Hi All, I need to parse data from a file, example shown below. The first two lines can be skipped, the third line contains the column names. The next 13 lines can be skipped. The next line "1991" is a year value, with the following 13 values data for that year. The file then repeats this format with (year, 13 lines of data for that year). I would ideally like to end up with an array/list/vector of the block of 13 values, indexed by year, each block using the column names given on the third line. If anyone has any good ideas on how to do this in R, pls. let me know. Thanks, Sean --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 725280 BUFFALO NIAGARA INTL A NY -5 N42 56 W078 44 215 988 1991-2005 MO AVGLO FL SDGLO AVDIR FL SDDIR AVDIF FL SDDIF AVETR AETRN TOT OPQ H2O TAU MAX_T MIN_T AVG_T AVGDT RH HTDD CLDD AVWS 1 1336 K5 222 1534 K7 676 837 K5 72 3806 13256 8.4 8.1 0.83 0.09 -0.52 -7.40 -3.86 -3.36 75 691 0 5.5 2 2261 K5 400 2691 K7 1026 1129 K5 74 5330 14714 7.6 7.1 0.79 0.10 0.97 -6.67 -2.76 -1.85 73 599 0 5.1 3 3249 K5 413 3207 K7 852 1578 K5 118 7428 16443 7.2 6.7 0.98 0.12 4.96 -3.21 0.93 2.04 71 541 0 4.9 4 4460 K5 570 4051 K6 1045 1951 K5 130 9509 18140 6.6 6.1 1.33 0.13 12.18 2.68 7.39 8.54 67 328 1 4.7 5 5484 K5 518 4529 K6 801 2408 K5 142 10999 19523 6.1 5.4 1.87 0.15 18.77 8.68 13.83 15.07 69 154 12 4.5 6 6046 K5 383 5011 K6 671 2567 K5 166 11616 20177 5.7 4.9 2.64 0.16 24.05 14.52 19.47 20.66 71 34 63 4.1 7 5793 K5 529 4734 K6 884 2537 K5 127 11250 19734 5.6 4.9 2.97 0.16 26.10 16.92 21.70 22.90 71 5 104 4.1 8 5057 K5 417 4390 K6 693 2245 K5 94 9974 18430 5.6 4.9 2.92 0.15 25.61 16.37 21.10 22.56 73 9 91 3.6 9 4001 K5 458 3864 K6 826 1797 K5 105 8078 16803 5.6 5.0 2.36 0.13 21.73 12.20 17.06 18.68 73 71 30 3.9 10 2502 K5 254 2564 K7 584 1306 K5 88 5948 15098 6.3 5.8 1.67 0.11 14.89 6.40 10.71 12.16 72 241 3 4.3 11 1395 K5 198 1394 K7 492 887 K5 47 4170 13545 7.9 7.5 1.30 0.10 8.37 1.42 4.91 5.82 73 403 0 5.0 12 1120 K5 173 1391 K7 475 701 K5 52 3351 12733 7.9 7.7 0.94 0.09 2.41 -3.92 -0.70 -0.03 75 592 0 5.0 13 3559 K5 201 3280 K7 383 1662 K5 50 7622 16550 6.7 6.2 1.72 0.12 13.29 4.83 9.15 10.27 72 3668 304 4.5 1991 1 1313 I5 637 1374 I6 1636 832 I5 169 3800 13249 8.2 7.8 0.75 0.07 -0.09 -6.67 -3.46 -2.94 73 673 0 5.9 2 1875 I5 887 1767 I6 2080 1137 I5 263 5310 14694 8.3 7.6 0.85 0.08 2.44 -3.84 -0.61 0.15 73 533 0 5.9 3 3205 I5 1520 3371 I6 3133 1458 I5 392 7395 16417 6.7 6.1 1.12 0.10 7.23 -1.17 2.75 3.75 