HI Eliza,
May be this helps:
set.seed(42)
el <- matrix(sample(1:20,327*365,replace=TRUE),ncol=327)
colnames(el) <- as.character(interaction(df1,sep="*"))
el1 <- el[,colnames(el) %in%
as.character(interaction(df2,sep="*"))]
dim(el1)
#[1] 365 5
A.K.
On Tuesday, March 25, 2014 4:15 PM, eliza botto <eliza_botto@hotmail.com>
wrote:
[text format is also attached]
Dear Arun,
I need one more favor.This is regading to "df1". What if I have a
matrix "el" of 327 columns with 365rows each. I want to name them
with respect to df1. For suppose for first column the name should
be for first column the name should be 67.75*24.25(the first and
second column and first row of df1), similarly the name of vector
2 should be 68.25*24.25 and so on till 327th column of matrix.
Now there is another matrix, df2 with 2 columns and 5 row. I only
want to select those columns whose header are similar to what
written in df2. For example the first row of df2 is 67.75 and
24.25, so I want to select that column from df1 which has a name
of 67.75*24.25 and so on till I have a matrix with 5 columns and
365 rows with columns names as they were in df1.
Thankyou very much in advance
You can suppose "el" by yourself.
dput(df1)<-
structure(list(longitude = c(67.75, 68.25, 69.75, 67.25, 67.75,
68.25, 68.75, 69.25, 69.75, 70.25, 70.75, 61.75, 62.25, 62.75,
63.25, 66.75, 67.25, 67.75, 68.25, 68.75, 69.25, 69.75, 70.25,
70.75, 62.25, 62.75, 63.25, 63.75, 64.25, 64.75, 65.25, 65.75,
66.25, 66.75, 67.25, 67.75, 68.25, 68.75, 69.25, 69.75, 70.25,
62.25, 62.75, 63.25, 63.75, 64.25, 64.75, 65.25, 65.75, 66.25,
66.75, 67.25, 67.75, 68.25, 68.75, 69.25, 69.75, 63.25, 63.75,
64.25, 64.75, 65.25, 65.75, 66.25, 66.75, 67.25, 67.75, 68.25,
68.75, 69.25, 63.25, 63.75, 64.25, 64.75, 65.25, 65.75, 66.25,
66.75, 67.25, 67.75, 68.25, 68.75, 69.25, 69.75, 63.25, 63.75,
64.25, 64.75, 65.25, 65.75, 66.25, 66.75, 67.25, 67.75, 68.25,
68.75, 69.25, 69.75, 62.75, 63.25, 63.75, 64.25, 64.75, 65.25,
65.75, 66.25, 66.75, 67.25, 67.75, 68.25, 68.75, 69.25, 69.75,
70.25, 70.75, 71.25, 71.75, 62.25, 62.75, 63.25, 63.75, 64.25,
64.75, 65.25, 65.75, 66.25, 66.75, 67.25, 67.75, 68.25, 68.75,
69.25, 69.75, 70.25, 70.75, 71.25, 71.75, 72.25, 61.75, 62.25,
62.75, 63.25, 63.75, 64.25, 64.75, 65.25, 65.75, 66.25, 66.75,
67.25, 67.75, 68.25, 68.75, 69.25, 69.75, 70.25, 70.75, 71.25,
71.75, 72.25, 72.75, 61.25, 65.75, 66.25, 66.75, 67.25, 67.75,
68.25, 68.75, 69.25, 69.75, 70.25, 70.75, 71.25, 71.75, 72.25,
72.75, 73.25, 66.75, 67.25, 67.75, 68.25, 68.75, 69.25, 69.75,
70.25, 70.75, 71.25, 71.75, 72.25, 72.75, 73.25, 73.75, 66.75,
67.25, 67.75, 68.25, 68.75, 69.25, 69.75, 70.25, 70.75, 71.25,
71.75, 72.25, 72.75, 73.25, 73.75, 74.25, 67.75, 68.25, 68.75,
