2017 25 2 17.51 313891 17.94 7/26/2017 36 4 15.0475 313892 9.88 8/30/2017 1 8 10.39875 313899 9.27 8/31/2017 0 11 12.88909091 313904 19.94 8/9/2017 22 2 14.705 313905 19.12 8/12/2017 19 4 22.3525 313914 9.08 8/18/2017 13 6 13.64333333 313917 10.17 8/28/2017 3 1 10.17 313922 7.99 6/30/2017 62 1 7.99 313923 9.57 8/14/2017 17 3 10.07333333 313927 6.99 7/25/2017 37 1 6.99 313928 8.79 8/31/2017 0 2 7.78 313934 7.19 8/29/2017 2 3 11.01666667 313936 9.38 6/27/2017 65 2 9.83 313937 7.56 8/15/2017 16 2 9.86 313938 22.34 8/30/2017 1 5 18.678 313948 21.16 8/5/2017 26 2 19.81 313951 9.27 8/29/2017 2 1 9.27 313958 8.49 8/30/2017 1 1 8.49 313972 10.77 6/12/2017 80 1 10.77 313975 11.74 7/25/2017 37 3 13.19666667 313989 6.48 8/22/2017 9 2 14.415 313992 8.49 8/22/2017 9 3 8.323333333 313997 9.38 6/12/2017 80 1 9.38 314000 8.27 7/10/2017 52 2 8.27 314003 20.35 8/20/2017 11 9 9.475555556 314005 9.88 8/28/2017 3 34 10.44970588 314006 8.47 8/28/2017 3 8 24.32625 314017 6.88 8/3/2017 28 1 6.88 314018 17.24 7/18/2017 44 1 17.24 314020 21.36 8/29/2017 2 1 21.36 314022 10.28 8/5/2017 26 1 10.28 314023 21.64 7/4/2017 58 2 17.895 314035 12.77 7/10/2017 52 1 12.77 314037 21.74 8/12/2017 19 5 13.4 314048 10.47 8/25/2017 6 4 9.8975 314054 12.78 8/30/2017 1 9 13.40333333 314059 22.94 8/5/2017 26 1 22.94 314082 23.04 8/23/2017 8 1 23.04 314086 13.26 8/21/2017 10 4 12.39 314090 7.08 8/6/2017 25 2 8.08 314091 10.28 6/26/2017 66 2 10.28 314092 13.94 8/7/2017 24 1 13.94 314099 6.19 7/30/2017 32 1 6.19 314107 24.35 8/18/2017 13 2 21.155 314108 8.17 8/31/2017 0 25 9.0932 314111 10.58 8/28/2017 3 5 10.816 314114 7.23 8/16/2017 15 2 7.23 314120 27.24 7/22/2017 40 1 27.24 314121 14.37 8/7/2017 24 1 14.37 314122 17.66 6/21/2017 71 1 17.66 314127 21.16 8/28/2017 3 6 19.955 314134 24.62 6/30/2017 62 1 24.62 314140 27.72 8/25/2017 6 36 9.754166667 314143 14.48 8/17/2017 14 3 12.10666667 314145 21.56 7/14/2017 48 4 18.0125 314146 8.26 8/15/2017 16 5 9.788 314153 13.17 8/1/2017 30 3 15.4 314160 24.56 8/9/2017 22 3 12.84 314161 16.15 8/29/2017 2 13 18.17 314163 7.88 8/21/2017 10 2 8.175 314164 9.97 7/14/2017 48 1 9.97 314167 13.46 8/28/2017 3 4 10.96 314173 19.75 6/19/2017 73 1 19.75 314175 50.55 6/12/2017 80 1 50.55 314178 34.04 8/28/2017 3 9 18.92666667 314179 11.47 8/22/2017 9 7 15.49857143 314181 17.97 7/13/2017 49 1 17.97 314186 9.74 7/28/2017 34 1 9.74 314189 6.97 8/29/2017 2 15 9.236666667 314190 10.06 8/6/2017 25 1 10.06 314192 26.76 7/31/2017 31 1 26.76 314198 8.07 8/21/2017 10 2 7.78 314202 21.82 8/12/2017 19 5 16.184 314207 9.67 8/29/2017 2 7 11.39571429 314208 9.27 8/28/2017 3 3 9.27 314214 9.36 8/6/2017 25 3 12.54 314221 10.67 6/30/2017 62 1 10.67 314222 18.39 8/24/2017 7 8 16.1175 314223 62.42 8/24/2017 7 7 33.48285714 314226 16.71 8/16/2017 15 5 12.082 314229 18.56 8/26/2017 5 1 18.56 314231 32.21 7/9/2017 53 1 32.21 314238 16.86 8/13/2017 18 5 13.928 314239 13.66 8/25/2017 6 14 9.75 314246 22.72 8/28/2017 3 3 17.17666667 314255 8.18 8/30/2017 1 2 7.485 314256 10 7/3/2017 59 2 11.68 314258 9.47 8/11/2017 20 1 9.47 314260 18.66 8/4/2017 27 5 16.464 314263 14.16 7/25/2017 37 3 22.13333333 314274 32.82 8/6/2017 25 4 19.73 314276 13.26 8/4/2017 27 3 12.43 314283 20.25 6/16/2017 76 1 20.25 314288 8.07 7/9/2017 53 2 8.67 314289 20.14 8/30/2017 1 9 16.61555556 314296 7.99 6/30/2017 62 2 7.99 314298 7.49 8/28/2017 3 15 8.435333333 314299 30.15 7/11/2017 51 2 21.4 314301 8.69 7/19/2017 43 1 8.69 314306 13.07 7/23/2017 39 3 13.64 314314 7.74 8/31/2017 0 56 7.876071429 314315 18.94 8/17/2017 14 3 16.41333333 314325 6.79 7/29/2017 33 2 7.39 314331 7.57 8/17/2017 14 4 11.9975 314338 10.07 8/24/2017 7 2 10.07 314340 8.07 8/31/2017 0 26 11.98923077 314343 19.34 8/17/2017 14 3 19.74 314344 26.07 8/7/2017 24 1 26.07 314348 19.44 7/31/2017 31 4 16.9 314353 27.14 6/19/2017 73 1 27.14 314355 13.98 7/24/2017 38 1 13.98 314356 9.98 8/29/2017 2 12 10.505 314359 15.54 8/15/2017 16 1 15.54 314371 6.97 8/27/2017 4 18 9.247222222 314375 10.48 7/12/2017 50 7 9.217142857 314376 8.58 7/4/2017 58 6 7.795 314377 9.77 8/15/2017 16 7 13.2 314384 13.66 8/4/2017 27 2 17.995 314387 17.15 7/23/2017 39 3 16.84666667 314389 11.77 8/25/2017 6 2 11.77 314390 19.74 8/23/2017 8 1 19.74 314395 9.67 8/24/2017 7 4 9.1375 314396 7.18 8/25/2017 6 15 7.585333333 314398 12.02 8/22/2017 9 10 11.365 314401 16.54 8/31/2017 0 7 19.61571429 314408 16.27 8/25/2017 6 5 10.136 314410 12.17 7/27/2017 35 3 11.84 314413 8.28 8/29/2017 2 6 7.73 314416 20.65 8/14/2017 17 4 12.075 314420 11.47 8/26/2017 5 9 9.922222222 314424 39.88 6/14/2017 78 1 39.88 314425 8.98 8/3/2017 28 2 8.98 314431 9.87 7/23/2017 39 2 9.12 314434 25.57 8/25/2017 6 2 17.545 314439 7.39 8/29/2017 2 3 7.39 314445 7.67 8/4/2017 27 1 7.67 314446 18.14 8/12/2017 19 1 18.14 314460 7.97 8/31/2017 0 8 11.92875 314466 6.06 8/22/2017 9 3 10.51 314472 20.26 8/30/2017 1 1 20.26 314473 16.95 8/9/2017 22 2 15.025 314474 22.53 8/5/2017 26 3 20.16666667 314475 11.97 6/11/2017 81 1 11.97 314484 8.8 8/27/2017 4 10 9.492 314486 7.19 7/17/2017 45 3 7.186666667 314504 28.33 6/10/2017 82 1 28.33 314509 6.08 7/17/2017 45 3 6.846666667 314512 12.45 8/12/2017 19 5 13.516 314519 14.08 7/31/2017 31 1 14.08 314527 8.08 8/21/2017 10 8 8.51625 314531 8.27 8/31/2017 0 3 9.096666667 314532 6.38 7/10/2017 52 2 7.23 314535 29.81 7/8/2017 54 3 17.15333333 314538 8.27 8/14/2017 17 7 8.647142857 314541 9.27 8/28/2017 3 1 9.27 314544 18.16 7/30/2017 32 5 13.646 314549 8.27 8/24/2017 7 2 11.62 314556 8.07 6/15/2017 77 1 8.07 314566 7.99 8/11/2017 20 1 7.99 314571 10.27 8/29/2017 2 6 10.28666667 314581 49.94 7/25/2017 37 2 41.975 314587 7.97 8/15/2017 16 1 7.97 314595 11.18 8/23/2017 8 9 11.93333333 314597 11.95 7/4/2017 58 1 11.95 314598 10.08 8/28/2017 3 20 10.2225 314600 8.98 8/24/2017 7 2 8.03 314601 24.34 7/16/2017 46 1 24.34 314616 10.08 8/18/2017 13 4 14.52 314619 17.66 8/27/2017 4 21 15.1752381 314623 10.17 8/10/2017 21 5 11.036 314628 18.76 7/19/2017 43 4 14.9125 314632 6.68 8/25/2017 6 4 7.935 314639 17.44 7/12/2017 50 1 17.44 314640 9.67 8/4/2017 27 1 9.67 314646 29.3 6/24/2017 68 1 29.3 314650 9.47 8/31/2017 0 11 11.36727273 314670 8.49 8/30/2017 1 7 8.49 314672 7.18 7/10/2017 52 4 7.585 314678 8.17 8/30/2017 1 6 11.43666667 314688 9.47 8/1/2017 30 1 9.47 314689 29.42 8/6/2017 25 3 28.91666667 314708 20.83 8/30/2017 1 3 12.76 314717 15.36 8/31/2017 0 12 10.28833333 314721 17.26 7/24/2017 38 4 11.6425 314723 6.79 8/26/2017 5 7 8.287142857 314726 8.37 8/18/2017 13 4 9.0675 314727 10.27 8/29/2017 2 3 10.33666667 314728 10.48 8/27/2017 4 3 9.91 314731 10.67 8/31/2017 0 1 10.67 314733 7.18 6/13/2017 79 2 7.68 314738 9.06 8/12/2017 19 10 13.196 314744 18.06 8/31/2017 0 5 19.202 314745 7.78 8/29/2017 2 11 