在R中使用rle()函数后如何提取日期 [英] How to extract dates after using rle() function in R
本文介绍了在R中使用rle()函数后如何提取日期的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我有以下数据文件.这是四列(YY，MM，DD，RR)的每日降雨数据.抱歉，这是我可以生成的最小数据.
I have the following data file. This is a daily data of rainfall with four columns (YY,MM,DD,RR). Apologies, this is the smallest data that I can generate.
dat<-structure(list(YY = c(1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L), MM = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L), DD = c(1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L,
13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L,
31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L,
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L,
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
29L, 30L, 31L), RR = c(65.3, 2.6, 3.8, 93.5, 0, 0, 1, 0, 0, 0,
20.6, 3.4, 0, 0, 0, 0, 0, 0, 29.2, 6.6, 0.5, 1, 18.5, 3.3, 0,
2, 2.8, 0, 0, 12.8, 15.8, 0, 1.6, 0.3, 25, 3.6, 0, 19.6, 1.8,
0, 0, 0, 0, 25.9, 0, 6.6, 15.7, 1.3, 30, 0, 0, 0, 0.5, 17, 14.7,
6.1, 0.5, 67.6, 133.8, 114.6, 0, 0, 0, 25.1, 1.8, 1.4, 0, 0,
0, 0, 0, 2, 55.7, 36.9, 65, 3.1, 0, 0, 0, 0, 0, 0, 0, 41.4, 13.2,
29.8, 1, 170.7, 115, 72.9, 25.9, 18, 15.7, 1.3, 4, 0, 0, 0, 8.9,
0, 1, 0, 0, 6.1, 9.4, 21.6, 11, 13.1, 2.3, 0, 11.3, 4.9, 0.8,
0, 0.3, 0, 0, 0, 0.3, 6.4, 0, 0, 2.3, 6.9, 21.4, 57.7, 0.3, 35.5,
2.3, 0, 8.1, 0, 0, 108.2, 7.1, 8.2, 9.4, 14.2, 42.7, 0, 0, 1.3,
0, 45.2, 203.2, 14.5, 9.2, 22.2, 2.9, 0, 59.5, 19.9, 162.9, 0,
1, 0, 0, 0, 1.8, 9.9, 54, 8.1, 9.4, 0, 0.8, 0, 0, 0, 0, 0.3,
0, 0, 7.4, 28.5, 101.2, 87.9, 26.9, 128.9, 78.1, 3.6, 0, 0, 77.5,
130.1, 262.5, 105.5, 14.9, 0, 0, 0, 2.5, 2.3, 15.5, 28.8, 4.6,
34.8, 22.1, 60.5, 0.5, 24.1, 0, 0, 37, 128.3, 26, 27.8, 2.3,
2.3, 195.9, 227.7, 0.8, 2.8, 0, 0, 5.1, 0.3, 0, 0, 0, 0, 9.7,
125.9, 64.9, 78.3, 3.3, 0, 0, 46.2, 52.6, 3, 24.9, 22.1, 14.2,
0, 0, 170.6, 64.5, 30.3, 35.8, 204.5, 5.3, 0.5, 3.1, 0, 0, 17.2,
136.6, 37.9, 0.8, 0, 0.3, 5.1, 2.4, 0, 9.8, 0, 0, 0, 0.2, 0,
0.3, 0, 0.3, 1.5, 1, 0, 0, 0, 0, 0, 0.8, 1.3, 7.8, 0, 12, 25.2,
74.3, 26.5, 1.6, 11.2, 0, 0, 0, 0, 5.4, 186.1, 99.7, 46.3, 2.8,
7.6, 5.6, 22.9, 81, 2, 0, 7.1, 24, 68, 121.8, 10.4, 0, 24.4,
77.1, 18, 8.9, 0.8, 0, 18.6, 0, 2, 1.3, 0, 18.8, 0, 0, 8.6, 5.6,
0, 0.5, 61.8, 146.6, 16.5, 0, 18.6, 0, 0, 0, 8.1, 59.4, 8.5,
1, 54.8, 0, 21.6, 0, 0, 0, 0, 0, 0, 0, 44.2, 0.5, 0, 1.3, 0,
1.8, 1, 0, 9.7, 93.5, 48.5, 158.3, 78.5, 2.8, 4.1, 13, 98.8,
55.2, 76.3, 56.3, 0, 6.1, 0, 0, 0, 0, 5.3, 0, 14.5, 0, 0)), row.names =
c(274L,
275L, 276L, 277L, 278L, 279L, 280L, 281L, 282L, 283L, 284L, 285L,