69.25, 69.75, 70.25, 70.75, 71.25, 71.75, 72.25, 72.75, 73.25,
73.75, 74.25, 68.25, 69.25, 69.75, 70.25, 70.75, 71.25, 71.75,
72.25, 72.75, 73.25, 73.75, 74.25, 69.75, 70.25, 70.75, 71.25,
71.75, 72.25, 72.75, 73.25, 73.75, 74.25, 74.75, 75.25, 69.75,
70.25, 70.75, 71.25, 71.75, 72.25, 72.75, 73.25, 73.75, 74.25,
70.25, 70.75, 71.25, 71.75, 72.25, 72.75, 73.25, 73.75, 70.25,
70.75, 71.25, 71.75, 72.25, 72.75, 73.25, 73.75, 71.25, 71.75,
72.25, 72.75, 73.25, 73.75, 71.75, 72.25, 72.75, 73.25, 73.75,
74.25, 74.75, 75.25, 75.75, 76.25, 76.75, 71.75, 72.25, 72.75,
73.25, 73.75, 74.25, 74.75, 75.25, 75.75, 76.25, 76.75, 77.25,
71.75, 72.25, 72.75, 73.25, 73.75, 74.25, 74.75, 75.25, 75.75,
76.25, 76.75, 71.75, 72.25, 72.75, 73.25, 73.75, 74.25, 74.75,
75.25, 75.75, 73.25, 73.75, 74.25, 74.75, 75.25), latitude = c
(24.25,
24.25, 24.25, 24.75, 24.75, 24.75, 24.75, 24.75, 24.75, 24.75,
24.75, 25.25, 25.25, 25.25, 25.25, 25.25, 25.25, 25.25, 25.25,
25.25, 25.25, 25.25, 25.25, 25.25, 25.75, 25.75, 25.75, 25.75,
25.75, 25.75, 25.75, 25.75, 25.75, 25.75, 25.75, 25.75, 25.75,
25.75, 25.75, 25.75, 25.75, 26.25, 26.25, 26.25, 26.25, 26.25,
26.25, 26.25, 26.25, 26.25, 26.25, 26.25, 26.25, 26.25, 26.25,
26.25, 26.25, 26.75, 26.75, 26.75, 26.75, 26.75, 26.75, 26.75,
26.75, 26.75, 26.75, 26.75, 26.75, 26.75, 27.25, 27.25, 27.25,
27.25, 27.25, 27.25, 27.25, 27.25, 27.25, 27.25, 27.25, 27.25,
27.25, 27.25, 27.75, 27.75, 27.75, 27.75, 27.75, 27.75, 27.75,
27.75, 27.75, 27.75, 27.75, 27.75, 27.75, 27.75, 28.25, 28.25,
28.25, 28.25, 28.25, 28.25, 28.25, 28.25, 28.25, 28.25, 28.25,
28.25, 28.25, 28.25, 28.25, 28.25, 28.25, 28.25, 28.25, 28.75,
28.75, 28.75, 28.75, 28.75, 28.75, 28.75, 28.75, 28.75, 28.75,
28.75, 28.75, 28.75, 28.75, 28.75, 28.75, 28.75, 28.75, 28.75,
28.75, 28.75, 29.25, 29.25, 29.25, 29.25, 29.25, 29.25, 29.25,
29.25, 29.25, 29.25, 29.25, 29.25, 29.25, 29.25, 29.25, 29.25,
29.25, 29.25, 29.25, 29.25, 29.25, 29.25, 29.25, 29.75, 29.75,
29.75, 29.75, 29.75, 29.75, 29.75, 29.75, 29.75, 29.75, 29.75,
29.75, 29.75, 29.75, 29.75, 29.75, 29.75, 30.25, 30.25, 30.25,
30.25, 30.25, 30.25, 30.25, 30.25, 30.25, 30.25, 30.25, 30.25,
30.25, 30.25, 30.25, 30.75, 30.75, 30.75, 30.75, 30.75, 30.75,
30.75, 30.75, 30.75, 30.75, 30.75, 30.75, 30.75, 30.75, 30.75,
30.75, 31.25, 31.25, 31.25, 31.25, 31.25, 31.25, 31.25, 31.25,
31.25, 31.25, 31.25, 31.25, 31.25, 31.25, 31.75, 31.75, 31.75,
31.75, 31.75, 31.75, 31.75, 31.75, 31.75, 31.75, 31.75, 31.75,
32.25, 32.25, 32.25, 32.25, 32.25, 32.25, 32.25, 32.25, 32.25,
32.25, 32.25, 32.25, 32.75, 32.75, 32.75, 32.75, 32.75, 32.75,
32.75, 32.75, 32.75, 32.75, 33.25, 33.25, 33.25, 33.25, 33.25,
33.25, 33.25, 33.25, 33.75, 33.75, 33.75, 33.75, 33.75, 33.75,