9.722727273 314747 9.76 8/28/2017 3 3 9.693333333 314756 14.27 8/20/2017 11 2 11.625 314762 8.47 8/24/2017 7 1 8.47 314763 9.67 8/4/2017 27 3 9.206666667 314767 11.95 8/29/2017 2 30 11.36366667 314775 8.67 8/22/2017 9 1 8.67 314776 13.47 8/15/2017 16 4 10.7325 314782 8.48 8/27/2017 4 5 9.754 314783 8.57 8/18/2017 13 1 8.57 314785 7.63 8/31/2017 0 7 7.832857143 314787 23.72 8/30/2017 1 3 13.33 314793 6.99 6/10/2017 82 1 6.99 314797 10.78 8/23/2017 8 3 10.78 314803 7.28 8/28/2017 3 9 9.412222222 314807 7.32 7/18/2017 44 2 7.32 314811 11.67 8/31/2017 0 2 9.83 314814 8.27 8/31/2017 0 14 7.998571429 314828 9.85 8/19/2017 12 10 16.641 314829 22.96 7/6/2017 56 1 22.96 314832 9.38 6/8/2017 84 1 9.38 314843 8.28 6/5/2017 87 1 8.28 314863 16.14 6/14/2017 78 1 16.14 314868 7.37 8/21/2017 10 5 14.546 314871 6.98 8/28/2017 3 1 6.98 314882 13.38 7/30/2017 32 1 13.38 314883 7.77 8/25/2017 6 18 8.441666667 314898 9.67 8/31/2017 0 32 7.9753125 314900 6.47 8/15/2017 16 1 6.47 314902 7.44 8/19/2017 12 4 12.2425 314904 16.56 8/16/2017 15 5 15.222 314909 16.27 8/19/2017 12 4 14.9175 314912 7.77 8/1/2017 30 3 8.71 314915 8.16 7/11/2017 51 2 10.18 314933 11.67 8/21/2017 10 9 11.67 314940 9.06 8/8/2017 23 2 12.9 314957 8.57 8/31/2017 0 6 12.78833333 314972 11.47 6/29/2017 63 3 11.14 314975 9.66 8/9/2017 22 2 9.615 314985 9.38 7/7/2017 55 2 8.54 314996 13.54 7/13/2017 49 2 12.295 315002 11.43 7/8/2017 54 2 16.525 315032 7.19 6/23/2017 69 2 8.09 315048 17.98 8/31/2017 0 2 17.98 315051 6.79 7/7/2017 55 4 6.8125 315054 11.97 8/22/2017 9 4 10.025 315056 8.78 6/27/2017 65 3 8.766666667 315059 25.14 8/9/2017 22 1 25.14 315061 30.44 6/24/2017 68 1 30.44 315063 9.67 8/30/2017 1 2 9.72 315070 6.67 8/15/2017 16 4 8.94 315072 16.96 8/15/2017 16 6 17.21833333 315073 16.66 6/19/2017 73 1 16.66 315082 7.67 8/7/2017 24 1 7.67 315083 30.89 6/8/2017 84 1 30.89 315089 9.37 7/19/2017 43 2 9.67 315097 8.44 7/18/2017 44 2 12.13 315098 11.37 6/30/2017 62 1 11.37 315110 9.78 8/16/2017 15 1 9.78 315111 40.17 8/11/2017 20 3 20.54 315116 11.68 7/19/2017 43 1 11.68 315122 8.27 6/30/2017 62 1 8.27 315126 9.59 7/2/2017 60 3 10.34 315128 17.83 8/21/2017 10 1 17.83 315132 7.99 7/25/2017 37 2 12.665 315147 8 8/26/2017 5 3 10.71333333 315155 10 7/3/2017 59 2 9.785 315156 8.16 8/23/2017 8 9 9.218888889 315160 16.77 8/27/2017 4 4 12.85 315161 11.28 8/1/2017 30 1 11.28 315166 7.98 8/28/2017 3 2 10.175 315177 14.05 8/15/2017 16 4 10.45 315184 5.99 6/27/2017 65 3 7.413333333 315187 9.52 8/3/2017 28 3 10.01333333 315191 7.98 8/18/2017 13 3 12.70666667 315195 18.85 7/29/2017 33 1 18.85 315198 10.98 7/27/2017 35 2 18.06 315203 6.99 7/7/2017 55 1 6.99 315204 16.26 8/25/2017 6 3 13.83333333 315205 31.63 8/22/2017 9 4 25.605 315230 20.55 8/12/2017 19 3 21.18666667 315233 20.95 8/5/2017 26 1 20.95 315235 8.47 8/6/2017 25 3 7.71 315242 11.16 6/9/2017 83 1 11.16 315246 8.98 8/30/2017 1 5 8.86 315252 8.99 8/20/2017 11 14 9.035 315262 11.87 8/29/2017 2 7 23.83 315264 13.75 6/3/2017 89 1 13.75 315266 10.59 6/11/2017 81 1 10.59 315270 11.98 8/26/2017 5 1 11.98 315273 15.16 8/24/2017 7 1 15.16 315278 9.28 8/31/2017 0 4 11.775 315287 27.03 8/24/2017 7 3 15.45333333 315293 8.34 8/31/2017 0 4 8.1175 315294 8.47 8/24/2017 7 5 9.28 315295 24.54 8/26/2017 5 8 18.445 315296 8.47 6/1/2017 91 1 8.47 315323 21.94 8/27/2017 4 10 14.309 315329 12.37 7/31/2017 31 3 12.87 315333 6.88 6/18/2017 74 2 6.935 315337 9.28 8/28/2017 3 7 8.272857143 315347 6.78 8/10/2017 21 5 7.678 315348 5.99 8/11/2017 20 4 13.7975 315355 15.74 8/15/2017 16 5 16.822 315364 6.89 8/26/2017 5 7 11.82428571 315372 20.92 8/3/2017 28 4 15.1725 315375 7.55 8/6/2017 25 4 11.4875 315377 11.37 8/25/2017 6 10 10.366 315384 9.47 8/30/2017 1 3 7.546666667 315385 6.47 8/8/2017 23 7 6.727142857 315388 7.89 8/31/2017 0 12 11.265 315391 12 8/21/2017 10 1 12 315396 7.36 6/28/2017 64 1 7.36 315398 12.37 8/27/2017 4 3 10.07666667 315400 17.34 8/25/2017 6 1 17.34 315401 8.98 8/12/2017 19 6 9.126666667 315415 12.36 6/30/2017 62 1 12.36 315417 10.58 8/28/2017 3 5 9.052 315424 8.27 8/23/2017 8 9 10.50222222 315427 9.47 8/5/2017 26 2 10.57 315437 11.87 7/13/2017 49 1 11.87 315440 10.56 7/31/2017 31 3 11.42 315446 6.17 8/3/2017 28 4 17.525 315447 9.08 8/10/2017 21 3 9.806666667 315448 7.99 7/29/2017 33 2 9.28 315449 18.94 8/30/2017 1 2 12.865 315453 13.26 8/21/2017 10 5 8.512 315461 7.18 7/26/2017 36 1 7.18 315466 19.75 8/30/2017 1 4 22.1525 315468 6.99 7/29/2017 33 6 10.36166667 315473 12.94 8/29/2017 2 5 13.476 315474 8.37 8/17/2017 14 3 9.466666667 315477 6.49 8/31/2017 0 1 6.49 315480 18.94 6/25/2017 67 1 18.94 315483 12.07 8/6/2017 25 6 12.48833333 315489 8.17 8/8/2017 23 3 13.06 315492 6.67 8/8/2017 23 1 6.67 315497 9.65 8/21/2017 10 1 9.65 315498 12.36 8/5/2017 26 2 10.265 315499 13.17 7/30/2017 32 1 13.17 315503 8.71 6/29/2017 63 5 12.854 315511 9.67 8/15/2017 16 5 9.992 315513 9.58 8/24/2017 7 2 9.125 315522 8.47 7/12/2017 50 1 8.47 315523 10.47 8/1/2017 30 2 8.63 315532 8.47 8/16/2017 15 5 11.362 315533 10.29 6/7/2017 85 1 10.29 315538 6.39 7/8/2017 54 2 16.51 315542 18.66 7/6/2017 56 1 18.66 315549 21.54 8/22/2017 9 6 20.71333333 315550 59.33 8/1/2017 30 5 19.566 315551 17.56 8/24/2017 7 5 12.908 315552 10.75 7/22/2017 40 3 8.796666667 315556 6.06 7/26/2017 36 2 7.66 315559 14.98 8/15/2017 16 4 21.93 315562 13.15 8/6/2017 25 8 9.9725 315563 9.47 8/30/2017 1 1 9.47 315567 18.77 8/28/2017 3 2 25.955 315575 10.86 8/22/2017 9 5 10.626 315579 7.38 7/31/2017 31 1 7.38 315581 8.78 8/17/2017 14 1 8.78 315582 6.99 8/19/2017 12 1 6.99 315591 22.86 8/11/2017 20 4 22.4925 315599 7.77 8/9/2017 22 1 7.77 315602 6.18 8/20/2017 11 4 6.18 315608 12.36 8/21/2017 10 1 12.36 315609 8.98 7/10/2017 52 2 11.21 315610 7.99 8/25/2017 6 6 14.73833333 315611 8.49 8/31/2017 0 3 8.323333333 315618 0 7/25/2017 37 4 17.85 315629 8.67 8/6/2017 25 4 8.17 315632 14.66 8/15/2017 16 2 10.475 315634 8.47 7/25/2017 37 2 8.82 315638 13.25 7/25/2017 37 2 13.055 315642 17.47 7/22/2017 40 2 12.13 315645 6.99 7/6/2017 56 1 6.99 315649 22.03 8/6/2017 25 1 22.03 315650 8.43 8/25/2017 6 2 9.15 315651 12.94 8/15/2017 16 5 14.666 315654 7.49 8/8/2017 23 2 9.98 315655 13.95 7/28/2017 34 2 11.21 315660 8.27 7/27/2017 35 1 8.27 315663 6.99 8/29/2017 2 5 6.664 315665 9.48 6/30/2017 62 2 8.885 315670 10.07 8/17/2017 14 2 8.47 315672 10.78 8/5/2017 26 1 10.78 315673 12.48 8/3/2017 28 2 17.265 315680 14.26 8/21/2017 10 4 14.13 315684 8.07 6/2/2017 90 1 8.07 315685 11.97 7/20/2017 42 3 10.64666667 315688 11.9 8/27/2017 4 3 10.49 315689 39.9 7/2/2017 60 1 39.9 315697 30.23 8/4/2017 27 3 18.56 315700 11.05 8/6/2017 25 4 10.335 315702 12.06 8/4/2017 27 2 10.765 315703 8.47 8/20/2017 11 2 9.915 315705 8.07 8/14/2017 17 3 8.043333333 315707 23.34 