如何在 r 中的 x 和 y 轴上使用指定的多个变量构建相关矩阵图
How to build correlation matrix plot using specified multiple variables on x and y axis in r
我有一个包含多个变量的数据框。我可以通过给定的
轻松地用它们的系数值制作相关矩阵图
structure(list(Plot_code = c("AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu",
"AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu",
"AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum",
"AU_Tum", "AU_Tum", "AU_Tum", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra",
"BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra",
"BE_Bra", "BE_Bra", "BE_Bra", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon",
"BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon",
"BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "CA_Gro", "CA_Gro", "CA_Gro",
"CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro",
"CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas",
"CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Obs", "CA_Obs", "CA_Obs",
"CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs",
"CA_Obs", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4",
"CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CH_Cha",
"CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha",
"CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Dav", "CH_Dav", "CH_Dav",
"CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav",
"CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav",
"CH_Dav", "CH_Dav", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru",
"CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Lae",
"CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae",
"CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Oe2",
"CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2",
"CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2",
"CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1",
"CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_wet", "CZ_wet",
"CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet",
"CZ_wet", "CZ_wet", "CZ_wet", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb",
"DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb",
"DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb",
"DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri",
"DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri",
"DE_Gri", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai",
"DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai",
"DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Kli",
"DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli",
"DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli"), year = c(2002L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2001L, 2002L, 2003L, 2005L, 2006L, 2007L, 2008L, 2009L,
2010L, 2011L, 2004L, 2005L, 2006L, 2007L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2004L, 2005L,
2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L,
2015L, 2016L, 2017L, 2018L, 2004L, 2005L, 2006L, 2007L, 2008L,
2009L, 2010L, 2011L, 2012L, 2013L, 2000L, 2001L, 2002L, 2003L,
2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2000L, 2001L,
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2006L, 2007L, 2008L, 2010L, 2011L, 2012L,
2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2000L, 2001L, 2002L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2007L, 2008L,
2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L,
2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 2018L, 2004L, 2005L, 2006L, 2007L,