70 474 0 5.3 4 3999 I5 1911 3451 I6 3501 1918 I5 521 9482 18116 6.9 5.9 1.60 0.12 14.46 5.65 9.91 11.04 68 250 2 5.4 5 5968 I5 1854 5369 I6 2936 2296 I5 437 10983 19506 6.1 4.5 2.46 0.14 23.15 12.56 17.85 19.12 68 81 66 4.8 6 6988 I5 1577 6761 I6 2983 2288 I5 604 11614 20176 4.8 3.0 2.42 0.15 26.09 14.95 20.80 22.28 64 14 80 4.3 7 6364 I5 1538 5779 I6 2799 2404 I5 568 11262 19749 5.0 3.7 2.89 0.16 27.17 16.96 22.43 23.77 66 1 116 4.4 8 5407 I5 1478 5114 I6 2693 2106 I5 527 9999 18451 4.8 4.0 2.91 0.18 26.64 16.49 21.44 23.08 73 2 102 4.2 9 4482 I5 1010 4126 I6 1953 2033 I5 415 8109 16830 5.8 4.6 2.24 0.19 22.05 10.98 16.67 18.53 66 97 42 4.3 10 2534 I5 864 2419 I6 1859 1396 I5 289 5978 15123 6.1 5.3 1.83 0.20 16.44 6.92 11.72 13.21 72 213 7 4.4 11 1264 I5 716 1059 I6 1733 851 I5 206 4190 13565 8.3 8.0 1.33 0.21 7.63 0.44 3.94 4.82 77 429 0 5.1 12 976 I5 423 826 I6 1172 714 I5 156 3354 12738 7.6 7.2 0.98 0.22 3.40 -4.20 -0.34 0.21 78 581 0 5.6 13 3698 I5 2146 3451 I6 2002 1619 I5 629 7623 16551 6.6 5.6 1.78 0.15 14.72 5.76 10.26 11.42 71 3347 415 5.0 1992 1 1149 I5 496 701 I6 919 896 I5 231 3791 13236 8.5 8.1 0.84 0.24 0.68 -6.20 -2.60 -1.69 79 654 0 5.4 2 1580 I5 708 898 I6 1469 1198 I5 255 5328 14708 8.2 7.7 0.86 0.27 1.26 -6.19 -2.40 -1.56 78 603 0 4.7 3 2968 I5 1429 2145 I6 2037 1760 I5 452 7449 16457 7.3 6.7 0.97 0.29 3.82 -4.35 -0.11 1.01 70 577 0 4.8 4 4050 I5 1812 2937 I6 2634 2146 I5 404 9527 18154 7.3 6.4 1.41 0.29 10.64 2.33 6.40 7.50 71 356 1 4.1 5 5654 I5 1935 4311 I6 2843 2695 I5 557 11009 19528 5.4 4.3 1.74 0.29 19.79 8.17 14.13 15.66 66 148 13 3.8 6 6170 I5 2120 4608 I6 3029 2877 I5 695 11617 20176 5.3 4.1 2.17 0.28 22.76 11.91 17.63 19.06 65 56 26 4.0 7 4879 I5 1816 2795 I6 1915 2835 I5 595 11242 19729 7.2 6.3 2.99 0.27 23.05 15.33 19.23 20.19 75 18 44 4.4 8 5168 I5 1720 4473 I6 2922 2256 I5 444 9959 18415 5.8 4.9 2.64 0.24 23.28 14.62 19.05 20.37 72 26 46 4.4 9 4094 I5 1361 3741 I6 2382 1893 I5 375 8058 16789 5.8 4.5 2.50 0.21 21.25 11.59 16.56 18.13 72 84 27 4.5 10 2499 I5 1177 2228 I6 1904 1393 I5 311 5928 15081 6.1 5.6 1.45 0.18 13.37 4.21 8.81 10.50 70 296 0 4.7 11 1134 I5 680 731 I6 1287 849 I5 249 4156 13533 8.5 8.1 1.39 0.15 7.58 1.22 4.38 5.30 77 418 0 4.8 12 1048 I5 508 1136 I6 1428 687 I5 146 3348 12729 7.8 7.3 0.96 0.14 3.30 -3.43 -0.06 0.83 69 570 0 5.1 13 3366 I5 1883 2559 I6 1489 1790 I5 790 7618 16545 6.9 6.1 1.66 0.24 12.56 4.10 8.42 9.61 72 3806 157 4.6 ... [[alternative HTML version deleted]]
