How to read 3D data in R

General
1

Hello, I am just starting to use R and I wonder if there is a nice way to read a "3D data file (x,y,Elevation)
where x latitude, y is the logitude and z is the elevation. This file I am using is a sample dataset use just for learning purpose.

This file could be in CSV or XLSX format.

The first row show the x values
the first column show the y value
in between we have the z value ex:

x - > 1 2 3
y
1 11.5 12.6 12.7
2 10.0 10.6 11.0
3 9.0 9.2 10.0

so the file in csv format look like that

,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23
0,27.80985,49.61936,83.08067,116.6632,130.414,150.7206,220.1871,156.1536,148.6416,203.7845,206.0386,107.1618,68.36975,45.3359,49.96142,21.89279,17.02552,11.74317,14.75226,13.6671,5.677561,3.31234,1.156517,-0.147662
1,27.71966,48.55022,65.21374,95.27666,116.9964,133.9056,152.3412,151.934,160.1139,179.5327,147.6184,170.3943,121.8194,52.58537,33.08871,38.40972,44.24843,69.5786,4.019351,3.050024,3.039719,2.996142,2.967954,1.999594
2,30.4267,33.47752,44.80953,62.47495,77.43523,104.2153,102.7393,137.0004,186.0706,219.3173,181.7615,120.9154,143.1835,82.40501,48.47132,74.71461,60.0909,7.073525,6.089851,6.53745,6.666096,7.306965,5.73684,3.625628
3,16.66549,30.1086,39.96952,44.12225,59.57512,77.56929,106.8925,166.5539,175.2381,185.2815,154.5056,83.0433,62.61732,62.33167,60.55916,55.92124,15.17284,8.248324,36.68087,61.93413,20.26867,68.58819,46.49812,0.2360095
4,8.815617,18.3516,8.658275,27.5859,48.62691,60.18013,91.3286,145.7109,116.0653,106.2662,68.69447,53.10596,37.92797,47.95942,47.42691,69.20731,44.95468,29.17197,17.91674,16.25515,14.65559,17.26048,31.22245,46.71704
5,6.628881,10.41339,24.81939,26.08952,30.1605,52.30802,64.71007,76.30823,84.63686,99.4324,62.52132,46.81647,55.76606,82.4099,140.2647,81.26501,56.45756,30.42164,17.28782,8.302431,2.981626,2.698536,5.886086,5.268358
6,21.83975,6.63927,18.97085,32.89204,43.15014,62.86014,104.6657,130.2294,114.8494,106.9873,61.89647,55.55682,86.80986,89.27802,122.4221,123.9698,109.0952,98.41956,77.61374,32.49031,14.67344,7.370775,0.03711011,0.6423392
7,53.34303,26.79797,6.63927,10.88787,17.2044,56.18116,79.70141,90.8453,98.27675,80.87243,74.7931,75.54661,73.4373,74.11694,68.1749,46.24076,39.93857,31.21653,36.88335,40.02525,117.4297,12.70328,1.729771,0
8,25.66785,63.05717,22.1414,17.074,41.74483,60.27227,81.42432,114.444,102.3234,101.7878,111.031,119.2309,114.0777,110.5296,59.19355,42.47175,14.63598,6.944074,6.944075,27.74936,0,0,0.09449376,0.07732264
9,12.827,69.20554,46.76293,13.96517,33.88744,61.82613,84.74799,121.122,145.2741,153.1797,204.786,227.9242,236.3038,228.3655,79.34425,25.93483,6.944074,6.944074,6.944075,7.553681,0,0,0,0
10,0,68.66396,59.0435,33.35762,47.45282,57.8355,78.91689,107.8275,168.0053,130.9597,212.5541,165.8122,210.2429,181.1713,189.7617,137.3378,84.65395,8.677168,6.956576,8.468093,0,0,0,0