2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L,
2017L, 2018L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 2018L, 2007L, 2008L, 2009L, 2010L,
2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2001L,
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L,
2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2004L,
2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 2018L, 2000L, 2001L, 2002L, 2003L,
2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L,
2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2005L, 2006L, 2007L,
2008L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L,
2018L), a = c(326.481, 203.934, 245.127, 231.151, 190.164, 233.289,
494.055, 650.641, 446.945, 642.901, 482.894, -544.618, -642.753,
-923.629, -359.137, -638.72, -410.261, -717.406, -581.556, -629.457,
-658.499, -118.493, -268.354, -58.7087, -120.634, -260.701, -50.8907,
21.7235, -157.983, -297.687, -437.75, -203.646, -460.485, -269.649,
-318.619, -492.288, -508.739, -95.514, -477.766, -795.529, -355.451,
184.326, -391.115, -386.415, -410.626, 91.4199, -532.322, -479.533,
-296.511, 65.3056, -145.629, -91.3028, -73.2877, -49.6909, -82.8684,
-134.79, -223.375, -140.681, -132.045, -102.353, -183.515, -334.138,
-100.423, -95.8733, 1.74024, -124.402, -139.338, 45.6885, -72.917,
-158.771, -112.727, -54.3582, -52.8691, -35.6459, -71.4098, -24.7926,
-55.6283, -65.9635, -38.1077, 11.8527, 11.7729, -29.846, -140.74,
-65.404, -85.4606, -150.958, -29.3352, -83.6895, -84.6284, -14.823,
-231.079, -20.6379, -134.878, -116.523, -10.5079, -84.896, -104.2,
-1.4777, -104.078, 371.479, -545.508, -688.586, -462.645, 113.487,
-628.393, -212.363, -254.655, -298.623, -200.623, 121.233, 14.7268,
-10.1752, 243.233, -23.1854, -5.98903, -52.3182, -135.09, -253.466,
-83.5408, -165.738, -391.073, -463.639, -27.2125, -113.151, 65.3596,
-358.027, -280.791, -231.078, -325.604, -224.164, -212.406, -296.681,
-80.6472, -226.267, -168.346, -277.308, -879.968, -672.64, -913.254,
-788.656, -892.532, -1158.66, -1069.79, -1155.44, -1207.05, -1246.63,
-1033.21, -1525.85, 160.592, -227.713, -247.628, -172.983, 359.106,
58.8087, 49.8333, -246.873, 741.346, -338.443, -185.905, -1.20619,
-171.167, -220.584, 692.192, -215.788, 296.959, -736.218, -805.674,
-814.118, -813.073, -1049.4, -885.368, -868.744, -1115.26, -952.366,
-929.597, -823.728, -873.533, -221.182, -74.6576, -160.622, -190.21,
-28.2721, 103.069, 37.2297, 85.9477, 233.07, -5.81195, 192.551,
220.122, -195.731, -32.7337, -300.576, -232.568, -89.0346, -598.824,
-86.2762, -297.222, -83.6348, -282.213, 9.0492, -109.163, -296.809,
-377.416, -77.4289, -362.023, -272.873, -196.248, 17.7066, -76.3452,
-54.6378, -110.499, -88.0087, -119.344, -56.078, -160.209, -88.247,
-77.6548, -84.1161, -31.4015, -138.573, -80.9845, -16.4784, -632.864,
-638.75, -630.527, -559.942, -414.712, -657.618, -566.553, -563.711,
-535.207, -610.427, -467.942, -472.147, -524.325, -544.337, -500.376,
-481.629, -481.609, -675.079, -374.189, -37.0132, 50.0497, -35.562,
182.579, -53.4777, -293.517, 177.378, 19.4601, -260.309, -59.0721,
-330.385, -4.59423, -109.657), b = c(322.634, 193.444, 227.661,
233.379, 183.711, 256.219, 453.632, 653.229, 452.533, 635.507,
504.897, -544.62, -651.515, -918.768, -384.088, -644.314, -457.779,
-724.055, -587.384, -617.951, -646.402, -123.123, -265.508, -60.6077,
-120.783, -258.057, -54.2095, 23.0595, -154.059, -292.435, -434.236,