Sean
I'm sure there are many ways of doing this. I assume you have read the
data in R as a data.frame with 24 columns and 2+1+13+(1+13)*n rows,
where n is the number of years, and that you want a data.frame with 25
columns (one extra for year) and 13*n rows (although I am not sure why
13 MOnths) and the columns named appropriately.
#First create your new data.frame
newDF <- as.data.frame(matrix(NA, (nrow(oldDF)-15)/14, 25,
dimnames=list(NULL, c('year', oldDF[3,]))))
#Now fill the year column (column 1)
newDF[,1] <- rep(oldDf[seq(16, nrow(oldDF), 14),1], each=13)
#And finally deal with the data
newDF[,-1] <- oldDF[-(1:15),][c(F, rep(T,13)),]
The above is untested and not guaranteed to work, but hopefully is
enough to get you going. If not, you could get back to me privately.
Peter Alspach
> -----Original Message-----
> From: r-help-bounces at r-project.org
> [mailto:r-help-bounces at r-project.org] On Behalf Of sean
> Sent: Friday, 7 March 2008 8:06 a.m.
> To: r-help at r-project.org
> Subject: [R] Help with parsing a data file
>
> Hi All,
>
> I need to parse data from a file, example shown below. The
> first two lines can be skipped, the third line contains the
> column names. The next 13 lines can be skipped. The next
> line "1991" is a year value, with the following 13 values
> data for that year. The file then repeats this format with
> (year, 13 lines of data for that year). I would ideally like
> to end up with an array/list/vector of the block of 13
> values, indexed by year, each block using the column names
> given on the third line.
>
> If anyone has any good ideas on how to do this in R, pls. let me know.
>
> Thanks,
> Sean
>
> --------------------------------------------------------------
> --------------------------------------------------------------
> -----------------------------------------------------------
> 725280 BUFFALO NIAGARA INTL A NY -5 N42 56 W078 44 215 988
> 1991-2005
> MO AVGLO FL SDGLO AVDIR FL SDDIR AVDIF FL SDDIF AVETR AETRN TOT OPQ
> H2O TAU MAX_T MIN_T AVG_T AVGDT RH HTDD CLDD AVWS
> 1 1336 K5 222 1534 K7 676 837 K5 72 3806 13256
> 8.4 8.1 0.83
> 0.09 -0.52 -7.40 -3.86 -3.36 75 691 0 5.5
> 2 2261 K5 400 2691 K7 1026 1129 K5 74 5330 14714
> 7.6 7.1 0.79
> 0.10 0.97 -6.67 -2.76 -1.85 73 599 0 5.1
> 3 3249 K5 413 3207 K7 852 1578 K5 118 7428 16443
> 7.2 6.7 0.98
> 0.12 4.96 -3.21 0.93 2.04 71 541 0 4.9
> 4 4460 K5 570 4051 K6 1045 1951 K5 130 9509 18140
> 6.6 6.1 1.33