286L, 287L, 288L, 289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L,
297L, 298L, 299L, 300L, 301L, 302L, 303L, 304L, 640L, 641L, 642L,
643L, 644L, 645L, 646L, 647L, 648L, 649L, 650L, 651L, 652L, 653L,
654L, 655L, 656L, 657L, 658L, 659L, 660L, 661L, 662L, 663L, 664L,
665L, 666L, 667L, 668L, 669L, 670L, 1005L, 1006L, 1007L, 1008L,
1009L, 1010L, 1011L, 1012L, 1013L, 1014L, 1015L, 1016L, 1017L,
1018L, 1019L, 1020L, 1021L, 1022L, 1023L, 1024L, 1025L, 1026L,
1027L, 1028L, 1029L, 1030L, 1031L, 1032L, 1033L, 1034L, 1035L,
1370L, 1371L, 1372L, 1373L, 1374L, 1375L, 1376L, 1377L, 1378L,
1379L, 1380L, 1381L, 1382L, 1383L, 1384L, 1385L, 1386L, 1387L,
1388L, 1389L, 1390L, 1391L, 1392L, 1393L, 1394L, 1395L, 1396L,
1397L, 1398L, 1399L, 1400L, 1735L, 1736L, 1737L, 1738L, 1739L,
1740L, 1741L, 1742L, 1743L, 1744L, 1745L, 1746L, 1747L, 1748L,
1749L, 1750L, 1751L, 1752L, 1753L, 1754L, 1755L, 1756L, 1757L,
1758L, 1759L, 1760L, 1761L, 1762L, 1763L, 1764L, 1765L, 2101L,
2102L, 2103L, 2104L, 2105L, 2106L, 2107L, 2108L, 2109L, 2110L,
2111L, 2112L, 2113L, 2114L, 2115L, 2116L, 2117L, 2118L, 2119L,
2120L, 2121L, 2122L, 2123L, 2124L, 2125L, 2126L, 2127L, 2128L,
2129L, 2130L, 2131L, 2466L, 2467L, 2468L, 2469L, 2470L, 2471L,
2472L, 2473L, 2474L, 2475L, 2476L, 2477L, 2478L, 2479L, 2480L,
2481L, 2482L, 2483L, 2484L, 2485L, 2486L, 2487L, 2488L, 2489L,
2490L, 2491L, 2492L, 2493L, 2494L, 2495L, 2496L, 2831L, 2832L,
2833L, 2834L, 2835L, 2836L, 2837L, 2838L, 2839L, 2840L, 2841L,
2842L, 2843L, 2844L, 2845L, 2846L, 2847L, 2848L, 2849L, 2850L,
2851L, 2852L, 2853L, 2854L, 2855L, 2856L, 2857L, 2858L, 2859L,
2860L, 2861L, 3196L, 3197L, 3198L, 3199L, 3200L, 3201L, 3202L,
3203L, 3204L, 3205L, 3206L, 3207L, 3208L, 3209L, 3210L, 3211L,
3212L, 3213L, 3214L, 3215L, 3216L, 3217L, 3218L, 3219L, 3220L,
3221L, 3222L, 3223L, 3224L, 3225L, 3226L, 3562L, 3563L, 3564L,
3565L, 3566L, 3567L, 3568L, 3569L, 3570L, 3571L, 3572L, 3573L,
3574L, 3575L, 3576L, 3577L, 3578L, 3579L, 3580L, 3581L, 3582L,
3583L, 3584L, 3585L, 3586L, 3587L, 3588L, 3589L, 3590L, 3591L,
3592L, 3927L, 3928L, 3929L, 3930L, 3931L, 3932L, 3933L, 3934L,
3935L, 3936L, 3937L, 3938L, 3939L, 3940L, 3941L, 3942L, 3943L,
3944L, 3945L, 3946L, 3947L, 3948L, 3949L, 3950L, 3951L, 3952L,
3953L, 3954L, 3955L, 3956L, 3957L, 4292L, 4293L, 4294L, 4295L,
4296L, 4297L, 4298L, 4299L, 4300L, 4301L, 4302L, 4303L, 4304L,
4305L, 4306L, 4307L, 4308L, 4309L, 4310L, 4311L, 4312L, 4313L,
4314L, 4315L, 4316L, 4317L, 4318L, 4319L, 4320L, 4321L, 4322L
), class = "data.frame")
我正在计算有多少事件具有仅1天的持续时间，2天连续的持续时间，3天连续的持续时间.然后绘制它的直方图.