-200.377, -462.919, -268.476, -313.765, -498.154, -506.65, -98.5015,
-469.605, -797.243, -357.67, 188.347, -397.956, -391.178, -408.19,
92.86, -535.276, -490.835, -290.804, 59.7977, -149.497, -95.338,
-67.7797, -50.3322, -90.2691, -140.999, -218.437, -149.943, -133.808,
-103.559, -186.694, -337.364, -104.151, -91.2041, 1.21685, -125.483,
-143.733, 45.6502, -74.3712, -160.832, -111.191, -55.5079, -51.3575,
-37.6118, -72.9554, -23.6008, -55.6863, -72.505, -39.026, 8.64705,
12.3014, -29.6163, -136.31, -65.1504, -86.0661, -156.25, -16.7411,
-76.7034, -84.6127, -7.4518, -216.709, -26.2025, -148.2, -106.077,
-60.9692, -112.691, -116.436, -71.1547, -125.89, 364.33, -516.965,
-651.809, -513.061, 82.9459, -635.43, -181.048, -294.642, -336.096,
-253.744, 76.6592, -24.7232, -80.2533, 147.947, -66.7923, 42.2208,
-28.2218, -118.43, -257.176, -47.0861, -161.117, -333.379, -510.496,
-52.936, -202.695, 14.7941, -362.261, -261.379, -220.378, -381.937,
-190.237, -188.287, -282.316, -76.9707, -229.074, -130.691, -315.434,
-814.644, -640.745, -906.927, -789.157, -873.037, -1134.97, -1066.63,
-1174.04, -1139.25, -1218.83, -997.174, -1552.44, 138.109, -181.225,
-237.657, -165.386, 367.384, 60.6187, 42.8955, -260.846, 741.742,
-338.482, -205.791, -11.8622, -158.317, -219.694, 708.457, -226.663,
290.774, -730.813, -801.908, -793.431, -808.587, -1036.24, -887.217,
-863.565, -1120.19, -962.892, -928.74, -830.217, -873.571, -223.823,
-76.5969, -162.284, -189.794, -32.3768, 94.4481, 37.2759, 88.9164,
238.534, -8.46004, 193.22, 220.151, -196.397, -30.202, -305.369,
-230.381, -85.9459, -593.508, -86.7986, -287.566, -81.6529, -278.603,
10.513, -110.688, -300.755, -384.073, -85.2458, -361.478, -271.902,
-198.22, 17.3501, -79.3437, -54.9024, -112.517, -89.0407, -117.046,
-56.2903, -156.699, -91.3378, -80.769, -84.2795, -36.6802, -141.531,
-82.7491, -9.47905, -641.951, -655.197, -637.111, -568.627, -424.166,
-662.521, -572.782, -561.137, -547.09, -615.618, -466.17, -480.047,
-529.037, -551.73, -506.746, -477.391, -487.317, -673.51, -381.566,
-35.6867, 51.2804, -40.1103, 178.331, -53.8158, -293.854, 179.136,
23.2453, -264.489, -61.4489, -329.167, -6.39689, -111.783), c = c(8.11395,
4.69183, 3.94601, 3.54897, 5.21155, 12.1515, 4.62441, 7.28486,
5.59524, 8.29465, 8.06398, 0.00153059, 8.84912, 5.03982, 4.01537,
2.21725, 7.40027, 4.78034, 1.94876, 5.00531, 4.58972, 2.29123,
6.45276, 2.18537, 1.13422, 0.928997, 1.77812, 1.42241, 2.0839,
1.34805, 1.80062, 2.05553, 7.40603, 4.51429, 5.20749, 1.62373,
1.97971, 0.623137, 3.68308, 5.37488, 6.3727, 3.01464, 4.56223,
1.70532, 0.440911, 1.25472, 0.692534, 2.32074, 2.63057, 1.09008,
2.29437, 1.26616, 1.30544, 1.87968, 1.84791, 2.46733, 3.06766,
3.9044, 3.27443, 3.09323, 2.48735, 0.573311, 0.958169, 1.69844,
0.672918, 0.309432, 1.24827, 1.61291, 1.46997, 1.49926, 1.23057,
0.47406, 0.762624, 1.3271, 0.549278, 0.28815, 0.378701, 0.598918,
1.15464, 1.51677, 1.3537, 2.52231, 2.92066, 1.63151, 1.46882,
0.83477, 7.81569, 7.12095, 4.7557, 4.80368, 3.94623, 2.36429,
4.2003, 7.31042, 13.7233, 15.1242, 8.5967, 17.9395, 23.5283,
14.2777, 20.6924, 11.6454, 16.8474, 9.29696, 15.9649, 11.9063,
8.22721, 8.98131, 7.9822, 15.153, 8.78069, 10.4863, 21.7927,
22.0191, 38.0869, 29.2025, 28.1252, 24.6324, 30.4137, 26.38,
24.7401, 28.8121, 23.2191, 11.7715, 30.6534, 3.7051, 8.48356,
5.55515, 7.87199, 8.28644, 7.72792, 6.84922, 9.927, 12.1588,
23.7546, 10.9479, 13.0295, 11.5461, 10.8413, 7.12994, 10.7487,
