I did a GGally-ggpairs-plot (see below) with now having the following issue:
The y-axis of the first variable PdKeyT is labelled with the incorrect values (yellow), instead should be labelled with values according to its x-axis from minus 25 to plus 75 (green). I cannot figure out / explain why, as the code seems ok, and especially as the other variables are labelled correctly (each with the same range at both axes).
Any ideas?
Below the image you will find two code samples.
The first one shows only the corr- and plot-section.
The second is (should be) the complete, reproducible sample with (quite long) df-section ahead.
Here the corr- and plot section of the code:
CorrPoint_LevelvsBands <- round(cor(subset(loopsubset_created[c(45,16:25)])),2)
print(CorrPoint_LevelvsBands)
# Computing correlation matrix with p-values
CorrPoint_LevelvsBands_PVal <- cor_pmat(loopsubset_created[c(45,16:25)])
print(CorrPoint_LevelvsBands_PVal)
print(
ggpairs(loopsubset_created[c(45,16:25)],
title = paste("Corr. analysis"),
lower = list(continuous = wrap("cor",
size = 3)),
upper = list(
continuous = wrap("smooth",
alpha = 0.3,
size = 0.1))
) +
theme(axis.text.x = element_text(angle = 90, hjust = 1, size=8)) +
theme(axis.text.y = element_text(hjust = 1, size=8))
)
Here the full code with df ahead:
loopsubset_created<-structure(list(Site_ID = c("A", "A", "A", "A", "A", "A", "A",
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A",
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A",
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A"
), Spot_Nr = c("1", "1", "1", "1", "1", "1", "1", "1", "1", "1",
"1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1",
"1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1",
"1", "1", "1", "1", "1", "1", "1", "1", "1", "1"), Transkt_Nr = c("2",
"2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2",
"2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2",
"2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2",
"2", "2", "2", "2", "2", "2"), Point_Nr = c("8", "8", "8", "8",
"8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8",
"8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8",
"8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8",
"8", "8", "8"), n = c(46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L,
46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L,
46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L,
46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L),
rank = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), Date = c(20190208L, 20190213L, 20190215L,
20190218L, 20190223L, 20190228L, 20190302L, 20190305L, 20190315L,
20190320L, 20190322L, 20190325L, 20190330L, 20190401L, 20190416L,
20190419L, 20190421L, 20190501L, 20190506L, 20190524L, 20190531L,
20190603L, 20190618L, 20190625L, 20190628L, 20190705L, 20190710L,
20190720L, 20190730L, 20190804L, 20190809L, 20190814L, 20190817L,
20190827L, 20190903L, 20190911L, 20190913L, 20190916L, 20190921L,
20191008L, 20191023L, 20191026L, 20191110L, 20191130L, 20191205L,
20191210L), Point_ID = c("1026", "1026", "1026", "1026",
"1026", "1026", "1026", "1026", "1026", "1026", "1026", "1026",
"1026", "1026", "1026", "1026", "1026", "1026", "1026", "1026",
"1026", "1026", "1026", "1026", "1026", "1026", "1026", "1026",
"1026", "1026", "1026", "1026", "1026", "1026", "1026", "1026",
"1026", "1026", "1026", "1026", "1026", "1026", "1026", "1026",
"1026", "1026"), BLUE = c(1173, 1131, 888, 1045, 997, 938,