> 0.13 12.18 2.68 7.39 8.54 67 328 1 4.7
> 5 5484 K5 518 4529 K6 801 2408 K5 142 10999 19523
> 6.1 5.4 1.87
> 0.15 18.77 8.68 13.83 15.07 69 154 12 4.5
> 6 6046 K5 383 5011 K6 671 2567 K5 166 11616 20177
> 5.7 4.9 2.64
> 0.16 24.05 14.52 19.47 20.66 71 34 63 4.1
> 7 5793 K5 529 4734 K6 884 2537 K5 127 11250 19734
> 5.6 4.9 2.97
> 0.16 26.10 16.92 21.70 22.90 71 5 104 4.1
> 8 5057 K5 417 4390 K6 693 2245 K5 94 9974 18430
> 5.6 4.9 2.92
> 0.15 25.61 16.37 21.10 22.56 73 9 91 3.6
> 9 4001 K5 458 3864 K6 826 1797 K5 105 8078 16803
> 5.6 5.0 2.36
> 0.13 21.73 12.20 17.06 18.68 73 71 30 3.9
> 10 2502 K5 254 2564 K7 584 1306 K5 88 5948 15098
> 6.3 5.8 1.67
> 0.11 14.89 6.40 10.71 12.16 72 241 3 4.3
> 11 1395 K5 198 1394 K7 492 887 K5 47 4170 13545
> 7.9 7.5 1.30
> 0.10 8.37 1.42 4.91 5.82 73 403 0 5.0
> 12 1120 K5 173 1391 K7 475 701 K5 52 3351 12733
> 7.9 7.7 0.94
> 0.09 2.41 -3.92 -0.70 -0.03 75 592 0 5.0
> 13 3559 K5 201 3280 K7 383 1662 K5 50 7622 16550
> 6.7 6.2 1.72
> 0.12 13.29 4.83 9.15 10.27 72 3668 304 4.5
> 1991
> 1 1313 I5 637 1374 I6 1636 832 I5 169 3800 13249
> 8.2 7.8 0.75
> 0.07 -0.09 -6.67 -3.46 -2.94 73 673 0 5.9
> 2 1875 I5 887 1767 I6 2080 1137 I5 263 5310 14694
> 8.3 7.6 0.85
> 0.08 2.44 -3.84 -0.61 0.15 73 533 0 5.9
> 3 3205 I5 1520 3371 I6 3133 1458 I5 392 7395 16417
> 6.7 6.1 1.12
> 0.10 7.23 -1.17 2.75 3.75 70 474 0 5.3
> 4 3999 I5 1911 3451 I6 3501 1918 I5 521 9482 18116
> 6.9 5.9 1.60
> 0.12 14.46 5.65 9.91 11.04 68 250 2 5.4
> 5 5968 I5 1854 5369 I6 2936 2296 I5 437 10983 19506
> 6.1 4.5 2.46
> 0.14 23.15 12.56 17.85 19.12 68 81 66 4.8
> 6 6988 I5 1577 6761 I6 2983 2288 I5 604 11614 20176
> 4.8 3.0 2.42
> 0.15 26.09 14.95 20.80 22.28 64 14 80 4.3
> 7 6364 I5 1538 5779 I6 2799 2404 I5 568 11262 19749
> 5.0 3.7 2.89
> 0.16 27.17 16.96 22.43 23.77 66 1 116 4.4
> 8 5407 I5 1478 5114 I6 2693 2106 I5 527 9999 18451
> 4.8 4.0 2.91
> 0.18 26.64 16.49 21.44 23.08 73 2 102 4.2
> 9 4482 I5 1010 4126 I6 1953 2033 I5 415 8109 16830
> 5.8 4.6 2.24
> 0.19 22.05 10.98 16.67 18.53 66 97 42 4.3
> 10 2534 I5 864 2419 I6 1859 1396 I5 289 5978 15123
> 6.1 5.3 1.83
> 0.20 16.44 6.92 11.72 13.21 72 213 7 4.4
> 11 1264 I5 716 1059 I6 1733 851 I5 206 4190 13565
> 8.3 8.0 1.33
> 0.21 7.63 0.44 3.94 4.82 77 429 0 5.1
> 12 976 I5 423 826 I6 1172 714 I5 156 3354 12738
> 7.6 7.2 0.98
> 0.22 3.40 -4.20 -0.34 0.21 78 581 0 5.6
> 13 3698 I5 2146 3451 I6 2002 1619 I5 629 7623 16551
> 6.6 5.6 1.78
> 0.15 14.72 5.76 10.26 11.42 71 3347 415 5.0