7.39817, 11.0487, 9.2065, 14.5651, 9.3008, 10.738, 17.6314, 8.35181,
15.291, 6.09852, 3.53532, 5.92717, 2.95389, 5.17524, 1.64728,
2.87371, 1.1697, 3.75515, 3.86018, 5.75163, 6.44313, 4.35274,
2.30329, 3.4527, 5.01465, 2.85555, 6.32233, 1.21829, 4.34273,
1.20555, 1.36025, 1.19302, 2.11738, 4.23596, 2.30242, 2.21917,
1.07283, 0.588832, 0.677145, 0.516664, 1.73665, 7.07306, 5.31417,
3.46085, 0.878398, 1.33794, 0.532913, 1.30456, 4.33008, 1.41525,
1.09158, 0.58211, 1.51661, 1.98902, 1.4248, 2.77915, 2.34724,
1.01295, 2.25518, 2.44303, 0.832564, 0.91921, 3.13882, 0.760879,
0.619897, 2.54895, 0.810879, 1.0869, 0.907865, 1.0499, 0.402154,
0.379856, 1.57361, 0.542193, 0.526181, 1.51088, 1.70106, 0.739337,
1.45576, 1.7926, 2.52713, 4.60597, 4.45995, 3.25605, 3.01084,
1.56884, 3.42755, 5.41048, 3.53527, 4.34503, 5.01294, 1.67405,
2.63015, 3.27977, 5.88868, 4.14693, 1.27931, 5.30468, 1.95638,
0.954256, 1.19003, 1.22576, 4.63183, 2.11131, 0.480344, 1.16239,
1.70187, 5.01625, 2.26359, 0.447506, 0.786618, 0.769038, 1.40851
), d = c(2364.88, 2095.94, 2236.45, 2074.26, 2272.24, 2610.75,
3092.71, 3337.97, 2658.63, 3264.33, 2650.9, 3354.49, 2417.31,
2134.16, 2687.91, 2608.11, 2728.2, 2607.78, 2754.87, 2588.26,
2706.36, 1096.88, 828.526, 1252.22, 1236.95, 1243.46, 1272.43,
1885.31, 1654.19, 1280.48, 1147.4, 1399.04, 1312.73, 1528.54,
1099.12, 969.212, 1167.43, 767.743, 1245.71, 900.431, 1321.3,
739.596, 1117.8, 1136.33, 1075.59, 653.556, 1179.42, 797.182,
978.486, 601.904, 859.527, 1117.43, 1161.08, 1087.04, 1181.68,
906.008, 792.19, 789.177, 800.62, 718.711, 927.875, 946.487,
835.784, 880.955, 880.766, 981.336, 1149.87, 1069.85, 1015.56,
986.14, 1059.07, 765.716, 795.637, 697.466, 713.383, 726.391,
813.597, 772.567, 820.073, 861.23, 900.648, 936.558, 1244.46,
1212.09, 1157.77, 1287.61, 1377.25, 1532.01, 1545.1, 1731.48,
1349.46, 1402.36, 1430.59, 1724.46, 2775.9, 2900.95, 2666.68,
2818.56, 2385.12, 2229.74, 2033.06, 1939.02, 2026.15, 3129.63,
2073.54, 1957.84, 1345.32, 1272.64, 1331.49, 1640.54, 1419.61,
1438.01, 1307.09, 833.701, 933.431, 588.714, 948.922, 920.67,
876.146, 465.514, 752.314, 868.809, 1317.47, 1191.55, 1376.63,
1625.36, 1615.15, 1621.79, 1943.26, 1829.28, 1655.05, 1881.57,
1882.41, 1938.6, 2117.85, 2255.26, 811.992, 1183.09, 1223.19,
1142.1, 934.924, 985.541, 1209.79, 1068.88, 839.981, 832.602,
979.319, 1343.52, 1855.38, 1442.8, 1085.95, 1341.46, 1418.45,
1496.5, 1427.77, 1283.25, 1316.73, 1299.02, 1285.09, 1341.89,
1451.11, 1563.17, 1272.28, 1769.69, 1668.88, 1070.27, 1070.77,
1016.89, 1135.04, 912.102, 783.108, 967.88, 966.743, 893.888,
1015.97, 1229.3, 1457.76, 1179.29, 1014.33, 1057.41, 969.066,
993.651, 1410.2, 1173.4, 1087.09, 1106.54, 1107.95, 1247.9, 1367.47,
996.407, 861.01, 673.115, 1054.01, 1185.34, 825.778, 884.163,
960.616, 661.482, 864.329, 656.779, 789.821, 825.212, 1124.46,
1177.24, 1163.56, 1019.91, 1125.93, 1444.11, 980.447, 1139.74,
1516.58, 1544.64, 966.443, 1442.65, 1586.29, 1592.7, 1474.45,
1941.27, 1605.55, 1802.65, 1766.17, 1238.43, 1161.48, 1053.05,
1124.67, 1040.27, 1128.22, 1074.81, 1092.27, 1050.8, 1096.84,
1115.03, 950.926, 1038.46, 1064.06, 1103.09, 1187.83, 1152.38,
1004.36, 1029.2, 744.56, 1483.48, 1131.6, 1169.72, 717.072, 1140.42,
1214.57, 943.749, 1435.17, 1377.54, 1616.22, 1333.38, 824.056,
748.039), x = c(0.025833333, 0.027692308, 0.027692308, 0.026153846,
0.028333333, 0.0275, 0.025384615, 0.022307692, 0.023846154, 0.023846154,
0.026153846, 0.007777778, 0.009473684, 0.016315789, 0.010555556,