7/29/2017 33 1 23.34 315711 10.57 7/6/2017 56 4 11.3325 315712 22.36 8/7/2017 24 1 22.36 315717 8.88 7/22/2017 40 1 8.88 315723 10.47 8/21/2017 10 6 10.95166667 315725 6.79 8/22/2017 9 6 7.338333333 315726 10.97 6/23/2017 69 2 9.48 315730 12.01 8/30/2017 1 4 11.875 315731 28.73 8/15/2017 16 5 14.042 315740 7.28 8/9/2017 22 2 7.28 315754 8.18 6/11/2017 81 1 8.18 315755 9.24 8/27/2017 4 8 8.22375 315760 22 7/3/2017 59 1 22 315768 18.76 8/4/2017 27 2 19.405 315779 21.55 6/10/2017 82 1 21.55 315785 6.79 6/5/2017 87 1 6.79 315788 10.58 8/15/2017 16 3 10.05333333 315793 6.79 7/25/2017 37 4 9.23 315799 12.59 8/23/2017 8 3 10.35333333 315802 11.86 8/31/2017 0 3 17.02 315809 8.76 8/1/2017 30 2 8.76 315817 11.26 7/30/2017 32 2 9.765 315818 9.67 6/20/2017 72 1 9.67 315826 8.48 8/6/2017 25 4 8.8525 315845 11.07 8/5/2017 26 1 11.07 315853 8.47 7/29/2017 33 5 16.268 315854 27.93 7/9/2017 53 1 27.93 315855 12.76 7/5/2017 57 4 10.57 315856 10.78 7/28/2017 34 1 10.78 315860 17.46 8/24/2017 7 1 17.46 315861 8.49 8/8/2017 23 2 7.39 315873 32.84 7/30/2017 32 1 32.84 315875 20.75 6/12/2017 80 1 20.75 315883 19.64 6/13/2017 79 1 19.64 On 13 October 2017 at 10:35, PIKAL Petr <petr.pikal at precheza.cz> wrote:> Hi > > Your statement about attaching data is problematic. We cannot do much with > it. Instead use output from dput(yourdata) to show us what exactly your > data look like. > > We also do not know how do you want to split your data. It would be nice > if you can show also what should be the bins with respective data. Unless > you provide this information you probably would not get any sensible answer. > > Cheers > Petr > > > > -----Original Message----- > > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Hemant > Sain > > Sent: Thursday, October 12, 2017 10:18 AM > > To: r-help mailing list <r-help at r-project.org> > > Subject: [R] How to define proper breaks in RFM analysis > > > > Hello, > > I'm working on RFM analysis and i wanted to define my own breaks but my > > frequency distribution is not normally distributed so when I'm using > quartile its > > not giving the optimal results. > > so I'm looking for a better approach where i can define breaks > dynamically > > because after visualization i can do it easily but i want to apply this > model so > > that it can automatically define the breaks according to data set. > > I'm attaching sample data for reference. > > > > Thanks > > > > *Freq* > > 5 > > 15 > > 1 > > 8 > > 2 > > 2 > > 2 > > 1 > > 1 > > 2 > > 2 > > 1 > > 1 > > 1 > > 1 > > 4 > > 10 > > 22 > > 24 > > 1 > > 1 > > 2 > > 2 > > 7 > > 1 > > 1 > > 4 > > 6 > > 1 > > 1 > > 2 > > 2 > > 17 > > 2 > > 7 > > 1 > > 5 > > 2 > > 7 > > 7 > > 1 > > 4 > > 13 > > 4 > > 1 > > 9 > > 1 > > 1 > > 1 > > 3 > > 2 > > 1 > > 1 > > 2 > > 4 > > 5 > > 8 > > 4 > > 14 > > 18 > > 4 > > 1 > > 1 > > 1 > > 7 > > 1 > > 1 > > 1 > > 1 > > 10 > > 6 > > 4 > > 6 > > 1 > > 3 > > 13 > > 2 > > 4 > > 8 > > 11 > > 2 > > 4 > > 6 > > 1 > > 1 > > 3 > > 1 > > 2 > > 3 > > 2 > > 2 > > 5 > > 2 > > 1 > > 1 > > 1 > > 3 > > 2 > > 3 > > 1 > > 2 > > 9 > > 34 > > 8 > > 1 > > 1 > > 1 > > 1 > > 2 > > 1 > > 5 > > 4 > > 9 > > 1 > > 1 > > 4 > > 2 > > 2 > > 1 > > 1 > > 2 > > 25 > > 5 > > 2 > > 1 > > 1 > > 1 > > 6 > > 1 > > 36 > > 3 > > 4 > > 5 > > 3 > > 3 > > 13 > > 2 > > 1 > > 4 > > 1 > > 1 > > 9 > > 7 > > 1 > > 1 > > 15 > > 1 > > 1 > > 2 > > 5 > > 7 > > 3 > > 3 > > 1 > > 8 > > 7 > > 5 > > 1 > > 1 > > 5 > > 14 > > 3 > > 2 > > 2 > > 1 > > 5 > > 3 > > 4 > > 3 > > 1 > > 2 > > 9 > > 2 > > 15 > > 2 > > 1 > > 3 > > 56 > > 3 > > 2 > > 4 > > 2 > > 26 > > 3 > > 1 > > 4 > > 1 > > 1 > > 12 > > 1 > > 18 > > 7 > > 6 > > 7 > > 2 > > 3 > > 2 > > 1 > > 4 > > 15 > > 10 > > 7 > > 5 > > 3 > > 6 > > 4 > > 9 > > 1 > > 2 > > 2 > > 2 > > 3 > > 1 > > 1 > > 8 > > 3 > > 1 > > 2 > > 3 > > 1 > > 10 > > 3 > > 1 > > 3 > > 5 > > 1 > > 8 > > 3 > > 2 > > 3 > > 7 > > 1 > > 5 > > 2 > > 1 > > 1 > > 6 > > 2 > > 1 > > 9 > > 1 > > 20 > > 2 > > 1 > > 4 > > 21 > > 5 > > 4 > > 4 > > 1 > > 1 > > 1 > > 11 > > 7 > > 4 > > 6 > > 1 > > 3 > > 3 > > 12 > > 4 > > 7 > > 4 > > 3 > > 3 > > 1 > > 2 > > 10 > > 5 > > 11 > > 3 > > 2 > > 1 > > 3 > > 30 > > 1 > > 4 > > 5 > > 1 > > 7 > > 3 > > 1 > > 3 > > 9 > > 2 > > 2 > > 14 > > 10 > > 1 > > 1 > > 1 > > 1 > > 5 > > 1 > > 1 > > 18 > > 32 > > 1 > > 4 > > 5 > > 4 > > 3 > > 2 > > 9 > > 2 > > 6 > > 3 > > 2 > > 2 > > 2 > > 2 > > 2 > > 2 > > 4 > > 4 > > 3 > > 1 > > 1 > > 2 > > 4 > > 6 > > 1 > > 1 > > 1 > > 2 > > 2 > > 1 > > 1 > > 3 > > 1 > > 1 > > 3 > > 1 > > 2 > > 3 > > 2 > > 9 > > 4 > > 1 > > 2 > > 4 > > 3 > > 3 > > 3 > > 1 > > 2 > > 1 > > 3 > > 4 > > 3 > > 1 > > 3 > > 1 > > 5 > > 14 > > 7 > > 1 > > 1 > > 1 > > 1 > > 4 > > 3 > > 4 > > 5 > > 8 > > 1 > > 10 > > 3 > > 2 > > 7 > > 5 > > 4 > > 5 > > 7 > > 4 > > 4 > > 10 > > 3 > > 7 > > 12 > > 1 > > 1 > > 3 > > 1 > > 6 > > 1 > > 5 > > 9 > > 2 > > 1 > > 3 > > 4 > > 3 > > 2 > > 2 > > 5 > > 1 > > 4 > > 6 > > 5 > > 3 > > 1 > > 1 > > 6 > > 3 > > 1 > > 1 > > 2 > > 1 > > 5 > > 5 > > 2 > > 1 > > 2 > > 5 > > 1 > > 2 > > 1 > > 6 > > 5 > > 5 > > 3 > > 2 > > 4 > > 8 > > 1 > > 2 > > 5 > > 1 > > 1 > > 1 > > 4 > > 1 > > 4 > > 1 > > 2 > > 6 > > 3 > > 4 > > 4 > > 2 > > 2 > > 2 > > 2 > > 1 > > 1 > > 2 > > 5 > > 2 > > 2 > > 1 > > 5 > > 2 > > 2 > > 1 > > 2 > > 4 > > 1 > > 3 > > 3 > > 1 > > 3 > > 4 > > 2 > > 2 > > 3 > > 1 > > 4 > > 1 > > 1 > > 6 > > 6 > > 2 > > 4 > > 5 > > 2 > > 1 > > 8 > > 1 > > 2 > > 1 > > 1 > > 3 > > 4 > > 3 > > 3 > > 2 > > 2 > > 1 > > 4 > > 1 > > 5 > > 1 > > 4 > > 1 > > 1 > > 2 > > 1 > > 1 > > 1 > > 8 > > 1 > > 1 > > 1 > > 1 > > 1 > > 3 > > 3 > > 5 > > 2 > > 3 > > 1 > > 1 > > 5 > > 2 > > 3 > > 6 > > 3 > > 3 > > 14 > > 2 > > 1 > > 1 > > 2 > > 1 > > 2 > > 4 > > 2 > > 1 > > 6 > > 1 > > 7 > > 2 > > 3 > > 3 > > 2 > > 2 > > 2 > > 2 > > 1 > > 2 > > 4 > > 1 > > 6 > > 2 > > 5 > > 2 > > 1 > > 2 > > 2 > > 5 > > 8 > > 4 > > 1 > > 1 > > 1 > > 1 > > 4 > > 1 > > 3 > > 2 > > 1 > > 2 > > 2 > > 3 > > 3 > > 3 > > 6 > > 1 > > 1 > > 1 > > 5 > > 7 > > 1 > > 5 > > 2 > > 1 > > 1 > > 1 > > 3 > > 20 > > 2 > > 3 > > 3 > > 1 > > 2 > > 1 > > 15 > > 4 > > 4 > > 1 > > 1 > > 2 > > 1 > > 1 > > 3 > > 2 > > 6 > > 5 > > 1 > > 5 > > 1 > > 7 > > 4 > > 3 > > 2 > > 5 > > 2 > > 1 > > 1 > > 3 > > 2 > > 6 > > 2 > > 4 > > 2 > > 1 > > 24 > > 4 > > 17 > > 1 > > 3 > > 2 > > 2 > > 2 > > 2 > > 8 > > 1 > > 3 > > 1 > > 9 > > 2 > > 4 > > 1 > > 1 > > 6 > > 3 > > 4 > > 1 > > 9 > > 2 > > 1 > > 3 > > 2 > > 6 > > 2 > > 1 > > 3 > > 1 > > 20 > > 3 > > 4 > > 7 > > 3 > > 7 > > 1 > > 7 > > 1 > > 5 > > 2 > > 1 > > 1 > > 1 > > 2 > > 1 > > 2 > > 4 > > 1 > > 1 > > 2 > > 3 > > 4 > > 1 > > 4 > > 1 > > 1 > > 1 > > 1 > > 1 > > 2 > > 1 > > 6 > > 2 > > 3 > > 2 > > 1 > > 9 > > 8 > > 11 > > 1 > > 1 > > 2 > > 1 > > 3 > > 1 > > 2 > > 15 > > 5 > > 2 > > 2 > > 9 > > 1 > > 4 > > 2 > > 1 > > 1 > > 14 > > 1 > > 1 > > 2 > > 1 > > 3 > > 10 > > 1 > > 1 > > 3 > > 1 > > 1 > > 1 > > 4 > > 2 > > 8 > > 1 > > 2 > > 2 > > 1 > > 11 > > 1 > > 3 > > 1 > > 7 > > 1 > > 3 > > 10 > > 3 > > 3 > > 1 > > 1 > > 1 > > 11 > > 1 > > 2 > > 1 > > 1 > > 2 > > 2 > > 5 > > 5 > > 4 > > 1 > > 2 > > 5 > > 2 > > 4 > > 3 > > 1 > > 1 > > 2 > > 2 > > 4 > > 2 > > 1 > > 1 > > 4 > > 1 > > 4 > > 1 > > 5 > > 1 > > 1 > > 2 > > 1 > > 4 > > 7 > > 1 > > 2 > > 1 > > 2 > > 9 > > 3 > > 1 > > 7 > > 2 > > 2 > > 1 > > 2 > > 3 > > 5 > > 2 > > 7 > > 1 > > 5 > > 1 > > 1 > > 2 > > 2 > > 2 > > 4 > > 2 > > 8 > > 4 > > 6 > > 1 > > 1 > > 1 > > 1 > > 1 > > 16 > > 2 > > 1 > > 6 > > 4 > > 4 > > 1 > > 1 > > 1 > > 1 > > 4 > > 3 > > 2 > > 6 > > 11 > > 10 > > 21 > > 2 > > 1 > > 1 > > 3 > > 2 > > 2 > > 2 > > 7 > > 1 > > 6 > > 4 > > 1 > > 7 > > 4 > > 11 > > 1 > > 2 > > 8 > > 1 > > 1 > > 1 > > 1 > > 2 > > 17 > > 1 > > 2 > > 3 > > 4 > > 2 > > 1 > > 2 > > 2 > > 4 > > 3 > > 2 > > 3 > > 1 > > 3 > > 3 > > 1 > > 3 > > 37 > > 4 > > 3 > > 1 > > 2 > > 1 > > 1 > > 3 > > 1 > > 2 > > 3 > > 1 > > 5 > > 1 > > 2 > > 1 > > 3 > > 2 > > 3 > > 3 > > 4 > > 4 > > 2 > > 4 > > 1 > > 1 > > 3 > > 3 > > 2 > > 1 > > 2 > > 1 > > 1 > > 3 > > 1 > > 1 > > 3 > > 3 > > 4 > > 2 > > 4 > > 1 > > 1 > > 1 > > 10 > > 3 > > 2 > > 2 > > 2 > > 2 > > 2 > > 2 > > 1 > > 19 > > 2 > > 2 > > 4 > > 1 > > 3 > > 1 > > 13 > > 5 > > 2 > > 1 > > 2 > > 2 > > 4 > > 2 > > 1 > > 3 > > 5 > > 1 > > 1 > > 1 > > 6 > > 3 > > 9 > > 4 > > 1 > > 1 > > 1 > > 3 > > 1 > > 17 > > 4 > > 1 > > 4 > > 6 > > 2 > > 1 > > 2 > > 4 > > 4 > > 2 > > 2 > > 2 > > 4 > > 4 > > 1 > > 1 > > 1 > > 2 > > 7 > > 2 > > 1 > > 2 > > 8 > > 1 > > 1 > > 7 > > 4 > > 1 > > 2 > > 1 > > 1 > > 3 > > 1 > > 3 > > 1 > > 1 > > 3 > > 5 > > 8 > > 1 > > 1 > > 4 > > 1 > > 1 > > 15 > > 1 > > 1 > > 6 > > 2 > > 3 > > 3 > > 8 > > 4 > > 1 > > 4 > > 2 > > 4 > > 2 > > 5 > > 4 > > 4 > > 1 > > 1 > > 7 > > 1 > > 10 > > 1 > > 10 > > 2 > > 15 > > 7 > > 3 > > 1 > > 3 > > 2 > > 19 > > 2 > > 9 > > 1 > > 10 > > 2 > > 1 > > 2 > > 2 > > 4 > > 6 > > 1 > > 4 > > 3 > > 1 > > 2 > > 3 > > 2 > > 1 > > 3 > > 7 > > 1 > > 4 > > 2 > > 13 > > 2 > > 5 > > 3 > > 6 > > 2 > > 1 > > 2 > > 1 > > 5 > > 1 > > > > > > -- > > hemantsain.com > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posti > ng-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > ________________________________ > Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou > ur?eny pouze jeho adres?t?m. > Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? > neprodlen? jeho odes?latele. 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Hi You expect us to solve your problem but you ignore advice already recieved. Your data are unreadable, use dput(yourdata) instead. see ?dput> test<-read.table("clipboard", heade=T)Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : line 115 did not have 6 elements What is ?ideal interval? can you define it? Should it be such to provide eqal number of observations? Or maybe you could normalise your values and use quartile method. Cheers Petr From: Hemant Sain [mailto:hemantsain55 at gmail.com] Sent: Friday, October 13, 2017 8:51 AM To: PIKAL Petr <petr.pikal at precheza.cz> Cc: r-help mailing list <r-help at r-project.org> Subject: Re: [R] How to define proper breaks in RFM analysis Hey, i want to define 3 ideal breaks (bin) for each variable one of those variables is attached in the previous email, i don't want to consider quartile method because quartile is not working ideally for that data set because data distribution is non normal. so i want you to suggest another method so that i can define 3 breaks with the ideal interval for Recency, frequency and monetary to calculate RFM score. i'm again attaching you some of the data set. please look into it and help me with the R code. Thanks Data user_id subtotal_amount created_at Recency Frequency Monetary 194849 6.99 8/22/2017 9 5 9.996 194978 14.78 8/28/2017 3 15 16.308 198614 18.44 7/31/2017 31 1 18.44 234569 34.99 8/20/2017 11 8 13.5075 252686 7.99 7/31/2017 31 2 7.99 291719 21.26 8/25/2017 6 2 15.67 291787 46.1 8/31/2017 0 2 32.57 292630 24.34 7/31/2017 31 1 24.34 295204 21.86 7/18/2017 44 1 21.86 295989 8.98 8/20/2017 11 2 14.095 298883 14.38 8/24/2017 7 2 11.185 308824 10.77 7/31/2017 31 1 10.77 308874 8.29 6/11/2017 81 1 8.29 309088 17.16 8/3/2017 28 1 17.16 309126 20.54 7/30/2017 32 1 20.54 309127 15.24 8/2/2017 29 4 13.3925 309159 10.78 8/28/2017 3 10 13.694 309170 8.66 8/29/2017 2 22 9.383636364 309190 7.19 8/31/2017 0 24 10.33791667 309218 8.49 6/22/2017 70 1 8.49 309250 18.27 7/30/2017 32 1 18.27 309358 8 8/31/2017 0 2 11.99 309418 43.21 8/13/2017 18 2 26.35 309421 6.49 8/26/2017 5 7 10.72428571 309440 20.37 6/24/2017 68 1 20.37 309468 11.37 6/10/2017 82 1 11.37 309538 9.08 7/30/2017 32 4 10.075 309548 7.06 8/30/2017 1 6 7.83 309564 9.57 6/10/2017 82 1 9.57 309616 7.37 6/27/2017 65 1 7.37 309751 8.87 8/5/2017 26 2 8.925 309788 11.21 8/4/2017 27 2 10.81 309842 10.68 8/31/2017 0 17 10.49647059 309938 17.77 8/20/2017 11 2 12.38 310017 8.06 8/31/2017 0 7 12.12 310125 8.47 8/4/2017 27 1 8.47 310126 23.66 8/5/2017 26 5 21.908 310294 12.57 8/13/2017 18 2 9.675 312589 18.34 8/29/2017 2 7 12.93 312591 11.96 8/16/2017 15 7 15.12571429 312593 8.98 7/2/2017 60 1 8.98 312595 19.37 8/18/2017 13 4 11.8025 312633 8.77 8/27/2017 4 13 7.446923077 312634 8.49 6/29/2017 63 4 8.49 312659 10.08 6/23/2017 69 1 10.08 313602 7.49 8/26/2017 5 9 8.704444444 313615 10.47 6/6/2017 86 1 10.47 313618 10.49 7/23/2017 39 1 10.49 313625 7.28 7/26/2017 36 1 7.28 313630 8.37 8/23/2017 8 3 23.95 313635 9.07 8/3/2017 28 2 8.025 313651 7.78 8/30/2017 1 1 7.78 313668 15.77 6/3/2017 89 1 15.77 313679 10.17 8/14/2017 17 2 10.17 313691 10.56 8/8/2017 23 4 12.03 313693 93.86 8/24/2017 7 5 38.108 313695 7.99 8/23/2017 8 8 7.615 313706 17.05 8/27/2017 4 4 16.355 313708 20.87 8/5/2017 26 14 12.20857143 313715 7.99 8/28/2017 3 18 10.63333333 313741 32.5 8/12/2017 19 4 17.245 313744 16.96 8/8/2017 23 1 16.96 313765 7.49 8/19/2017 12 1 7.49 313778 8.38 7/24/2017 38 1 8.38 313785 11.97 8/29/2017 2 7 10.25571429 313818 6.49 7/31/2017 31 1 6.49 313822 20.35 7/18/2017 44 1 20.35 313828 10.28 7/20/2017 42 1 10.28 313843 11.87 6/19/2017 73 1 11.87 313847 19.36 8/25/2017 6 10 9.525 313858 8.08 8/25/2017 6 6 9.076666667 313862 6 7/28/2017 34 4 11.3575 313866 11.16 8/31/2017 0 6 15.6 313868 9.27 8/26/2017 5 1 9.27 313879 10.08 7/3/2017 59 3 12.01 313889 7.97 8/18/2017 13 13 8.322307692 313890 19.86 8/6/2017 25 2 17.51 313891 17.94 7/26/2017 36 4 15.0475 313892 9.88 8/30/2017 1 8 10.39875 313899 9.27 8/31/2017 0 11 12.88909091 313904 19.94 8/9/2017 22 2 14.705 313905 19.12 8/12/2017 19 4 22.3525 313914 9.08 8/18/2017 