我最近开始自学R编程，在这种情况下，我需要使用R绘制多变量数据作为雷达或蜘蛛图。现在我已经通过CSV文件对我的数据进行了子集并将其添加到R.但我有尝试了几个通用代码，它们似乎不起作用。有人可以给我一个好的教程的来源或只是告诉我该怎么做？提前谢谢。
再次问好，
我今天一整天都在尝试，并没有任何积极的结果。这是我的问题， 我的数据是18行和96列数字数据，它们被标准化。
由于我不允许附加图像，因此我将表格的前三行作为代码添加到此处以用于视觉目的，以便您可以了解我的数据的外观。但我将数据作为csv文件提供给R并执行以下代码
HC1 HC2 HC3 HC4 HC5 HC6 HC7 HC8 HC9 HC10 p5-2011 p9-2011 p12-2011 p13-2011 op6-2012 op18-2012 op20-2012 p5-2012 p6-2012 p15-2012 p36-2012 op2-2013 p7-2013 p26-2013 p38-2013 op1-2014 op2-2014 op4-2014 op5-2014 op6-2014 op7-2014 op8-2014 op9-2014 p3-2014 p4-2014 p5-2014 p7-2014 p10-2014 p1-2009 p2-2009 p3-2009 p4-2009 p1-2011 p2-2011 p3-2011 p6-2011 p10-2011 p14-2011 p15-2011 p16-2011 p17-2011 p18-2011 p19-2011 p20-2011 p21-2011 p22-2011 p2-2012 p3-2012 p4-2012 p7-2012 p8-2012 p10-2012 p10-2012 p12-2012 p13-2012 p14-2012 p17-2012 p18-2012 p20-2012 p23-2012 p24-2012 p25-2012 p31-2012 p35-2012 p37-2012 p38-2012 p1-2013 p2-2013 p5-2013 p6-2013 p9-2013 p11-2013 p12-2013 p13-2013 p15-2013 p18-2013 p19-2013 p20-2013 p24-2013 p25-2013 p27-2013 p32-2013 p34-2013 p36-2013 p39-2013 p44-2013
GMCSF -0.1 -0.41 -0.31 0.18 -0.08 -0.57 0.16 -0.35 -0.18 0.5 -0.18 0.06 -0.31 0.73 -0.03 -0.32 0.41 0.37 -0.45 0.55 -0.35 -0.01 -0.04 0.04 0.35 0.02 -0.15 -0.07 1.05 0.03 0.03 -0.22 -0.45 0.08 0.18 -0.18 -0.01 -0.25 0.52 0 -0.05 -0.18 0.16 0.61 0.67 0.56 1.75 -0.26 0.09 0.13 -0.35 -0.19 0.27 -0.12 0.17 0.58 0.31 0.5 -0.41 0.24 0.71 0.81 -0.03 0.59 -0.06 0.04 0.72 -0.28 0.1 0.58 0.16 0.27 0.81 0.25 0.11 -0.11 0.48 -0.31 -0.07 0.18 0.88 0.5 0.3 -0.05 -0.28 -0.39 -0.03 -0.05 -0.52 0.41 0.44 0.09 0.13 -0.35 -0.08 -0.01
IFNa2 -1.64 -0.6 -0.35 0.08 -0.35 -0.35 0.08 -0.11 0.28 0.52 -0.89 0.4 0.66 0.68 0.36 -0.89 0.48 0.61 0.32 0.42 -0.6 0.36 0.38 0.27 0.33 0.5 -0.52 -0.09 0.84 0.27 0.41 -0.52 -0.89 -0.26 0.31 -0.89 -0.26 1.94 0.93 0.06 -0.89 0.31 -0.12 0.76 0.59 0.29 1.18 0.94 0.15 0.44 0.34 -0.37 0.3 0.14 0.45 0.3 -0.15 0.23 -0.32 -0.04 0.89 0.49 0.18 0 0.28 0.45 0.98 0.09 -0.23 0.35 0.26 0.36 0.88 0.98 0.51 0.07 0.48 -0.07 0.28 0.39 0.86 0.37 0.6 -0.12 -0.89 0.02 0.32 0.06 0.15 0.44 0.56 0.04 0.41 0.08 0.05 -0.89
IFNg -0.85 -1.14 -0.94 0.36 -1.1 -0.29 -0.51 -0.58 -0.18 0.74 -0.74 -0.08 -0.53 -0.35 -0.19 -1.39 -0.53 -0.3 -0.61 -0.6 -0.61 -0.64 -1.02 -0.81 -0.62 -0.92 -0.5 -0.74 -0.17 -0.21 -0.5 -0.47 -1.39 0.82 -0.07 -0.51 -0.91 -0.28 0.33 -0.84 -0.69 -1.39 -0.37 0.73 -0.08 -0.37 0.24 0.14 -0.77 -0.67 -0.88 -0.44 -0.82 -0.62 0.28 -0.06 -0.96 0.02 -0.44 -1.06 0.4 -0.84 -0.66 -1.04 -0.72 -0.64 0.94 -0.49 -0.99 -0.26 -0.88 -0.3 -0.25 0.01 -0.59 -0.77 0.01 -1.04 -0.81 0.52 -0.16 -0.06 -0.49 -0.87 -1.31 -0.36 -0.75 -0.83 -0.13 -0.51 -0.2 -0.2 -0.72 -0.66 0.71 -1.14