0.01, 0.012105263, 0.01, 0.008421053, 0.006842105, 0.007894737,
0.024285714, 0.019444444, 0.025333333, 0.019333333, 0.018823529,
0.025, 0.018823529, 0.023333333, 0.018125, 0.022352941, 0.019285714,
0.02125, 0.02, 0.020588235, 0.042, 0.039166667, 0.044545455,
0.036363636, 0.041, 0.033333333, 0.047272727, 0.041818182, 0.045,
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0.021666667, 0.019166667, 0.02, 0.02, 0.015454545, 0.018, 0.019166667,
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0.0175, 0.016363636, 0.019166667, 0.019166667, 0.0175, 0.016666667,
0.018181818, 0.0175, 0.018333333, 0.019090909, 0.030833333, 0.027692308,
0.027142857, 0.029230769, 0.027692308, 0.028461538, 0.028333333,
0.028461538, 0.029230769, 0.027142857, 0.028461538, 0.028461538,
0.013333333, 0.011666667, 0.016666667, 0.018, 0.018333333, 0.015,
0.02, 0.021666667, 0.015, 0.02, 0.015, 0.018, 0.013333333, 0.03,
0.025, 0.023333333, 0.015, 0.018, 0.015, 0.023, 0.026666667,
0.025, 0.027, 0.025, 0.021, 0.025, 0.03, 0.025, 0.025, 0.025,
0.016153846, 0.017692308, 0.02, 0.015384615, 0.017692308, 0.015384615,
0.018461538, 0.014166667, 0.019230769, 0.016923077, 0.017692308,
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0.028333333, 0.029166667, 0.029166667, 0.029166667, 0.026363636,
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0.024285714, 0.025384615, 0.02, 0.0225, 0.02, 0.022727273, 0.025384615,
0.013, 0.014545455, 0.012727273, 0.017272727, 0.018181818, 0.0125,
0.015833333, 0.012727273, 0.013333333, 0.015454545, 0.014166667,
0.015833333, 0.011666667, 0.0125, 0.019090909, 0.012727273, 0.0125,
0.012727273, 0.013636364, 0.045454545, 0.041818182, 0.049090909,
0.053636364, 0.045, 0.040833333, 0.0425, 0.043636364, 0.035833333,
0.044166667, 0.037272727, 0.038333333, 0.051818182), y = c(0.058333333,
0.06, 0.053846154, 0.056923077, 0.0575, 0.056666667, 0.051538462,
0.050769231, 0.056923077, 0.055384615, 0.058461538, 0.025, 0.03,
0.036842105, 0.03, 0.029473684, 0.033157895, 0.027368421, 0.027368421,
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0.025833333, 0.025454545, 0.025833333, 0.029166667, 0.026666667,
0.025833333, 0.023636364, 0.0275, 0.0275, 0.025454545, 0.055,
0.046153846, 0.050714286, 0.055384615, 0.052307692, 0.059230769,
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0.051818182, 0.053333333, 0.046363636, 0.050909091, 0.050833333,
0.072307692, 0.072307692, 0.098666667, 0.100714286, 0.09, 0.065384615,
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0.046153846, 0.045833333, 0.047272727, 0.045, 0.05, 0.043846154,
0.049090909, 0.045833333, 0.052142857, 0.053846154, 0.043846154,
0.049166667, 0.039166667, 0.041818182, 0.054615385, 0.026, 0.026363636,
0.03, 0.029090909, 0.037272727, 0.021666667, 0.034166667, 0.025454545,
0.025833333, 0.027272727, 0.025833333, 0.025833333, 0.023333333,
0.025833333, 0.03, 0.024545455, 0.025, 0.023636364, 0.024545455,
0.097272727, 0.079090909, 0.094545455, 0.100909091, 0.093333333,
0.076666667, 0.09, 0.094545455, 0.079166667, 0.089166667, 0.076363636,
0.0825, 0.108181818), z = c(0.438333333, 0.386923077, 0.425384615,
0.4, 0.408333333, 0.395, 0.38, 0.426923077, 0.42, 0.39, 0.439230769,
0.212222222, 0.203684211, 0.201052632, 0.186111111, 0.192105263,
0.208947368, 0.203157895, 0.208947368, 0.204736842, 0.200526316,
0.233571429, 0.220555556, 0.217333333, 0.234666667, 0.229411765,
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0.337, 0.360833333, 0.340909091, 0.328181818, 0.329166667, 0.351,