13 6 13.64333333 313917 10.17 8/28/2017 3 1 10.17 313922 7.99 6/30/2017 62 1 7.99 313923 9.57 8/14/2017 17 3 10.07333333 313927 6.99 7/25/2017 37 1 6.99 313928 8.79 8/31/2017 0 2 7.78 313934 7.19 8/29/2017 2 3 11.01666667 313936 9.38 6/27/2017 65 2 9.83 313937 7.56 8/15/2017 16 2 9.86 313938 22.34 8/30/2017 1 5 18.678 313948 21.16 8/5/2017 26 2 19.81 313951 9.27 8/29/2017 2 1 9.27 313958 8.49 8/30/2017 1 1 8.49 313972 10.77 6/12/2017 80 1 10.77 313975 11.74 7/25/2017 37 3 13.19666667 313989 6.48 8/22/2017 9 2 14.415 313992 8.49 8/22/2017 9 3 8.323333333 313997 9.38 6/12/2017 80 1 9.38 314000 8.27 7/10/2017 52 2 8.27 314003 20.35 8/20/2017 11 9 9.475555556 314005 9.88 8/28/2017 3 34 10.44970588 314006 8.47 8/28/2017 3 8 24.32625 314017 6.88 8/3/2017 28 1 6.88 314018 17.24 7/18/2017 44 1 17.24 314020 21.36 8/29/2017 2 1 21.36 314022 10.28 8/5/2017 26 1 10.28 314023 21.64 7/4/2017 58 2 17.895 314035 12.77 7/10/2017 52 1 12.77 314037 21.74 8/12/2017 19 5 13.4 314048 10.47 8/25/2017 6 4 9.8975 314054 12.78 8/30/2017 1 9 13.40333333 314059 22.94 8/5/2017 26 1 22.94 314082 23.04 8/23/2017 8 1 23.04 314086 13.26 8/21/2017 10 4 12.39 314090 7.08 8/6/2017 25 2 8.08 314091 10.28 6/26/2017 66 2 10.28 314092 13.94 8/7/2017 24 1 13.94 314099 6.19 7/30/2017 32 1 6.19 314107 24.35 8/18/2017 13 2 21.155 314108 8.17 8/31/2017 0 25 9.0932 314111 10.58 8/28/2017 3 5 10.816 314114 7.23 8/16/2017 15 2 7.23 314120 27.24 7/22/2017 40 1 27.24 314121 14.37 8/7/2017 24 1 14.37 314122 17.66 6/21/2017 71 1 17.66 314127 21.16 8/28/2017 3 6 19.955 314134 24.62 6/30/2017 62 1 24.62 314140 27.72 8/25/2017 6 36 9.754166667 314143 14.48 8/17/2017 14 3 12.10666667 314145 21.56 7/14/2017 48 4 18.0125 314146 8.26 8/15/2017 16 5 9.788 314153 13.17 8/1/2017 30 3 15.4 314160 24.56 8/9/2017 22 3 12.84 314161 16.15 8/29/2017 2 13 18.17 314163 7.88 8/21/2017 10 2 8.175 314164 9.97 7/14/2017 48 1 9.97 314167 13.46 8/28/2017 3 4 10.96 314173 19.75 6/19/2017 73 1 19.75 314175 50.55 6/12/2017 80 1 50.55 314178 34.04 8/28/2017 3 9 18.92666667 314179 11.47 8/22/2017 9 7 15.49857143 314181 17.97 7/13/2017 49 1 17.97 314186 9.74 7/28/2017 34 1 9.74 314189 6.97 8/29/2017 2 15 9.236666667 314190 10.06 8/6/2017 25 1 10.06 314192 26.76 7/31/2017 31 1 26.76 314198 8.07 8/21/2017 10 2 7.78 314202 21.82 8/12/2017 19 5 16.184 314207 9.67 8/29/2017 2 7 11.39571429 314208 9.27 8/28/2017 3 3 9.27 314214 9.36 8/6/2017 25 3 12.54 314221 10.67 6/30/2017 62 1 10.67 314222 18.39 8/24/2017 7 8 16.1175 314223 62.42 8/24/2017 7 7 33.48285714 314226 16.71 8/16/2017 15 5 12.082 314229 18.56 8/26/2017 5 1 18.56 314231 32.21 7/9/2017 53 1 32.21 314238 16.86 8/13/2017 18 5 13.928 314239 13.66 8/25/2017 6 14 9.75 314246 22.72 8/28/2017 3 3 17.17666667 314255 8.18 8/30/2017 1 2 7.485 314256 10 7/3/2017 59 2 11.68 314258 9.47 8/11/2017 20 1 9.47 314260 18.66 8/4/2017 27 5 16.464 314263 14.16 7/25/2017 37 3 22.13333333 314274 32.82 8/6/2017 25 4 19.73 314276 13.26 8/4/2017 27 3 12.43 314283 20.25 6/16/2017 76 1 20.25 314288 8.07 7/9/2017 53 2 8.67 314289 20.14 8/30/2017 1 9 16.61555556 314296 7.99 6/30/2017 62 2 7.99 314298 7.49 8/28/2017 3 15 8.435333333 314299 30.15 7/11/2017 51 2 21.4 314301 8.69 7/19/2017 43 1 8.69 314306 13.07 7/23/2017 39 3 13.64 314314 7.74 8/31/2017 0 56 7.876071429 314315 18.94 8/17/2017 14 3 16.41333333 314325 6.79 7/29/2017 33 2 7.39 314331 7.57 8/17/2017 14 4 11.9975 314338 10.07 8/24/2017 7 2 10.07 314340 8.07 8/31/2017 0 26 11.98923077 314343 19.34 8/17/2017 14 3 19.74 314344 26.07 8/7/2017 24 1 26.07 314348 19.44 7/31/2017 31 4 16.9 314353 27.14 6/19/2017 73 1 27.14 314355 13.98 7/24/2017 38 1 13.98 314356 9.98 8/29/2017 2 12 10.505 314359 15.54 8/15/2017 16 1 15.54 314371 6.97 8/27/2017 4 18 9.247222222 314375 10.48 7/12/2017 50 7 9.217142857 314376 8.58 7/4/2017 58 6 7.795 314377 9.77 8/15/2017 16 7 13.2 314384 13.66 8/4/2017 27 2 17.995 314387 17.15 7/23/2017 39 3 16.84666667 314389 11.77 8/25/2017 6 2 11.77 314390 19.74 8/23/2017 8 1 19.74 314395 9.67 8/24/2017 7 4 9.1375 314396 7.18 8/25/2017 6 15 7.585333333 314398 12.02 8/22/2017 9 10 11.365 314401 16.54 8/31/2017 0 7 19.61571429 314408 16.27 8/25/2017 6 5 10.136 314410 12.17 7/27/2017 35 3 11.84 314413 8.28 8/29/2017 2 6 7.73 314416 20.65 8/14/2017 17 4 12.075 314420 11.47 8/26/2017 5 9 9.922222222 314424 39.88 6/14/2017 78 1 39.88 314425 8.98 8/3/2017 28 2 8.98 314431 9.87 7/23/2017 39 2 9.12 314434 25.57 8/25/2017 6 2 17.545 314439 7.39 8/29/2017 2 3 7.39 314445 7.67 8/4/2017 27 1 7.67 314446 18.14 8/12/2017 19 1 18.14 314460 7.97 8/31/2017 0 8 11.92875 314466 6.06 8/22/2017 9 3 10.51 314472 20.26 8/30/2017 1 1 20.26 314473 16.95 8/9/2017 22 2 15.025 314474 22.53 8/5/2017 26 3 20.16666667 314475 11.97 6/11/2017 81 1 11.97 314484 8.8 8/27/2017 4 10 9.492 314486 7.19 7/17/2017 45 3 7.186666667 314504 28.33 6/10/2017 82 1 28.33 314509 6.08 7/17/2017 45 3 6.846666667 314512 12.45 8/12/2017 19 5 13.516 314519 14.08 7/31/2017 31 1 14.08 314527 8.08 8/21/2017 10 8 8.51625 314531 8.27 8/31/2017 0 3 9.096666667 314532 6.38 7/10/2017 52 2 7.23 314535 29.81 7/8/2017 54 3 17.15333333 314538 8.27 8/14/2017 17 7 8.647142857 314541 9.27 8/28/2017 3 1 9.27 314544 18.16 7/30/2017 32 5 13.646 314549 8.27 8/24/2017 7 2 11.62 314556 8.07 6/15/2017 77 1 8.07 314566 7.99 8/11/2017 20 1 7.99 314571 10.27 8/29/2017 2 6 10.28666667 314581 49.94 7/25/2017 37 2 41.975 314587 7.97 8/15/2017 16 1 7.97 314595 11.18 8/23/2017 8 9 11.93333333 314597 11.95 7/4/2017 58 1 11.95 314598 10.08 8/28/2017 3 20 10.2225 314600 8.98 8/24/2017 7 2 8.03 314601 24.34 7/16/2017 46 1 24.34 314616 10.08 8/18/2017 13 4 14.52 314619 17.66 8/27/2017 4 21 15.1752381 314623 10.17 8/10/2017 21 5 11.036 314628 18.76 7/19/2017 43 4 14.9125 314632 6.68 8/25/2017 6 4 7.935 314639 17.44 7/12/2017 50 1 17.44 314640 9.67 8/4/2017 27 1 9.67 314646 29.3 6/24/2017 68 1 29.3 314650 9.47 8/31/2017 0 11 11.36727273 314670 8.49 8/30/2017 1 7 8.49 314672 7.18 7/10/2017 52 4 7.585 314678 8.17 8/30/2017 1 6 11.43666667 314688 9.47 8/1/2017 30 1 9.47 314689 29.42 8/6/2017 25 3 28.91666667 314708 20.83 8/30/2017 1 3 12.76 314717 15.36 8/31/2017 0 12 10.28833333 314721 17.26 7/24/2017 38 4 11.6425 314723 6.79 8/26/2017 5 7 8.287142857 314726 8.37 8/18/2017 13 4 9.0675 314727 10.27 8/29/2017 2 3 10.33666667 314728 10.48 8/27/2017 4 3 9.91 314731 10.67 8/31/2017 0 1 10.67 314733 7.18 6/13/2017 79 2 7.68 314738 9.06 8/12/2017 19 10 13.196 314744 18.06 8/31/2017 0 5 19.202 314745 7.78 8/29/2017 2 11 9.722727273 314747 9.76 8/28/2017 3 3 9.693333333 314756 14.27 8/20/2017 11 2 11.625 314762 8.47 8/24/2017 7 1 8.47 314763 9.67 8/4/2017 27 3 9.206666667 314767 11.95 8/29/2017 2 30 11.36366667 314775 8.67 8/22/2017 9 