> 1992
> 1 1149 I5 496 701 I6 919 896 I5 231 3791 13236
> 8.5 8.1 0.84
> 0.24 0.68 -6.20 -2.60 -1.69 79 654 0 5.4
> 2 1580 I5 708 898 I6 1469 1198 I5 255 5328 14708
> 8.2 7.7 0.86
> 0.27 1.26 -6.19 -2.40 -1.56 78 603 0 4.7
> 3 2968 I5 1429 2145 I6 2037 1760 I5 452 7449 16457
> 7.3 6.7 0.97
> 0.29 3.82 -4.35 -0.11 1.01 70 577 0 4.8
> 4 4050 I5 1812 2937 I6 2634 2146 I5 404 9527 18154
> 7.3 6.4 1.41
> 0.29 10.64 2.33 6.40 7.50 71 356 1 4.1
> 5 5654 I5 1935 4311 I6 2843 2695 I5 557 11009 19528
> 5.4 4.3 1.74
> 0.29 19.79 8.17 14.13 15.66 66 148 13 3.8
> 6 6170 I5 2120 4608 I6 3029 2877 I5 695 11617 20176
> 5.3 4.1 2.17
> 0.28 22.76 11.91 17.63 19.06 65 56 26 4.0
> 7 4879 I5 1816 2795 I6 1915 2835 I5 595 11242 19729
> 7.2 6.3 2.99
> 0.27 23.05 15.33 19.23 20.19 75 18 44 4.4
> 8 5168 I5 1720 4473 I6 2922 2256 I5 444 9959 18415
> 5.8 4.9 2.64
> 0.24 23.28 14.62 19.05 20.37 72 26 46 4.4
> 9 4094 I5 1361 3741 I6 2382 1893 I5 375 8058 16789
> 5.8 4.5 2.50
> 0.21 21.25 11.59 16.56 18.13 72 84 27 4.5
> 10 2499 I5 1177 2228 I6 1904 1393 I5 311 5928 15081
> 6.1 5.6 1.45
> 0.18 13.37 4.21 8.81 10.50 70 296 0 4.7
> 11 1134 I5 680 731 I6 1287 849 I5 249 4156 13533
> 8.5 8.1 1.39
> 0.15 7.58 1.22 4.38 5.30 77 418 0 4.8
> 12 1048 I5 508 1136 I6 1428 687 I5 146 3348 12729
> 7.8 7.3 0.96
> 0.14 3.30 -3.43 -0.06 0.83 69 570 0 5.1
> 13 3366 I5 1883 2559 I6 1489 1790 I5 790 7618 16545
> 6.9 6.1 1.66
> 0.24 12.56 4.10 8.42 9.61 72 3806 157 4.6
> ...
>
> [[alternative HTML version deleted]]
>
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Try this:
lines <- readLines('yourfile')
newLines <- lines[-(1:(13+3))]
coln <- scan(textConnection(lines[3]), what="")
lapply(which(nchar(newLines) == 4),
function(x)read.table(textConnection(newLines[seq(x + 1, x + 13)]),
col.names=coln))
On 06/03/2008, sean <smachin1000 at gmail.com>
wrote:> Hi All,
>
> I need to parse data from a file, example shown below. The first two
lines
> can be skipped, the third line contains the column names. The next 13
lines
> can be skipped. The next line "1991" is a year value, with the
following 13
> values data for that year. The file then repeats this format with (year,
13
> lines of data for that year). I would ideally like to end up with an
> array/list/vector of the block of 13 values, indexed by year, each block
> using the column names given on the third line.
>
> If anyone has any good ideas on how to do this in R, pls. let me know.