0.369166667, 0.344166667, 0.348888889, 0.352, 0.32, 0.235, 0.2625,
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0.225833333, 0.220909091, 0.303, 0.318, 0.314, 0.292, 0.271,
0.269, 0.286, 0.253, 0.265, 0.285555556, 0.265, 0.154545455,
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0.225, 0.23, 0.237272727, 0.2375, 0.234166667, 0.263333333, 0.249166667,
0.26, 0.24, 0.246666667, 0.258181818, 0.405833333, 0.426923077,
0.385, 0.405384615, 0.415384615, 0.385384615, 0.384166667, 0.424615385,
0.386923077, 0.412142857, 0.406923077, 0.371538462, 0.133333333,
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0.1125, 0.126666667, 0.126666667, 0.142, 0.135, 0.371, 0.357777778,
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0.315714286, 0.340769231, 0.365384615, 0.335833333, 0.32, 0.320833333,
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0.335833333, 0.17625, 0.2075, 0.19125, 0.19, 0.19375, 0.18375,
0.198571429, 0.18125, 0.1975, 0.18, 0.18375, 0.181428571, 0.341818182,
0.340833333, 0.3475, 0.31, 0.3425, 0.320833333, 0.290833333,
0.35, 0.345833333, 0.350909091, 0.327272727, 0.3425, 0.279230769,
0.253076923, 0.306666667, 0.365714286, 0.321333333, 0.347692308,
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0.333076923, 0.385833333, 0.350909091, 0.3875, 0.351538462, 0.406923077,
0.347272727, 0.355, 0.369285714, 0.378461538, 0.375384615, 0.335833333,
0.368333333, 0.355454545, 0.313846154, 0.313, 0.323636364, 0.34,
0.331818182, 0.296363636, 0.301666667, 0.3275, 0.319090909, 0.378333333,
0.344545455, 0.351666667, 0.344166667, 0.344166667, 0.355, 0.353636364,
0.349090909, 0.325833333, 0.36, 0.367272727, 0.371818182, 0.273636364,
0.29, 0.245454545, 0.373333333, 0.313333333, 0.35, 0.283636364,
0.34, 0.415, 0.369090909, 0.29, 0.298181818)), class = "data.frame", row.names = c(NA,
-254L)
library(ggcorrplot)
ggcorrplot(df)
现在，我想在 x 轴上仅使用 a、b、c 和 d 变量，在 y 轴上仅使用 x、y 和 z 变量来构建相关矩阵图。我不希望它们都在 x 轴和 y 轴上。我还想在关系显着的地方将系数设为斜体。谁能告诉我如何使用任何包在 r 中执行此操作。
非常感谢任何帮助！
corrplot::corrplot(cor(data[-c(1:2)])[1:4,5:7], method = "number")
看看 ?corrplot 它非常可定制！尤其是参数 addshade、shade.lwd 和 shade.col 因为我不知道你定义什么为“重要”
我有一个包含多个变量的数据框。我可以通过给定的
轻松地用它们的系数值制作相关矩阵图structure(list(Plot_code = c("AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu",
"AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu", "AT_Neu",
"AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum", "AU_Tum",
"AU_Tum", "AU_Tum", "AU_Tum", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra",
"BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra", "BE_Bra",
"BE_Bra", "BE_Bra", "BE_Bra", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon",
"BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon",
"BE_Lon", "BE_Lon", "BE_Lon", "BE_Lon", "CA_Gro", "CA_Gro", "CA_Gro",
"CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro", "CA_Gro",
"CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas",
"CA_Oas", "CA_Oas", "CA_Oas", "CA_Oas", "CA_Obs", "CA_Obs", "CA_Obs",
"CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs", "CA_Obs",
"CA_Obs", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4",
"CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CA_TP4", "CH_Cha",
"CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha",
"CH_Cha", "CH_Cha", "CH_Cha", "CH_Cha", "CH_Dav", "CH_Dav", "CH_Dav",
"CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav",
"CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav", "CH_Dav",