1 8.67 314776 13.47 8/15/2017 16 4 10.7325 314782 8.48 8/27/2017 4 5 9.754 314783 8.57 8/18/2017 13 1 8.57 314785 7.63 8/31/2017 0 7 7.832857143 314787 23.72 8/30/2017 1 3 13.33 314793 6.99 6/10/2017 82 1 6.99 314797 10.78 8/23/2017 8 3 10.78 314803 7.28 8/28/2017 3 9 9.412222222 314807 7.32 7/18/2017 44 2 7.32 314811 11.67 8/31/2017 0 2 9.83 314814 8.27 8/31/2017 0 14 7.998571429 314828 9.85 8/19/2017 12 10 16.641 314829 22.96 7/6/2017 56 1 22.96 314832 9.38 6/8/2017 84 1 9.38 314843 8.28 6/5/2017 87 1 8.28 314863 16.14 6/14/2017 78 1 16.14 314868 7.37 8/21/2017 10 5 14.546 314871 6.98 8/28/2017 3 1 6.98 314882 13.38 7/30/2017 32 1 13.38 314883 7.77 8/25/2017 6 18 8.441666667 314898 9.67 8/31/2017 0 32 7.9753125 314900 6.47 8/15/2017 16 1 6.47 314902 7.44 8/19/2017 12 4 12.2425 314904 16.56 8/16/2017 15 5 15.222 314909 16.27 8/19/2017 12 4 14.9175 314912 7.77 8/1/2017 30 3 8.71 314915 8.16 7/11/2017 51 2 10.18 314933 11.67 8/21/2017 10 9 11.67 314940 9.06 8/8/2017 23 2 12.9 314957 8.57 8/31/2017 0 6 12.78833333 314972 11.47 6/29/2017 63 3 11.14 314975 9.66 8/9/2017 22 2 9.615 314985 9.38 7/7/2017 55 2 8.54 314996 13.54 7/13/2017 49 2 12.295 315002 11.43 7/8/2017 54 2 16.525 315032 7.19 6/23/2017 69 2 8.09 315048 17.98 8/31/2017 0 2 17.98 315051 6.79 7/7/2017 55 4 6.8125 315054 11.97 8/22/2017 9 4 10.025 315056 8.78 6/27/2017 65 3 8.766666667 315059 25.14 8/9/2017 22 1 25.14 315061 30.44 6/24/2017 68 1 30.44 315063 9.67 8/30/2017 1 2 9.72 315070 6.67 8/15/2017 16 4 8.94 315072 16.96 8/15/2017 16 6 17.21833333 315073 16.66 6/19/2017 73 1 16.66 315082 7.67 8/7/2017 24 1 7.67 315083 30.89 6/8/2017 84 1 30.89 315089 9.37 7/19/2017 43 2 9.67 315097 8.44 7/18/2017 44 2 12.13 315098 11.37 6/30/2017 62 1 11.37 315110 9.78 8/16/2017 15 1 9.78 315111 40.17 8/11/2017 20 3 20.54 315116 11.68 7/19/2017 43 1 11.68 315122 8.27 6/30/2017 62 1 8.27 315126 9.59 7/2/2017 60 3 10.34 315128 17.83 8/21/2017 10 1 17.83 315132 7.99 7/25/2017 37 2 12.665 315147 8 8/26/2017 5 3 10.71333333 315155 10 7/3/2017 59 2 9.785 315156 8.16 8/23/2017 8 9 9.218888889 315160 16.77 8/27/2017 4 4 12.85 315161 11.28 8/1/2017 30 1 11.28 315166 7.98 8/28/2017 3 2 10.175 315177 14.05 8/15/2017 16 4 10.45 315184 5.99 6/27/2017 65 3 7.413333333 315187 9.52 8/3/2017 28 3 10.01333333 315191 7.98 8/18/2017 13 3 12.70666667 315195 18.85 7/29/2017 33 1 18.85 315198 10.98 7/27/2017 35 2 18.06 315203 6.99 7/7/2017 55 1 6.99 315204 16.26 8/25/2017 6 3 13.83333333 315205 31.63 8/22/2017 9 4 25.605 315230 20.55 8/12/2017 19 3 21.18666667 315233 20.95 8/5/2017 26 1 20.95 315235 8.47 8/6/2017 25 3 7.71 315242 11.16 6/9/2017 83 1 11.16 315246 8.98 8/30/2017 1 5 8.86 315252 8.99 8/20/2017 11 14 9.035 315262 11.87 8/29/2017 2 7 23.83 315264 13.75 6/3/2017 89 1 13.75 315266 10.59 6/11/2017 81 1 10.59 315270 11.98 8/26/2017 5 1 11.98 315273 15.16 8/24/2017 7 1 15.16 315278 9.28 8/31/2017 0 4 11.775 315287 27.03 8/24/2017 7 3 15.45333333 315293 8.34 8/31/2017 0 4 8.1175 315294 8.47 8/24/2017 7 5 9.28 315295 24.54 8/26/2017 5 8 18.445 315296 8.47 6/1/2017 91 1 8.47 315323 21.94 8/27/2017 4 10 14.309 315329 12.37 7/31/2017 31 3 12.87 315333 6.88 6/18/2017 74 2 6.935 315337 9.28 8/28/2017 3 7 8.272857143 315347 6.78 8/10/2017 21 5 7.678 315348 5.99 8/11/2017 20 4 13.7975 315355 15.74 8/15/2017 16 5 16.822 315364 6.89 8/26/2017 5 7 11.82428571 315372 20.92 8/3/2017 28 4 15.1725 315375 7.55 8/6/2017 25 4 11.4875 315377 11.37 8/25/2017 6 10 10.366 315384 9.47 8/30/2017 1 3 7.546666667 315385 6.47 8/8/2017 23 7 6.727142857 315388 7.89 8/31/2017 0 12 11.265 315391 12 8/21/2017 10 1 12 315396 7.36 6/28/2017 64 1 7.36 315398 12.37 8/27/2017 4 3 10.07666667 315400 17.34 8/25/2017 6 1 17.34 315401 8.98 8/12/2017 19 6 9.126666667 315415 12.36 6/30/2017 62 1 12.36 315417 10.58 8/28/2017 3 5 9.052 315424 8.27 8/23/2017 8 9 10.50222222 315427 9.47 8/5/2017 26 2 10.57 315437 11.87 7/13/2017 49 1 11.87 315440 10.56 7/31/2017 31 3 11.42 315446 6.17 8/3/2017 28 4 17.525 315447 9.08 8/10/2017 21 3 9.806666667 315448 7.99 7/29/2017 33 2 9.28 315449 18.94 8/30/2017 1 2 12.865 315453 13.26 8/21/2017 10 5 8.512 315461 7.18 7/26/2017 36 1 7.18 315466 19.75 8/30/2017 1 4 22.1525 315468 6.99 7/29/2017 33 6 10.36166667 315473 12.94 8/29/2017 2 5 13.476 315474 8.37 8/17/2017 14 3 9.466666667 315477 6.49 8/31/2017 0 1 6.49 315480 18.94 6/25/2017 67 1 18.94 315483 12.07 8/6/2017 25 6 12.48833333 315489 8.17 8/8/2017 23 3 13.06 315492 6.67 8/8/2017 23 1 6.67 315497 9.65 8/21/2017 10 1 9.65 315498 12.36 8/5/2017 26 2 10.265 315499 13.17 7/30/2017 32 1 13.17 315503 8.71 6/29/2017 63 5 12.854 315511 9.67 8/15/2017 16 5 9.992 315513 9.58 8/24/2017 7 2 9.125 315522 8.47 7/12/2017 50 1 8.47 315523 10.47 8/1/2017 30 2 8.63 315532 8.47 8/16/2017 15 5 11.362 315533 10.29 6/7/2017 85 1 10.29 315538 6.39 7/8/2017 54 2 16.51 315542 18.66 7/6/2017 56 1 18.66 315549 21.54 8/22/2017 9 6 20.71333333 315550 59.33 8/1/2017 30 5 19.566 315551 17.56 8/24/2017 7 5 12.908 315552 10.75 7/22/2017 40 3 8.796666667 315556 6.06 7/26/2017 36 2 7.66 315559 14.98 8/15/2017 16 4 21.93 315562 13.15 8/6/2017 25 8 9.9725 315563 9.47 8/30/2017 1 1 9.47 315567 18.77 8/28/2017 3 2 25.955 315575 10.86 8/22/2017 9 5 10.626 315579 7.38 7/31/2017 31 1 7.38 315581 8.78 8/17/2017 14 1 8.78 315582 6.99 8/19/2017 12 1 6.99 315591 22.86 8/11/2017 20 4 22.4925 315599 7.77 8/9/2017 22 1 7.77 315602 6.18 8/20/2017 11 4 6.18 315608 12.36 8/21/2017 10 1 12.36 315609 8.98 7/10/2017 52 2 11.21 315610 7.99 8/25/2017 6 6 14.73833333 315611 8.49 8/31/2017 0 3 8.323333333 315618 0 7/25/2017 37 4 17.85 315629 8.67 8/6/2017 25 4 8.17 315632 14.66 8/15/2017 16 2 10.475 315634 8.47 7/25/2017 37 2 8.82 315638 13.25 7/25/2017 37 2 13.055 315642 17.47 7/22/2017 40 2 12.13 315645 6.99 7/6/2017 56 1 6.99 315649 22.03 8/6/2017 25 1 22.03 315650 8.43 8/25/2017 6 2 9.15 315651 12.94 8/15/2017 16 5 14.666 315654 7.49 8/8/2017 23 2 9.98 315655 13.95 7/28/2017 34 2 11.21 315660 8.27 7/27/2017 35 1 8.27 315663 6.99 8/29/2017 2 5 6.664 315665 9.48 6/30/2017 62 2 8.885 315670 10.07 8/17/2017 14 2 8.47 315672 10.78 8/5/2017 26 1 10.78 315673 12.48 8/3/2017 28 2 17.265 315680 14.26 8/21/2017 10 4 14.13 315684 8.07 6/2/2017 90 1 8.07 315685 11.97 7/20/2017 42 3 10.64666667 315688 11.9 8/27/2017 4 3 10.49 315689 39.9 7/2/2017 60 1 39.9 315697 30.23 8/4/2017 27 3 18.56 315700 11.05 8/6/2017 25 4 10.335 315702 12.06 8/4/2017 27 2 10.765 315703 8.47 8/20/2017 11 2 9.915 315705 8.07 8/14/2017 17 3 8.043333333 315707 23.34 7/29/2017 33 1 23.34 315711 10.57 7/6/2017 56 4 11.3325 315712 22.36 8/7/2017 24 1 22.36 315717 8.88 7/22/2017 40 1 8.88 315723 10.47 8/21/2017 10 6 10.95166667 315725 6.79 8/22/2017 9 6 7.338333333 315726 10.97 