>
> Thanks,
> Sean
>
>
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
> 725280 BUFFALO NIAGARA INTL A NY -5 N42 56 W078 44 215 988
> 1991-2005
> MO AVGLO FL SDGLO AVDIR FL SDDIR AVDIF FL SDDIF AVETR AETRN TOT OPQ
> H2O TAU MAX_T MIN_T AVG_T AVGDT RH HTDD CLDD AVWS
> 1 1336 K5 222 1534 K7 676 837 K5 72 3806 13256 8.4 8.1
0.83
> 0.09 -0.52 -7.40 -3.86 -3.36 75 691 0 5.5
> 2 2261 K5 400 2691 K7 1026 1129 K5 74 5330 14714 7.6 7.1
0.79
> 0.10 0.97 -6.67 -2.76 -1.85 73 599 0 5.1
> 3 3249 K5 413 3207 K7 852 1578 K5 118 7428 16443 7.2 6.7
0.98
> 0.12 4.96 -3.21 0.93 2.04 71 541 0 4.9
> 4 4460 K5 570 4051 K6 1045 1951 K5 130 9509 18140 6.6 6.1
1.33
> 0.13 12.18 2.68 7.39 8.54 67 328 1 4.7
> 5 5484 K5 518 4529 K6 801 2408 K5 142 10999 19523 6.1 5.4
1.87
> 0.15 18.77 8.68 13.83 15.07 69 154 12 4.5
> 6 6046 K5 383 5011 K6 671 2567 K5 166 11616 20177 5.7 4.9
2.64
> 0.16 24.05 14.52 19.47 20.66 71 34 63 4.1
> 7 5793 K5 529 4734 K6 884 2537 K5 127 11250 19734 5.6 4.9
2.97
> 0.16 26.10 16.92 21.70 22.90 71 5 104 4.1
> 8 5057 K5 417 4390 K6 693 2245 K5 94 9974 18430 5.6 4.9
2.92
> 0.15 25.61 16.37 21.10 22.56 73 9 91 3.6
> 9 4001 K5 458 3864 K6 826 1797 K5 105 8078 16803 5.6 5.0
2.36
> 0.13 21.73 12.20 17.06 18.68 73 71 30 3.9
> 10 2502 K5 254 2564 K7 584 1306 K5 88 5948 15098 6.3 5.8
1.67
> 0.11 14.89 6.40 10.71 12.16 72 241 3 4.3
> 11 1395 K5 198 1394 K7 492 887 K5 47 4170 13545 7.9 7.5
1.30
> 0.10 8.37 1.42 4.91 5.82 73 403 0 5.0
> 12 1120 K5 173 1391 K7 475 701 K5 52 3351 12733 7.9 7.7
0.94
> 0.09 2.41 -3.92 -0.70 -0.03 75 592 0 5.0
> 13 3559 K5 201 3280 K7 383 1662 K5 50 7622 16550 6.7 6.2
1.72
> 0.12 13.29 4.83 9.15 10.27 72 3668 304 4.5
> 1991
> 1 1313 I5 637 1374 I6 1636 832 I5 169 3800 13249 8.2 7.8
0.75
> 0.07 -0.09 -6.67 -3.46 -2.94 73 673 0 5.9
> 2 1875 I5 887 1767 I6 2080 1137 I5 263 5310 14694 8.3 7.6
0.85
> 0.08 2.44 -3.84 -0.61 0.15 73 533 0 5.9
> 3 3205 I5 1520 3371 I6 3133 1458 I5 392 7395 16417 6.7 6.1
1.12
> 0.10 7.23 -1.17 2.75 3.75 70 474 0 5.3
> 4 3999 I5 1911 3451 I6 3501 1918 I5 521 9482 18116 6.9 5.9
1.60
> 0.12 14.46 5.65 9.91 11.04 68 250 2 5.4
> 5 5968 I5 1854 5369 I6 2936 2296 I5 437 10983 19506 6.1 4.5
2.46
> 0.14 23.15 12.56 17.85 19.12 68 81 66 4.8
> 6 6988 I5 1577 6761 I6 2983 2288 I5 604 11614 20176 4.8 3.0
2.42
> 0.15 26.09 14.95 20.80 22.28 64 14 80 4.3