11,0,95.17499,80.03818,59.89862,39.58476,50.28058,63.81641,80.61302,66.37824,198.7651,244.3467,294.2474,264.3517,176.4082,60.21857,77.41475,53.16981,56.16393,6.949235,7.531059,3.780177,0,0,0
12,0,134.9879,130.3696,96.86325,75.70494,58.86466,57.20374,55.18837,78.128,108.5582,154.3774,319.1686,372.8826,275.4655,130.2632,54.93822,25.49719,8.047439,8.084393,5.115252,5.678269,0,0,0
13,0,48.08919,142.5558,140.3777,154.7261,87.9361,58.11092,52.83869,67.14822,83.66798,118.9242,150.0681,272.9709,341.1366,238.664,190.2,116.8943,91.48672,14.0157,42.29277,5.115252,0,0,0
14,0,54.1941,146.3839,99.48143,96.19411,102.9473,76.14089,57.7844,47.0402,64.36799,84.23767,162.7181,121.3275,213.1646,328.482,285.4489,283.8319,212.815,164.549,92.29631,7.244015,1.167,0,0
15,0,6.919659,195.1709,132.5253,135.2341,89.85069,89.45549,60.29967,50.33806,39.17583,59.06854,74.52159,84.93402,187.1219,123.9673,103.7027,128.986,165.1283,249.7054,95.39966,10.00284,2.39255,0,0
16,0,21.73871,123.1339,176.7414,158.2698,137.235,105.3089,86.63255,53.11591,29.03865,30.40539,39.04902,49.23405,63.27853,111.4215,101.1956,40.00962,59.84565,74.51253,17.06316,2.435141,2.287471,-0.000363698,0
17,0,0,62.04672,136.3122,201.7952,168.1343,95.2046,58.90624,46.94091,49.27053,37.10416,17.97011,30.93697,33.39257,44.03077,55.64542,78.22423,14.42782,9.954997,7.768213,13.0254,21.73166,2.156372,0.5317867
18,0,0,79.62993,139.6978,173.167,192.8718,196.3499,144.6611,106.5424,57.16653,41.16107,32.12764,13.8566,10.91772,12.07177,22.38254,24.72105,6.803666,4.200841,16.46857,15.70744,33.96221,7.575688,-0.04880907
19,0,0,33.2664,57.53643,167.2241,196.4833,194.7966,182.1884,119.6961,73.02113,48.36549,33.74652,26.2379,16.3578,6.811293,6.63927,6.639271,8.468093,6.194273,3.591233,3.81486,8.600739,5.21889,0
20,0,0,29.77937,54.97282,144.7995,207.4904,165.3432,171.4047,174.9216,100.2733,61.46441,50.19171,26.08209,17.18218,8.468093,6.63927,6.334467,6.334467,5.666687,4.272203,0,0,0,0
21,0,0,31.409,132.7418,185.5796,121.8299,185.3841,160.6566,116.1478,118.1078,141.7946,65.56351,48.84066,23.13864,18.12932,10.28531,6.029663,6.044627,5.694764,3.739085,3.896037,0,0,0
22,0,0,19.58994,42.30355,96.26777,187.1207,179.6626,221.3898,154.2617,142.1604,148.5737,67.17937,40.69044,39.74512,26.10166,14.48469,8.65873,3.896037,3.571392,3.896037,3.896037,3.896037,1.077756,0
23,0.001229679,3.008948,5.909858,33.50574,104.3341,152.2165,198.1988,191.841,228.7349,168.1041,144.2759,110.7436,57.65214,42.63504,27.91891,15.41052,8.056102,3.90283,3.879774,3.936718,3.968634,0.1236256,3.985531,-0.1835741
24,0,5.626141,7.676256,63.16226,45.99762,79.56688,227.311,203.9287,172.5618,177.1462,140.4554,123.9905,110.346,65.12319,34.31887,24.5278,9.561069,3.334991,5.590495,5.487353,5.909499,5.868994,5.833817,3.568177