33.75, 33.75, 34.25, 34.25, 34.25, 34.25, 34.25, 34.25, 34.75,
34.75, 34.75, 34.75, 34.75, 34.75, 34.75, 34.75, 34.75, 34.75,
34.75, 35.25, 35.25, 35.25, 35.25, 35.25, 35.25, 35.25, 35.25,
35.25, 35.25, 35.25, 35.25, 35.75, 35.75, 35.75, 35.75, 35.75,
35.75, 35.75, 35.75, 35.75, 35.75, 35.75, 36.25, 36.25, 36.25,
36.25, 36.25, 36.25, 36.25, 36.25, 36.25, 36.75, 36.75, 36.75,
36.75, 36.75)), .Names = c("longitude", "latitude"), class
=
"data.frame", row.names = c(54L,
55L, 58L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 118L, 119L,
120L, 121L, 128L, 129L, 130L, 131L, 132L, 133L, 134L, 135L, 136L,
157L, 158L, 159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L, 167L,
168L, 169L, 170L, 171L, 172L, 173L, 195L, 196L, 197L, 198L, 199L,
200L, 201L, 202L, 203L, 204L, 205L, 206L, 207L, 208L, 209L, 210L,
235L, 236L, 237L, 238L, 239L, 240L, 241L, 242L, 243L, 244L, 245L,
246L, 247L, 273L, 274L, 275L, 276L, 277L, 278L, 279L, 280L, 281L,
282L, 283L, 284L, 285L, 286L, 311L, 312L, 313L, 314L, 315L, 316L,
317L, 318L, 319L, 320L, 321L, 322L, 323L, 324L, 348L, 349L, 350L,
351L, 352L, 353L, 354L, 355L, 356L, 357L, 358L, 359L, 360L, 361L,
362L, 363L, 364L, 365L, 366L, 385L, 386L, 387L, 388L, 389L, 390L,
391L, 392L, 393L, 394L, 395L, 396L, 397L, 398L, 399L, 400L, 401L,
402L, 403L, 404L, 405L, 422L, 423L, 424L, 425L, 426L, 427L, 428L,
429L, 430L, 431L, 432L, 433L, 434L, 435L, 436L, 437L, 438L, 439L,
440L, 441L, 442L, 443L, 444L, 459L, 468L, 469L, 470L, 471L, 472L,
473L, 474L, 475L, 476L, 477L, 478L, 479L, 480L, 481L, 482L, 483L,
508L, 509L, 510L, 511L, 512L, 513L, 514L, 515L, 516L, 517L, 518L,
519L, 520L, 521L, 522L, 546L, 547L, 548L, 549L, 550L, 551L, 552L,
553L, 554L, 555L, 556L, 557L, 558L, 559L, 560L, 561L, 586L, 587L,
588L, 589L, 590L, 591L, 592L, 593L, 594L, 595L, 596L, 597L, 598L,
599L, 625L, 627L, 628L, 629L, 630L, 631L, 632L, 633L, 634L, 635L,
636L, 637L, 666L, 667L, 668L, 669L, 670L, 671L, 672L, 673L, 674L,
675L, 676L, 677L, 704L, 705L, 706L, 707L, 708L, 709L, 710L, 711L,
712L, 713L, 743L, 744L, 745L, 746L, 747L, 748L, 749L, 750L, 781L,
782L, 783L, 784L, 785L, 786L, 787L, 788L, 821L, 822L, 823L, 824L,
825L, 826L, 860L, 861L, 862L, 863L, 864L, 865L, 866L, 867L, 868L,
869L, 870L, 898L, 899L, 900L, 901L, 902L, 903L, 904L, 905L, 906L,
907L, 908L, 909L, 936L, 937L, 938L, 939L, 940L, 941L, 942L, 943L,
944L, 945L, 946L, 974L, 975L, 976L, 977L, 978L, 979L, 980L, 981L,
982L, 1015L, 1016L, 1017L, 1018L, 1019L))
dput(df2)<-structure(list(longitude = c(67.75, 68.25, 69.75,
67.25, 67.75
), latitude = c(24.25, 24.25, 24.25, 24.75, 24.75)), .Names = c
("longitude",
"latitude"), row.names = c(54L, 55L, 58L, 91L, 92L), class =
"data.frame")