780, 832, 1248, 1147, 1124, 1114, 1156, 1140, 1265, 1375,
1244, 2250, 2375, 2000, 2700, 2652, 2087, 1303, 1637, 700,
1235, 1258, 1342, 1369, 1140, 1418, 1352, 1767, 1159, 1530,
1321, 1566, 1468, 1325, 1274, 1354, 2563, 2880, 1777, 1480
), GREEN = c(1242, 1265, 993, 1251, 1302, 1264, 1176, 1171,
1442, 1469, 1450, 1448, 1524, 1530, 1385, 1601, 1451, 2381,
2447, 2163, 3052, 2727, 2354, 1498, 1938, 817, 1427, 1476,
1586, 1535, 1388, 1895, 1619, 2172, 1395, 1731, 1525, 1829,
1716, 1538, 1477, 1583, 2954, 3139, 1815, 1571), RED = c(880,
992, 835, 947, 976, 918, 849, 826, 1285, 1190, 1249, 1213,
1273, 1327, 1322, 1659, 1495, 1617, 1746, 1991, 2204, 1870,
1880, 1166, 1694, 625, 1096, 1206, 1266, 1302, 1102, 1944,
1377, 1793, 1162, 1613, 1393, 1747, 1692, 1399, 1316, 1516,
2683, 2219, 1622, 1573), REDEDGE1 = c(634, 794, 670, 869,
953, 1057, 1028, 924, 1265, 1230, 1193, 1242, 1313, 1412,
1208, 1552, 1322, 1204, 1299, 1834, 1665, 1424, 1637, 1131,
1696, 606, 1052, 1256, 1351, 1344, 1168, 1859, 1367, 1716,
1234, 1562, 1321, 1694, 1773, 1389, 1397, 1600, 2285, 1676,
1448, 1350), REDEDGE2 = c(112, 198, 201, 300, 361, 594, 376,
332, 809, 511, 575, 615, 700, 861, 811, 1128, 807, 428, 331,
1255, 620, 731, 964, 636, 1253, 360, 520, 701, 869, 1104,
620, 1127, 837, 1164, 772, 1131, 838, 1220, 1313, 927, 903,
1267, 1098, 586, 932, 926), REDEDGE3 = c(107, 188, 185, 277,
377, 576, 317, 328, 842, 492, 565, 643, 722, 872, 842, 1070,
893, 504, 303, 1289, 639, 763, 987, 660, 1283, 406, 538,
744, 906, 1183, 698, 1168, 853, 1190, 802, 1170, 893, 1188,
1306, 904, 914, 1261, 1056, 537, 932, 940), BROADNIR = c(79,
155, 164, 193, 340, 453, 294, 250, 801, 408, 558, 531, 663,
834, 839, 1097, 932, 412, 305, 1181, 566, 677, 840, 448,
986, 229, 314, 559, 569, 1071, 400, 875, 581, 920, 446, 802,
662, 1073, 1131, 679, 674, 1005, 892, 428, 923, 1117), NIR = c(21,
55, 70, 145, 233, 402, 125, 189, 677, 225, 261, 380, 477,
535, 651, 797, 617, 305, 146, 1033, 399, 689, 923, 530, 1187,
347, 341, 690, 813, 1213, 535, 919, 787, 1041, 756, 982,
777, 1097, 1133, 880, 824, 1261, 651, 281, 751, 797), SWIR1 = c(92,
136, 95, 88, 237, 173, 134, 182, 392, 119, 121, 215, 219,
209, 302, 146, 149, 214, 155, 560, 241, 574, 634, 416, 981,
256, 390, 649, 840, 928, 582, 683, 901, 924, 940, 818, 804,
1045, 1099, 871, 964, 1265, 118, 136, 425, 390), SWIR2 = c(78,
85, 70, 81, 189, 128, 128, 128, 289, 96, 122, 130, 176, 163,
224, 119, 108, 136, 118, 441, 187, 464, 509, 288, 755, 173,
274, 444, 557, 658, 395, 504, 607, 668, 711, 567, 550, 752,
776, 598, 698, 959, 72, 97, 355, 290), PdKeyT = c(-10L, -20L,
-22L, -22L, -27L, -26L, -26L, -27L, -22L, -17L, -19L, -19L,
-23L, -23L, -5L, -9L, -9L, 54L, 53L, 40L, 60L, 43L, 19L,
15L, 15L, 15L, 13L, 8L, 9L, 7L, 7L, 9L, 6L, 8L, 6L, 12L,
9L, 4L, 2L, 2L, 3L, 2L, 75L, 43L, 28L, 13L)), row.names = 125:170, class = "data.frame")
library(dplyr)
library(ggplot2)
library(ggcorrplot)
library(GGally)
CorrPoint_LevelvsBands <- round(cor(subset(loopsubset_created[c(19,9:18)])),2)
print(CorrPoint_LevelvsBands)
# Computing correlation matrix with p-values
CorrPoint_LevelvsBands_PVal <- cor_pmat(loopsubset_created[c(19,9:18)])
print(CorrPoint_LevelvsBands_PVal)
print(
ggpairs(loopsubset_created[c(19,9:18)],
title = paste("Corr. analysis"),
lower = list(continuous = wrap("cor",
size = 3)),
upper = list(
continuous = wrap("smooth",
alpha = 0.3,
size = 0.1))
) +
theme(axis.text.x = element_text(angle = 90, hjust = 1, size=8)) +
theme(axis.text.y = element_text(hjust = 1, size=8))
)