So, my question is: is there a nice way to read a flat file structure like a 3D dataset?
Thanks in advance for your help

Regards,
alepage

2

For a lot of uses it is most convenient to have the data in "long" format with a column for y values, one for x values and then the numeric values. There may be more elegant ways, but I would do it like this.

library(tidyr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
df <- read.csv("c:/users/fjcc/Documents/R/Play/3D.txt", header = FALSE)
head(df)
#>   V1        V2       V3        V4        V5        V6        V7       V8
#> 1 NA  0.000000  1.00000  2.000000   3.00000   4.00000   5.00000   6.0000
#> 2  0 27.809850 49.61936 83.080670 116.66320 130.41400 150.72060 220.1871
#> 3  1 27.719660 48.55022 65.213740  95.27666 116.99640 133.90560 152.3412
#> 4  2 30.426700 33.47752 44.809530  62.47495  77.43523 104.21530 102.7393
#> 5  3 16.665490 30.10860 39.969520  44.12225  59.57512  77.56929 106.8925
#> 6  4  8.815617 18.35160  8.658275  27.58590  48.62691  60.18013  91.3286
#>         V9      V10      V11       V12       V13       V14      V15
#> 1   7.0000   8.0000   9.0000  10.00000  11.00000  12.00000 13.00000
#> 2 156.1536 148.6416 203.7845 206.03860 107.16180  68.36975 45.33590
#> 3 151.9340 160.1139 179.5327 147.61840 170.39430 121.81940 52.58537
#> 4 137.0004 186.0706 219.3173 181.76150 120.91540 143.18350 82.40501
#> 5 166.5539 175.2381 185.2815 154.50560  83.04330  62.61732 62.33167
#> 6 145.7109 116.0653 106.2662  68.69447  53.10596  37.92797 47.95942
#>        V16      V17      V18       V19       V20       V21       V22
#> 1 14.00000 15.00000 16.00000 17.000000 18.000000 19.000000 20.000000
#> 2 49.96142 21.89279 17.02552 11.743170 14.752260 13.667100  5.677561
#> 3 33.08871 38.40972 44.24843 69.578600  4.019351  3.050024  3.039719
#> 4 48.47132 74.71461 60.09090  7.073525  6.089851  6.537450  6.666096
#> 5 60.55916 55.92124 15.17284  8.248324 36.680870 61.934130 20.268670
#> 6 47.42691 69.20731 44.95468 29.171970 17.916740 16.255150 14.655590
#>         V23       V24        V25
#> 1 21.000000 22.000000 23.0000000
#> 2  3.312340  1.156517 -0.1476620
#> 3  2.996142  2.967954  1.9995940
#> 4  7.306965  5.736840  3.6256280
#> 5 68.588190 46.498120  0.2360095
#> 6 17.260480 31.222450 46.7170400
Xval <- df[1,2:25] #get X values
Xval
#>   V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> 1  0  1  2  3  4  5  6  7   8   9  10  11  12  13  14  15  16  17  18  19
#>   V22 V23 V24 V25
#> 1  20  21  22  23
df <- df[2:nrow(df), ] #remove first row
dfLng <- gather(df, key = X, value = Value, V2:V25) #rotate to long format
head(dfLng)
#>   V1  X     Value
#> 1  0 V2 27.809850
#> 2  1 V2 27.719660
#> 3  2 V2 30.426700
#> 4  3 V2 16.665490
#> 5  4 V2  8.815617
#> 6  5 V2  6.628881
dfLng <- mutate(dfLng, X = rep(Xval[1,], each = 25))
colnames(dfLng)[1] <- "Y"
head(dfLng)
#>   Y X     Value
#> 1 0 0 27.809850
#> 2 1 0 27.719660
#> 3 2 0 30.426700
#> 4 3 0 16.665490
#> 5 4 0  8.815617
#> 6 5 0  6.628881

Created on 2019-05-22 by the reprex package (v0.2.1)

3

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