"CH_Dav", "CH_Dav", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru",
"CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Fru", "CH_Lae",
"CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae",
"CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Lae", "CH_Oe2",
"CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2",
"CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2", "CH_Oe2",
"CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1",
"CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_BK1", "CZ_wet", "CZ_wet",
"CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet", "CZ_wet",
"CZ_wet", "CZ_wet", "CZ_wet", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb",
"DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb",
"DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb", "DE_Geb",
"DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri",
"DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri", "DE_Gri",
"DE_Gri", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai",
"DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai",
"DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Hai", "DE_Kli",
"DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli",
"DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli", "DE_Kli"), year = c(2002L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2001L, 2002L, 2003L, 2005L, 2006L, 2007L, 2008L, 2009L,
2010L, 2011L, 2004L, 2005L, 2006L, 2007L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2004L, 2005L,
2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L,
2015L, 2016L, 2017L, 2018L, 2004L, 2005L, 2006L, 2007L, 2008L,
2009L, 2010L, 2011L, 2012L, 2013L, 2000L, 2001L, 2002L, 2003L,
2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2000L, 2001L,
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2006L, 2007L, 2008L, 2010L, 2011L, 2012L,
2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2000L, 2001L, 2002L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2007L, 2008L,
2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L,
2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 2018L, 2004L, 2005L, 2006L, 2007L,
2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L,
2017L, 2018L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 2018L, 2007L, 2008L, 2009L, 2010L,
2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2001L,
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L,
2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2004L,
2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 2018L, 2000L, 2001L, 2002L, 2003L,
2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L,
2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2005L, 2006L, 2007L,
2008L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L,
2018L), a = c(326.481, 203.934, 245.127, 231.151, 190.164, 233.289,
494.055, 650.641, 446.945, 642.901, 482.894, -544.618, -642.753,
-923.629, -359.137, -638.72, -410.261, -717.406, -581.556, -629.457,
-658.499, -118.493, -268.354, -58.7087, -120.634, -260.701, -50.8907,
21.7235, -157.983, -297.687, -437.75, -203.646, -460.485, -269.649,
-318.619, -492.288, -508.739, -95.514, -477.766, -795.529, -355.451,
184.326, -391.115, -386.415, -410.626, 91.4199, -532.322, -479.533,
-296.511, 65.3056, -145.629, -91.3028, -73.2877, -49.6909, -82.8684,
-134.79, -223.375, -140.681, -132.045, -102.353, -183.515, -334.138,