6/23/2017 69 2 9.48 315730 12.01 8/30/2017 1 4 11.875 315731 28.73 8/15/2017 16 5 14.042 315740 7.28 8/9/2017 22 2 7.28 315754 8.18 6/11/2017 81 1 8.18 315755 9.24 8/27/2017 4 8 8.22375 315760 22 7/3/2017 59 1 22 315768 18.76 8/4/2017 27 2 19.405 315779 21.55 6/10/2017 82 1 21.55 315785 6.79 6/5/2017 87 1 6.79 315788 10.58 8/15/2017 16 3 10.05333333 315793 6.79 7/25/2017 37 4 9.23 315799 12.59 8/23/2017 8 3 10.35333333 315802 11.86 8/31/2017 0 3 17.02 315809 8.76 8/1/2017 30 2 8.76 315817 11.26 7/30/2017 32 2 9.765 315818 9.67 6/20/2017 72 1 9.67 315826 8.48 8/6/2017 25 4 8.8525 315845 11.07 8/5/2017 26 1 11.07 315853 8.47 7/29/2017 33 5 16.268 315854 27.93 7/9/2017 53 1 27.93 315855 12.76 7/5/2017 57 4 10.57 315856 10.78 7/28/2017 34 1 10.78 315860 17.46 8/24/2017 7 1 17.46 315861 8.49 8/8/2017 23 2 7.39 315873 32.84 7/30/2017 32 1 32.84 315875 20.75 6/12/2017 80 1 20.75 315883 19.64 6/13/2017 79 1 19.64 On 13 October 2017 at 10:35, PIKAL Petr <petr.pikal at precheza.cz<mailto:petr.pikal at precheza.cz>> wrote: Hi Your statement about attaching data is problematic. We cannot do much with it. Instead use output from dput(yourdata) to show us what exactly your data look like. We also do not know how do you want to split your data. It would be nice if you can show also what should be the bins with respective data. Unless you provide this information you probably would not get any sensible answer. Cheers Petr> -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org<mailto:r-help-bounces at r-project.org>] On Behalf Of Hemant Sain > Sent: Thursday, October 12, 2017 10:18 AM > To: r-help mailing list <r-help at r-project.org<mailto:r-help at r-project.org>> > Subject: [R] How to define proper breaks in RFM analysis > > Hello, > I'm working on RFM analysis and i wanted to define my own breaks but my > frequency distribution is not normally distributed so when I'm using quartile its > not giving the optimal results. > so I'm looking for a better approach where i can define breaks dynamically > because after visualization i can do it easily but i want to apply this model so > that it can automatically define the breaks according to data set. > I'm attaching sample data for reference. > > Thanks > > *Freq* > 5 > 15 > 1 > 8 > 2 > 2 > 2 > 1 > 1 > 2 > 2 > 1 > 1 > 1 > 1 > 4 > 10 > 22 > 24 > 1 > 1 > 2 > 2 > 7 > 1 > 1 > 4 > 6 > 1 > 1 > 2 > 2 > 17 > 2 > 7 > 1 > 5 > 2 > 7 > 7 > 1 > 4 > 13 > 4 > 1 > 9 > 1 > 1 > 1 > 3 > 2 > 1 > 1 > 2 > 4 > 5 > 8 > 4 > 14 > 18 > 4 > 1 > 1 > 1 > 7 > 1 > 1 > 1 > 1 > 10 > 6 > 4 > 6 > 1 > 3 > 13 > 2 > 4 > 8 > 11 > 2 > 4 > 6 > 1 > 1 > 3 > 1 > 2 > 3 > 2 > 2 > 5 > 2 > 1 > 1 > 1 > 3 > 2 > 3 > 1 > 2 > 9 > 34 > 8 > 1 > 1 > 1 > 1 > 2 > 1 > 5 > 4 > 9 > 1 > 1 > 4 > 2 > 2 > 1 > 1 > 2 > 25 > 5 > 2 > 1 > 1 > 1 > 6 > 1 > 36 > 3 > 4 > 5 > 3 > 3 > 13 > 2 > 1 > 4 > 1 > 1 > 9 > 7 > 1 > 1 > 15 > 1 > 1 > 2 > 5 > 7 > 3 > 3 > 1 > 8 > 7 > 5 > 1 > 1 > 5 > 14 > 3 > 2 > 2 > 1 > 5 > 3 > 4 > 3 > 1 > 2 > 9 > 2 > 15 > 2 > 1 > 3 > 56 > 3 > 2 > 4 > 2 > 26 > 3 > 1 > 4 > 1 > 1 > 12 > 1 > 18 > 7 > 6 > 7 > 2 > 3 > 2 > 1 > 4 > 15 > 10 > 7 > 5 > 3 > 6 > 4 > 9 > 1 > 2 > 2 > 2 > 3 > 1 > 1 > 8 > 3 > 1 > 2 > 3 > 1 > 10 > 3 > 1 > 3 > 5 > 1 > 8 > 3 > 2 > 3 > 7 > 1 > 5 > 2 > 1 > 1 > 6 > 2 > 1 > 9 > 1 > 20 > 2 > 1 > 4 > 21 > 5 > 4 > 4 > 1 > 1 > 1 > 11 > 7 > 4 > 6 > 1 > 3 > 3 > 12 > 4 > 7 > 4 > 3 > 3 > 1 > 2 > 10 > 5 > 11 > 3 > 2 > 1 > 3 > 30 > 1 > 4 > 5 > 1 > 7 > 3 > 1 > 3 > 9 > 2 > 2 > 14 > 10 > 1 > 1 > 1 > 1 > 5 > 1 > 1 > 18 > 32 > 1 > 4 > 5 > 4 > 3 > 2 > 9 > 2 > 6 > 3 > 2 > 2 > 2 > 2 > 2 > 2 > 4 > 4 > 3 > 1 > 1 > 2 > 4 > 6 > 1 > 1 > 1 > 2 > 2 > 1 > 1 > 3 > 1 > 1 > 3 > 1 > 2 > 3 > 2 > 9 > 4 > 1 > 2 > 4 > 3 > 3 > 3 > 1 > 2 > 1 > 3 > 4 > 3 > 1 > 3 > 1 > 5 > 14 > 7 > 1 > 1 > 1 > 1 > 4 > 3 > 4 > 5 > 8 > 1 > 10 > 3 > 2 > 7 > 5 > 4 > 5 > 7 > 4 > 4 > 10 > 3 > 7 > 12 > 1 > 1 > 3 > 1 > 6 > 1 > 5 > 9 > 2 > 1 > 3 > 4 > 3 > 2 > 2 > 5 > 1 > 4 > 6 > 5 > 3 > 1 > 1 > 6 > 3 > 1 > 1 > 2 > 1 > 5 > 5 > 2 > 1 > 2 > 5 > 1 > 2 > 1 > 6 > 5 > 5 > 3 > 2 > 4 > 8 > 1 > 2 > 5 > 1 > 1 > 1 > 4 > 1 > 4 > 1 > 2 > 6 > 3 > 4 > 4 > 2 > 2 > 2 > 2 > 1 > 1 > 2 > 5 > 2 > 2 > 1 > 5 > 2 > 2 > 1 > 2 > 4 > 1 > 3 > 3 > 1 > 3 > 4 > 2 > 2 > 3 > 1 > 4 > 1 > 1 > 6 > 6 > 2 > 4 > 5 > 2 > 1 > 8 > 1 > 2 > 1 > 1 > 3 > 4 > 3 > 3 > 2 > 2 > 1 > 4 > 1 > 5 > 1 > 4 > 1 > 1 > 2 > 1 > 1 > 1 > 8 > 1 > 1 > 1 > 1 > 1 > 3 > 3 > 5 > 2 > 3 > 1 > 1 > 5 > 2 > 3 > 6 > 3 > 3 > 14 > 2 > 1 > 1 > 2 > 1 > 2 > 4 > 2 > 1 > 6 > 1 > 7 > 2 > 3 > 3 > 2 > 2 > 2 > 2 > 1 > 2 > 4 > 1 > 6 > 2 > 5 > 2 > 1 > 2 > 2 > 5 > 8 > 4 > 1 > 1 > 1 > 1 > 4 > 1 > 3 > 2 > 1 > 2 > 2 > 3 > 3 > 3 > 6 > 1 > 1 > 1 > 5 > 7 > 1 > 5 > 2 > 1 > 1 > 1 > 3 > 20 > 2 > 3 > 3 > 1 > 2 > 1 > 15 > 4 > 4 > 1 > 1 > 2 > 1 > 1 > 3 > 2 > 6 > 5 > 1 > 5 > 1 > 7 > 4 > 3 > 2 > 5 > 2 > 1 > 1 > 3 > 2 > 6 > 2 > 4 > 2 > 1 > 24 > 4 > 17 > 1 > 3 > 2 > 2 > 2 > 2 > 8 > 1 > 3 > 1 > 9 > 2 > 4 > 1 > 1 > 6 > 3 > 4 > 1 > 9 > 2 > 1 > 3 > 2 > 6 > 2 > 1 > 3 > 1 > 20 > 3 > 4 > 7 > 3 > 7 > 1 > 7 > 1 > 5 > 2 > 1 > 1 > 1 > 2 > 1 > 2 > 4 > 1 > 1 > 2 > 3 > 4 > 1 > 4 > 1 > 1 > 1 > 1 > 1 > 2 > 1 > 6 > 2 > 3 > 2 > 1 > 9 > 8 > 11 > 1 > 1 > 2 > 1 > 3 > 1 > 2 > 15 > 5 > 2 > 2 > 9 > 1 > 4 > 2 > 1 > 1 > 14 > 1 > 1 > 2 > 1 > 3 > 10 > 1 > 1 > 3 > 1 > 1 > 1 > 4 > 2 > 8 > 1 > 2 > 2 > 1 > 11 > 1 > 3 > 1 > 7 > 1 > 3 > 10 > 3 > 3 > 1 > 1 > 1 > 11 > 1 > 2 > 1 > 1 > 2 > 2 > 5 > 5 > 4 > 1 > 2 > 5 > 2 > 4 > 3 > 1 > 1 > 2 > 2 > 4 > 2 > 1 > 1 > 4 > 1 > 4 > 1 > 5 > 1 > 1 > 2 > 1 > 4 > 7 > 1 > 2 > 1 > 2 > 9 > 3 > 1 > 7 > 2 > 2 > 1 > 2 > 3 > 5 > 2 > 7 > 1 > 5 > 1 > 1 > 2 > 2 > 2 > 4 > 2 > 8 > 4 > 6 > 1 > 1 > 1 > 1 > 1 > 16 > 2 > 1 > 6 > 4 > 4 > 1 > 1 > 1 > 1 > 4 > 3 > 2 > 6 > 11 > 10 > 21 > 2 > 1 > 1 > 3 > 2 > 2 > 2 > 7 > 1 > 6 > 4 > 1 > 7 > 4 > 11 > 1 > 2 > 8 > 1 > 1 > 1 > 1 > 2 > 17 > 1 > 2 > 3 > 4 > 2 > 1 > 2 > 2 > 4 > 3 > 2 > 3 > 1 > 3 > 3 > 1 > 3 > 37 > 4 > 3 > 1 > 2 > 1 > 1 > 3 > 1 > 2 > 3 > 1 > 5 > 1 > 2 > 1 > 3 > 2 > 3 > 3 > 4 > 4 > 2 > 4 > 1 > 1 > 3 > 3 > 2 > 1 > 2 > 1 > 1 > 3 > 1 > 1 > 3 > 3 > 4 > 2 > 4 > 1 > 1 > 1 > 10 > 3 > 2 > 2 > 2 > 2 > 2 > 2 > 1 > 19 > 2 > 2 > 4 > 1 > 3 > 1 > 13 > 5 > 2 > 1 > 2 > 2 > 4 > 2 > 1 > 3 > 5 > 1 > 1 > 1 > 6 > 3 > 9 > 4 > 1 > 1 > 1 > 3 > 1 > 17 > 4 > 1 > 4 > 6 > 2 > 1 > 2 > 4 > 4 > 2 > 2 > 2 > 4 > 4 > 1 > 1 > 1 > 2 > 7 > 2 > 1 > 2 > 8 > 1 > 1 > 7 > 4 > 1 > 2 > 1 > 1 > 3 > 1 > 3 > 1 > 1 > 3 > 5 > 8 > 1 > 1 > 4 > 1 > 1 > 15 > 1 > 1 > 6 > 2 > 3 > 3 > 8 > 4 > 1 > 4 > 2 > 4 > 2 > 5 > 4 > 4 > 1 > 1 > 7 > 1 > 10 > 1 > 10 > 2 > 15 > 7 > 3 > 1 > 3 > 2 > 19 > 2 > 9 > 1 > 10 > 2 > 1 > 2 > 2 > 4 > 6 > 1 > 4 > 3 > 1 > 2 > 3 > 2 > 1 > 3 > 7 > 1 > 4 > 2 > 13 > 2 > 5 > 3 > 6 > 2 > 1 > 2 > 1 > 5 > 1 > > > -- > hemantsain.com<http://hemantsain.com> > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org<mailto:R-help at r-project.org> mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.