> 7 6364 I5 1538 5779 I6 2799 2404 I5 568 11262 19749 5.0 3.7
2.89
> 0.16 27.17 16.96 22.43 23.77 66 1 116 4.4
> 8 5407 I5 1478 5114 I6 2693 2106 I5 527 9999 18451 4.8 4.0
2.91
> 0.18 26.64 16.49 21.44 23.08 73 2 102 4.2
> 9 4482 I5 1010 4126 I6 1953 2033 I5 415 8109 16830 5.8 4.6
2.24
> 0.19 22.05 10.98 16.67 18.53 66 97 42 4.3
> 10 2534 I5 864 2419 I6 1859 1396 I5 289 5978 15123 6.1 5.3
1.83
> 0.20 16.44 6.92 11.72 13.21 72 213 7 4.4
> 11 1264 I5 716 1059 I6 1733 851 I5 206 4190 13565 8.3 8.0
1.33
> 0.21 7.63 0.44 3.94 4.82 77 429 0 5.1
> 12 976 I5 423 826 I6 1172 714 I5 156 3354 12738 7.6 7.2
0.98
> 0.22 3.40 -4.20 -0.34 0.21 78 581 0 5.6
> 13 3698 I5 2146 3451 I6 2002 1619 I5 629 7623 16551 6.6 5.6
1.78
> 0.15 14.72 5.76 10.26 11.42 71 3347 415 5.0
> 1992
> 1 1149 I5 496 701 I6 919 896 I5 231 3791 13236 8.5 8.1
0.84
> 0.24 0.68 -6.20 -2.60 -1.69 79 654 0 5.4
> 2 1580 I5 708 898 I6 1469 1198 I5 255 5328 14708 8.2 7.7
0.86
> 0.27 1.26 -6.19 -2.40 -1.56 78 603 0 4.7
> 3 2968 I5 1429 2145 I6 2037 1760 I5 452 7449 16457 7.3 6.7
0.97
> 0.29 3.82 -4.35 -0.11 1.01 70 577 0 4.8
> 4 4050 I5 1812 2937 I6 2634 2146 I5 404 9527 18154 7.3 6.4
1.41
> 0.29 10.64 2.33 6.40 7.50 71 356 1 4.1
> 5 5654 I5 1935 4311 I6 2843 2695 I5 557 11009 19528 5.4 4.3
1.74
> 0.29 19.79 8.17 14.13 15.66 66 148 13 3.8
> 6 6170 I5 2120 4608 I6 3029 2877 I5 695 11617 20176 5.3 4.1
2.17
> 0.28 22.76 11.91 17.63 19.06 65 56 26 4.0
> 7 4879 I5 1816 2795 I6 1915 2835 I5 595 11242 19729 7.2 6.3
2.99
> 0.27 23.05 15.33 19.23 20.19 75 18 44 4.4
> 8 5168 I5 1720 4473 I6 2922 2256 I5 444 9959 18415 5.8 4.9
2.64
> 0.24 23.28 14.62 19.05 20.37 72 26 46 4.4
> 9 4094 I5 1361 3741 I6 2382 1893 I5 375 8058 16789 5.8 4.5
2.50
> 0.21 21.25 11.59 16.56 18.13 72 84 27 4.5
> 10 2499 I5 1177 2228 I6 1904 1393 I5 311 5928 15081 6.1 5.6
1.45
> 0.18 13.37 4.21 8.81 10.50 70 296 0 4.7
> 11 1134 I5 680 731 I6 1287 849 I5 249 4156 13533 8.5 8.1
1.39
> 0.15 7.58 1.22 4.38 5.30 77 418 0 4.8
> 12 1048 I5 508 1136 I6 1428 687 I5 146 3348 12729 7.8 7.3
0.96
> 0.14 3.30 -3.43 -0.06 0.83 69 570 0 5.1
> 13 3366 I5 1883 2559 I6 1489 1790 I5 790 7618 16545 6.9 6.1
1.66
> 0.24 12.56 4.10 8.42 9.61 72 3806 157 4.6
> ...
>
> [[alternative HTML version deleted]]
>
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--
Henrique Dallazuanna
Curitiba-Paran?-Brasil
25? 25' 40" S 49? 16' 22" O