-100.423, -95.8733, 1.74024, -124.402, -139.338, 45.6885, -72.917,
-158.771, -112.727, -54.3582, -52.8691, -35.6459, -71.4098, -24.7926,
-55.6283, -65.9635, -38.1077, 11.8527, 11.7729, -29.846, -140.74,
-65.404, -85.4606, -150.958, -29.3352, -83.6895, -84.6284, -14.823,
-231.079, -20.6379, -134.878, -116.523, -10.5079, -84.896, -104.2,
-1.4777, -104.078, 371.479, -545.508, -688.586, -462.645, 113.487,
-628.393, -212.363, -254.655, -298.623, -200.623, 121.233, 14.7268,
-10.1752, 243.233, -23.1854, -5.98903, -52.3182, -135.09, -253.466,
-83.5408, -165.738, -391.073, -463.639, -27.2125, -113.151, 65.3596,
-358.027, -280.791, -231.078, -325.604, -224.164, -212.406, -296.681,
-80.6472, -226.267, -168.346, -277.308, -879.968, -672.64, -913.254,
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0.337, 0.360833333, 0.340909091, 0.328181818, 0.329166667, 0.351,
0.369166667, 0.344166667, 0.348888889, 0.352, 0.32, 0.235, 0.2625,
0.240833333, 0.243333333, 0.227272727, 0.244, 0.246666667, 0.2275,
0.225833333, 0.220909091, 0.303, 0.318, 0.314, 0.292, 0.271,
0.269, 0.286, 0.253, 0.265, 0.285555556, 0.265, 0.154545455,
0.161818182, 0.153333333, 0.156363636, 0.154166667, 0.153333333,
0.155, 0.146666667, 0.159090909, 0.161818182, 0.1525, 0.244166667,
0.225, 0.23, 0.237272727, 0.2375, 0.234166667, 0.263333333, 0.249166667,
0.26, 0.24, 0.246666667, 0.258181818, 0.405833333, 0.426923077,
0.385, 0.405384615, 0.415384615, 0.385384615, 0.384166667, 0.424615385,
0.386923077, 0.412142857, 0.406923077, 0.371538462, 0.133333333,
0.12, 0.123333333, 0.116, 0.15, 0.135, 0.121666667, 0.113333333,
0.123333333, 0.138333333, 0.135, 0.126, 0.116666667, 0.158333333,
0.1125, 0.126666667, 0.126666667, 0.142, 0.135, 0.371, 0.357777778,
0.372, 0.378, 0.4, 0.376, 0.393, 0.352, 0.367, 0.363, 0.392,
0.346153846, 0.333846154, 0.3375, 0.375384615, 0.362307692, 0.340769231,
0.366923077, 0.339166667, 0.346153846, 0.318461538, 0.359230769,
0.315714286, 0.340769231, 0.365384615, 0.335833333, 0.32, 0.320833333,
0.329166667, 0.316666667, 0.344166667, 0.330833333, 0.343333333,
0.338, 0.334545455, 0.343333333, 0.328333333, 0.326666667, 0.359166667,
0.335833333, 0.17625, 0.2075, 0.19125, 0.19, 0.19375, 0.18375,
0.198571429, 0.18125, 0.1975, 0.18, 0.18375, 0.181428571, 0.341818182,
0.340833333, 0.3475, 0.31, 0.3425, 0.320833333, 0.290833333,
0.35, 0.345833333, 0.350909091, 0.327272727, 0.3425, 0.279230769,
0.253076923, 0.306666667, 0.365714286, 0.321333333, 0.347692308,
0.237333333, 0.3, 0.238666667, 0.254666667, 0.276428571, 0.292,
0.335714286, 0.39, 0.302666667, 0.315333333, 0.306666667, 0.297333333,
0.333076923, 0.385833333, 0.350909091, 0.3875, 0.351538462, 0.406923077,
0.347272727, 0.355, 0.369285714, 0.378461538, 0.375384615, 0.335833333,
0.368333333, 0.355454545, 0.313846154, 0.313, 0.323636364, 0.34,
0.331818182, 0.296363636, 0.301666667, 0.3275, 0.319090909, 0.378333333,
0.344545455, 0.351666667, 0.344166667, 0.344166667, 0.355, 0.353636364,
0.349090909, 0.325833333, 0.36, 0.367272727, 0.371818182, 0.273636364,
0.29, 0.245454545, 0.373333333, 0.313333333, 0.35, 0.283636364,
0.34, 0.415, 0.369090909, 0.29, 0.298181818)), class = "data.frame", row.names = c(NA,
-254L)
library(ggcorrplot)
ggcorrplot(df)
现在，我想在 x 轴上仅使用 a、b、c 和 d 变量，在 y 轴上仅使用 x、y 和 z 变量来构建相关矩阵图。我不希望它们都在 x 轴和 y 轴上。我还想在关系显着的地方将系数设为斜体。谁能告诉我如何使用任何包在 r 中执行此操作。
非常感谢任何帮助！
corrplot::corrplot(cor(data[-c(1:2)])[1:4,5:7], method = "number")
看看 ?corrplot 它非常可定制！尤其是参数 addshade、shade.lwd 和 shade.col 因为我不知道你定义什么为“重要”