________________________________ Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou ur?eny pouze jeho adres?t?m. 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In case that this e-mail forms part of business dealings: - the sender reserves the right to end negotiations about entering into a contract in any time, for any reason, and without stating any reasoning. - if the e-mail contains an offer, the recipient is entitled to immediately accept such offer; The sender of this e-mail (offer) excludes any acceptance of the offer on the part of the recipient containing any amendment or variation. - the sender insists on that the respective contract is concluded only upon an express mutual agreement on all its aspects. - the sender of this e-mail informs that he/she is not authorized to enter into any contracts on behalf of the company except for cases in which he/she is expressly authorized to do so in writing, and such authorization or power of attorney is submitted to the recipient or the person represented by the recipient, or the existence of such authorization is known to the recipient of the person represented by the recipient. -- hemantsain.com<http://hemantsain.com> ________________________________ Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou ur?eny pouze jeho adres?t?m. 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If you received this e-mail by mistake, please immediately inform its sender. Delete the contents of this e-mail with all attachments and its copies from your system. If you are not the intended recipient of this e-mail, you are not authorized to use, disseminate, copy or disclose this e-mail in any manner. The sender of this e-mail shall not be liable for any possible damage caused by modifications of the e-mail or by delay with transfer of the email. 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> On Oct 13, 2017, at 2:51 AM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > > Hi > > You expect us to solve your problem but you ignore advice already recieved. > > Your data are unreadable, use dput(yourdata) instead. see ?dput > >> test<-read.table("clipboard", heade=T) > Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : > line 115 did not have 6 elementsI didn't have such a problem: (illustrated with a more minimal example) dat <- scan( what=list("",1,"",1L,1L,1), text="194849 6.99 8/22/2017 9 5 9.996 194978 14.78 8/28/2017 3 15 16.308 198614 18.44 7/31/2017 31 1 18.44 234569 34.99 8/20/2017 11 8 13.5075 252686 7.99 7/31/2017 31 2 7.99 291719 21.26 8/25/2017 6 2 15.67 291787 46.1 8/31/2017 0 2 32.57 292630 24.34 7/31/2017 31 1 24.34 295204 21.86 7/18/2017 44 1 21.86 295989 8.98 8/20/2017 11 2 14.095 298883 14.38 8/24/2017 7 2 11.185 308824 10.77 7/31/2017 31 1 10.77") names(dat) <- c("user_id", "subtotal_amount", "created_at", "Recency", "Frequency", "Monetary") dat <- data.frame(dat,stringsAsFactors=FALSE) I suspect read.table would also have worked for me, but I was expecting difficulties based on Petr's posting. #And ended up with this result (on the original copied data):> str(dat)'data.frame': 500 obs. of 6 variables: $ user_id : chr "194849" "194978" "198614" "234569" ... $ subtotal_amount: num 6.99 14.78 18.44 34.99 7.99 ... $ created_at : chr "8/22/2017" "8/28/2017" "7/31/2017" "8/20/2017" ... $ Recency : int 9 3 31 11 31 6 0 31 44 11 ... $ Frequency : int 5 15 1 8 2 2 2 1 1 2 ... $ Monetary : num 10 16.31 18.44 13.51 7.99 ... ... but the following criticism seems, well, _critical_ (as in essential for one to address if a reasonable proposal is to be offered.)> What is ?ideal interval? can you define it? Should it be such to provide eqal number of observations?That is the crucial question for you to answer, Hemant. Read the ?quartile help page if your answer is "yes" or even "maybe".> > Or maybe you could normalise your values and use quartile method.Well, maybe not so much on that last one, Petr. Normalization should not affect the classification based on quartiles. It doesn't change the ordering of variables. -- David.> > Cheers > Petr > > From: Hemant Sain [mailto:hemantsain55 at gmail.com] > Sent: Friday, October 13, 2017 8:51 AM > To: PIKAL Petr <petr.pikal at precheza.cz> > Cc: r-help mailing list <r-help at r-project.org> > Subject: Re: [R] How to define proper breaks in RFM analysis > > Hey, > i want to define 3 ideal breaks (bin) for each variable one of those variables is attached in the previous email, > i don't want to consider quartile method because quartile is not working ideally for that data set because data distribution is non normal. > so i want you to suggest another method so that i can define 3 breaks with the ideal interval for Recency, frequency and monetary to calculate RFM score. > i'm again attaching you some of the data set. > please look into it and help me with the R code. > Thanks > > > > Data > > user_id > > subtotal_amount > > created_at > > Recency > > Frequency > > Monetary > > 194849 > > 6.99 > > 8/22/2017 >snipped> > > On 13 October 2017 at 10:35, PIKAL Petr <petr.pikal at precheza.cz<mailto:petr.pikal at precheza.cz>> wrote: > Hi > > Your statement about attaching data is problematic. We cannot do much with it. Instead use output from dput(yourdata) to show us what exactly your data look like. > > We also do not know how do you want to split your data. It would be nice if you can show also what should be the bins with respective data. Unless you provide this information you probably would not get any sensible answer. > > Cheers > Petr > > >> -----Original Message----- >> From: R-help [mailto:r-help-bounces at r-project.org<mailto:r-help-bounces at r-project.org>] On Behalf Of Hemant Sain >> Sent: Thursday, October 12, 2017 10:18 AM >> To: r-help mailing list <r-help at r-project.org<mailto:r-help at r-project.org>> >> Subject: [R] How to define proper breaks in RFM analysis >> >> Hello, >> I'm working on RFM analysis and i wanted to define my own breaks but my >> frequency distribution is not normally distributed so when I'm using quartile its >> not giving the optimal results. >> so I'm looking for a better approach where i can define breaks dynamically >> because after visualization i can do it easily but i want to apply this model so >> that it can automatically define the breaks according to data set. >> I'm attaching sample data for reference. >> >> Thanks >> >> *Freq* >> 5 >> 15 >> 1snipped> . > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.David Winsemius Alameda, CA, USA 'Any technology distinguishable from magic is insufficiently advanced.' -Gehm's Corollary to Clarke's Third Law