I am counting how many events have 1 day only duration, 2 day consecutive duration, 3 day consecutive duration. Then plot the histogram of this.
我能够绘制直方图:
library(dplyr)
dat2 <- dat %>%
group_by(YY,MM) %>%
mutate(extreme = RR > quantile(RR,0.95,na.rm=TRUE))
result <- rle(dat2$extreme)
hist(result$lengths[result$values],breaks = c(0:5), xlab = "Length of extreme events", main = "")
我想要什么:
[1]我想为每个长度(连续1或2天，等等)提取日期(并将日期保存到单独的文件中).我不确定在应用rle()函数后如何过滤日期.我将把它应用于具有不同长度的多个文件.
[1] I want to extract the dates (and save the dates into separate files) for each length (1 or 2 consecutive days, etc). I am not sure how to filter the dates after applying the rle() function. I will be applying this to multiple files with different lengths.
我将不胜感激.
推荐答案
您可以使用 data.table 中的 rleid 来查找连续出现的日期，这些日期是极端，计算它们的出现次数，然后将数据分成数据帧列表.
You can use rleid from data.table to find consecutive occurrence of dates which are extreme, count their occurences and split the data into list of dataframes.
library(dplyr)
data <- dat %>%
group_by(YY,MM) %>%
mutate(extreme = RR > quantile(RR,0.95,na.rm=TRUE),
grp = data.table::rleid(extreme)) %>%
filter(extreme) %>%
add_count(grp) %>%
ungroup %>%
select(-extreme, -grp) %>%
group_split(n)
具有一个连续的 extreme 值
data[[1]]
# A tibble: 12 x 5
# YY MM DD RR n
# <int> <int> <int> <dbl> <int>
# 1 1979 10 1 65.3 1
# 2 1979 10 4 93.5 1
# 3 1982 10 13 21.6 1
# 4 1982 10 15 13.1 1
# 5 1983 10 21 203. 1
# 6 1983 10 29 163. 1
# 7 1986 10 19 171. 1
# 8 1986 10 23 204. 1
# 9 1988 10 7 186. 1
#10 1988 10 20 122. 1
#11 1990 10 12 158. 1
#12 1990 10 17 98.8 1
具有两个连续的 extreme 值
data[[2]]
# A tibble: 12 x 5
# YY MM DD RR n
# <int> <int> <int> <dbl> <int>
# 1 1980 10 28 134. 2
# 2 1980 10 29 115. 2
# 3 1981 10 26 171. 2
# 4 1981 10 27 115 2
# 5 1984 10 29 130. 2
# 6 1984 10 30 262. 2
# 7 1985 10 23 196. 2
# 8 1985 10 24 228. 2
# 9 1987 10 29 74.3 2
#10 1987 10 30 26.5 2
#11 1989 10 10 61.8 2
#12 1989 10 11 147. 2
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