所以，我做了以下代码，但在这个例子中似乎没有用。
#Data framing
dd<-data.frame(
clust = 1:18,
v1 <- c(-0.10,-1.64,-0.85,-0.28,0.00,-1.34,-0.02,0.00,0.00,0.00,-0.15,-0.45,-1.07,-1.18,-0.18,0.17,-0.77,0.00)
v2 <- c(-0.41,-0.60,-1.14,-0.28,0.00,-1.34,-0.02,0.00,0.00,0.00,-0.15,-0.45,-1.07,-2.04,-0.12,-0.07,-0.77,-0.04)
v3 <- c(-0.31,-0.35,-0.94,0.72,0.00,-0.11,-0.02,0.00,0.00,0.00,-0.15,0.15,-0.31,0.62,0.04,-0.06,-0.77,-0.15)
v4 <- c(0.18,0.08,0.36,-0.28,0.00,0.17,0.07,0.00,0.00,0.00,-0.15,0.15,0.59,-0.55,0.02,0.00,0.47,-0.15)
v5 <- c(-0.08,-0.35,-1.10,-0.28,0.00,-1.34,-0.02,0.00,0.00,0.00,-0.15,-0.45,-1.07,-2.04,-0.25,-0.03,-0.77,-0.22)
v6 <- c(-0.57,-0.35,-0.29,-0.28,0.00,-1.34,-0.02,0.00,0.00,0.00,-0.15,-0.45,-1.07,-0.61,0.06,0.02,-0.77,-0.10)
v7 <- c(0.16,0.08,-0.51,-0.28,0.00,-0.86,-0.02,0.00,0.00,0.01,-0.15,-0.12,-1.07,-0.26,0.19,-0.05,-0.35,0.11)
v8 <- c(-0.35,-0.11,-0.58,-0.28,0.00,0.49,-0.02,0.00,0.00,0.00,-0.15,-0.45,-1.07,-1.60,-0.10,0.09,-0.03,0.17)
v9 <- c(-0.18,0.28,-0.18,-0.28,0.00,-1.34,-0.02,0.00,0.00,0.00,-0.15,-0.45,-1.07,0.52,0.24,-0.19,-0.68,0.07)
v10 <- c(0.50,0.52,0.74,-0.28,0.00,0.63,0.08,0.00,0.00,0.00,0.57,0.63,0.70,0.12,-0.22,0.03,0.67,0.12)
v11 <- c(-0.18,-0.89,-0.74,1.39,0.97,-0.51,0.00,0.20,0.28,0.57,-0.59,-0.35,-0.51,-0.62,0.48,0.05,-0.88,0.35)
v12 <- c(0.06,0.40,-0.08,1.34,2.34,-0.29,0.75,0.11,0.48,0.58,0.02,-0.13,-0.10,-0.13,1.16,0.13,0.19,0.97)
v13 <- c(-0.31,0.66,-0.53,1.14,0.00,-1.34,0.37,0.00,0.00,0.00,-0.15,-0.33,-0.66,-0.52,0.68,0.37,-0.35,0.43)
v14 <- c(0.73,0.68,-0.35,1.77,1.79,-0.54,0.75,0.31,0.74,0.86,0.36,0.24,-0.13,-0.28,0.58,-0.27,-0.34,0.31)
v15 <- c(-0.03,0.36,-0.19,-0.28,0.00,-1.34,0.17,0.00,0.00,0.00,-0.15,-0.24,-0.61,0.00,0.51,0.19,-0.68,0.28)
v16 <- c(-0.32,-0.89,-1.39,0.91,0.54,-0.51,0.02,0.20,0.28,0.57,-0.59,-0.35,-0.75,-0.68,0.21,0.49,-0.28,-0.09)
v17 <- c(0.41,0.48,-0.53,0.94,1.68,-0.62,0.69,0.48,0.10,0.16,-0.15,0.04,-0.04,-0.18,0.49,-0.24,-0.77,0.03)
v18 <- c(0.37,0.61,-0.30,1.45,2.30,0.14,1.06,0.23,0.93,0.45,-0.15,-0.02,0.32,0.06,1.18,0.43,0.24,0.77)
v19 <- c(-0.45,0.32,-0.61,1.10,0.49,-0.52,0.44,0.00,0.32,0.54,-0.37,-0.21,0.48,-0.32,1.19,0.59,-1.02,-0.08)
v20 <- c(0.55,0.42,-0.60,1.20,1.15,-0.86,0.77,0.02,0.38,0.76,0.05,0.20,-0.14,-0.10,0.11,-0.39,-0.32,0.41)
