R从日常数据中增加几个月

Question

我有大约20年的日常数据，我使用month（）函数提取了几个月。现在我希望这些月份在一年结束时不会改变到1（1月）。我希望他们继续前进13,14,15等等。 R中有函数吗？或者我该怎么做？

，比如我有这样的：

1993-01-04  1.953   1 
1993-01-05  1.978   1 
1993-01-06  2.007   1 
1993-01-07  1.957   1 
1993-01-08  1.955   1 
1993-01-11  1.982   1 
1993-01-12  1.958   1 
1993-01-13  1.924   1 
1993-01-14  1.887   1 
1993-01-15  1.971   1 
1993-01-19  2.098   1 
1993-01-20  2.087   1 
1993-01-21  2.062   1 
1993-01-22  2.056   1 
1993-01-25  2.051   1 
1993-01-26  2.038   1 
1993-01-27  1.990   1 
1993-01-28  2.032   1 
1993-01-29  2.027   1 
1993-02-01  2.083   2 
1993-02-02  2.027   2 
1993-02-03  2.009   2 
1993-02-04  2.058   2 
1993-02-05  2.073   2 
1993-02-08  2.071   2 
1993-02-09  2.022   2 
1993-02-10  2.077   2 
1993-02-11  2.116   2 
1993-02-12  2.049   2 
1993-02-15  2.086   2 
1993-02-16  2.072   2 
1993-02-17  2.061   2 
1993-02-18  2.109   2 
1993-02-19  2.082   2 
1993-02-23  2.027   2 
1993-02-24  1.962   2 
1993-02-25  1.966   2 
1993-02-26  2.001   2 
1993-03-01  2.027   3 
1993-03-02  2.013   3 
1993-03-03  1.989   3 
1993-03-04  1.982   3 
1993-03-05  1.949   3 
1993-03-08  1.966   3 
1993-03-09  1.987   3 
1993-03-10  1.989   3 
1993-03-11  2.009   3 
1993-03-12  1.978   3 
1993-03-15  1.970   3 
1993-03-16  2.009   3 
1993-03-17  1.938   3 
1993-03-18  1.930   3 
1993-03-19  1.914   3 
1993-03-22  1.892   3 
1993-03-23  1.902   3 
1993-03-24  1.910   3 
1993-03-25  1.897   3 
1993-03-26  1.853   3 
1993-03-29  1.879   3 
1993-03-30  1.920   3 
1993-03-31  1.906   3 
1993-04-01  1.894   4 
1993-04-02  1.901   4 
1993-04-05  1.888   4 
1993-04-07  1.905   4 
1993-04-08  1.938   4 
1993-04-13  1.935   4 
1993-04-14  1.945   4 
1993-04-15  1.926   4 
1993-04-16  1.895   4 
1993-04-19  1.885   4 
1993-04-20  1.859   4 
1993-04-21  1.858   4 
1993-04-22  1.890   4 
1993-04-23  1.848   4 
1993-04-26  1.861   4 
1993-04-27  1.837   4 
1993-04-28  1.818   4 
1993-04-29  1.812   4 
1993-04-30  1.835   4 
1993-05-03  1.893   5 
1993-05-04  1.847   5 
1993-05-05  1.841   5 
1993-05-06  1.875   5 
1993-05-07  1.885   5 
1993-05-10  1.893   5 
1993-05-11  1.891   5 
1993-05-12  1.851   5 
1993-05-13  1.889   5 
1993-05-14  1.859   5 
1993-05-17  1.827   5 
1993-05-18  1.827   5 
1993-05-19  1.803   5 
1993-05-21  1.823   5 
1993-05-24  1.812   5 
1993-05-25  1.842   5 
1993-05-26  1.783   5 
1993-05-27  1.797   5 
1993-05-28  1.784   5 
1993-06-01  1.777   6 
1993-06-02  1.774   6 
1993-06-03  1.784   6 
1993-06-04  1.804   6 
1993-06-07  1.858   6 
1993-06-08  1.868   6 
1993-06-09  1.852   6 
1993-06-11  1.888   6 
1993-06-14  1.980   6 
1993-06-15  1.972   6 
1993-06-16  1.972   6 
1993-06-17  2.018   6 
1993-06-18  2.018   6 
1993-06-21  2.075   6 
1993-06-22  2.111   6 
1993-06-23  2.140   6 
1993-06-24  2.175   6 
1993-06-25  2.174   6 
1993-06-28  2.192   6 
1993-06-29  2.175   6 
1993-06-30  2.145   6 
1993-07-01  2.104   7 
1993-07-02  2.069   7 
1993-07-05  2.076   7 
1993-07-06  2.102   7 
1993-07-07  2.174   7 
1993-07-08  2.372   7 
1993-07-09  2.402   7 
1993-07-12  2.392   7 
1993-07-13  2.378   7 
1993-07-14  2.379   7 
1993-07-15  2.381   7 
1993-07-16  2.358   7 
1993-07-19  2.413   7 
1993-07-20  2.403   7 
1993-07-21  2.373   7 
1993-07-22  2.423   7 
1993-07-23  2.393   7 
1993-07-26  2.423   7 
1993-07-27  2.382   7 
1993-07-28  2.354   7 
1993-07-29  2.314   7 
1993-07-30  2.240   7 
1993-08-02  2.272   8 
1993-08-03  2.256   8 
1993-08-04  2.282   8 
1993-08-05  2.262   8 
1993-08-06  2.288   8 
1993-08-09  2.296   8 
1993-08-10  2.264   8 
1993-08-11  2.296   8 
1993-08-12  2.333   8 
1993-08-13  2.353   8 
1993-08-16  2.373   8 
1993-08-17  2.408   8 
1993-08-18  2.398   8 
1993-08-19  2.382   8 
1993-08-20  2.368   8 
1993-08-23  2.332   8 
1993-08-24  2.362   8 
1993-08-25  2.358   8 
1993-08-26  2.286   8 
1993-08-27  2.286   8 
1993-08-30  2.313   8 
1993-08-31  2.359   8 
1993-09-01  2.293   9 
1993-09-02  2.313   9 
1993-09-03  2.283   9 
1993-09-06  2.253   9 
1993-09-07  2.237   9 
1993-09-08  2.255   9 
1993-09-09  2.279   9 
1993-09-10  2.258   9 
1993-09-13  2.253   9 
1993-09-14  2.238   9 
1993-09-15  2.238   9 
1993-09-16  2.223   9 
1993-09-17  2.258   9 
1993-09-20  2.266   9 
1993-09-21  2.243   9 
1993-09-22  2.252   9 
1993-09-23  2.303   9 
1993-09-24  2.260   9 
1993-09-27  2.317   9 
1993-09-28  2.283   9 
1993-09-29  2.298   9 
1993-09-30  2.313   9 
1993-10-01  2.315  10 
1993-10-04  2.307  10 
1993-10-05  2.398  10 
1993-10-06  2.508  10 
1993-10-07  2.386  10 

Answer 1

尝试是这样的：

test = c(seq(1,12,by=1),seq(1,12,by=1)) 
[1] 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 
data.table::rleid(test) 
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 

这可能是一个更完整的答案。

library(data.table) 
dt = data.table("Date" = seq.Date(as.Date("2014-12-21"),as.Date("2015-01-01"),by = 1), value = runif(12)) 
dt[, "Month" := month(Date)] 
dt[, "ID" := rleid(Month)] 

Answer 2

我们可以base R（假定日期排序）

df1$index <- cumsum(c(TRUE, diff(df1$Month) < 0))