问题
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")
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.
I was able to plot the histogram:
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 = "")
What I want:
[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.
I'll appreciate any help.
回答1:
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)
With one consecutive extreme value
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
With two consecutive extreme value
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
来源：https://stackoverflow.com/questions/62442715/how-to-extract-dates-after-using-rle-function-in-r