v21 <- c(-0.35,-0.60,-0.61,-0.28,0.00,-1.34,-0.02,0.00,0.00,0.00,-0.15,-0.45,-0.93,-0.25,0.22,0.30,-0.11,0.29)
v22 <- c(-0.01,0.36,-0.64,-0.28,0.00,-1.15,-0.01,0.00,0.00,0.27,-0.15,-0.18,-1.07,-1.33,0.12,-0.11,-0.77,-0.06)
v23 <- c(-0.04,0.38,-1.02,0.68,0.57,-0.54,0.77,-0.06,0.13,0.25,-0.12,-0.56,-0.42,-0.53,0.26,-0.16,-0.40,0.05)
v24 <- c(0.04,0.27,-0.81,1.61,1.50,-0.51,0.45,0.20,0.28,0.57,-0.59,-0.35,-0.75,-0.35,0.46,0.39,-0.88,0.48)
v25 <- c(0.35,0.33,-0.62,0.38,1.10,-0.54,0.69,0.24,0.35,0.25,-0.14,-0.59,-0.91,-0.28,0.00,0.27,-0.41,0.25)
v26 <- c(0.02,0.50,-0.92,0.31,1.16,-0.51,0.40,0.20,0.28,0.57,-0.59,-0.35,-0.56,-0.02,0.64,0.58,-0.13,0.47)
v27 <- c(-0.15,-0.52,-0.50,1.96,0.54,-0.51,0.93,1.02,0.28,0.57,-0.59,-0.35,1.26,0.08,1.02,0.76,-0.58,0.42)
v28 <- c(-0.07,-0.09,-0.74,0.99,0.54,-0.51,0.15,0.20,0.28,0.57,-0.59,-0.19,-0.55,-1.05,0.91,-0.11,-0.41,0.06)
v29 <- c(1.05,0.84,-0.17,1.15,2.19,1.17,0.78,0.89,0.95,0.68,1.56,0.87,0.30,0.04,0.42,0.84,0.08,0.14)
v30 <- c(0.03,0.27,-0.21,1.31,1.09,-0.51,0.58,0.20,0.28,0.57,-0.59,-0.24,-0.64,-0.29,1.11,0.62,-0.18,0.26)
v31 <- c(0.03,0.41,-0.50,1.41,0.54,-0.51,0.72,0.20,0.28,0.57,-0.59,-0.30,-0.25,-0.54,1.11,0.11,-0.48,0.38)
v32 <- c(-0.22,-0.52,-0.47,1.17,0.54,-0.51,0.44,0.20,0.28,0.57,-0.59,-0.11,-0.75,-0.49,0.86,0.45,-0.70,0.13)
v33 <- c(-0.45,-0.89,-1.39,0.19,0.54,-0.51,0.00,0.20,0.28,0.57,-0.59,-0.35,-0.75,-1.75,-0.18,-0.06,-0.88,-0.11)
v34 <- c(0.08,-0.26,0.82,1.75,0.97,-0.51,0.00,0.20,0.28,0.57,-0.59,-0.17,-0.44,-0.36,0.98,0.45,-0.88,0.57)
v35 <- c(0.18,0.31,-0.07,1.37,1.89,0.10,0.89,0.33,0.28,0.57,0.08,-0.19,-0.08,0.45,1.20,1.30,0.08,0.82)
v36 <- c(-0.18,-0.89,-0.51,0.44,0.54,-0.51,1.40,0.20,0.28,0.57,-0.59,0.12,0.57,-0.24,0.72,1.10,-0.72,-0.37)
v37 <- c(-0.01,-0.26,-0.91,1.06,1.45,-0.51,0.68,3.35,0.28,0.57,-0.59,-0.21,0.69,2.30,0.12,0.30,1.54,1.79)
v38 <- c(-0.25,1.94,-0.28,1.82,1.44,-0.51,0.91,0.20,0.28,0.57,-0.59,-0.35,0.40,-0.03,1.20,1.52,-0.13,0.65)
v39 <- c(0.52,0.93,0.33,1.83,1.61,-0.44,1.02,0.20,0.28,0.57,-0.59,-0.21,0.99,0.22,1.20,1.20,0.15,0.77)
v40 <- c(0.00,0.06,-0.84,1.25,0.54,-0.51,0.95,0.20,0.28,0.57,-0.59,-0.34,2.31,0.64,0.92,1.47,0.46,0.87)
v41 <- c(-0.05,-0.89,-0.69,1.25,2.34,-0.51,0.91,0.20,0.28,0.57,-0.59,0.31,0.87,0.28,1.13,1.21,-0.14,-0.36)
v42 <- c(-0.18,0.31,-1.39,0.98,0.54,-0.51,1.01,0.20,0.28,0.57,-0.59,-0.35,-0.46,-0.59,0.24,0.10,-0.21,0.14)
v43 <- c(0.16,-0.12,-0.37,1.88,1.26,-0.86,1.14,0.00,0.22,0.54,-0.37,-0.30,0.37,0.27,1.20,0.36,0.19,0.66)
v44 <- c(0.61,0.76,0.73,2.15,0.00,-1.23,1.08,0.53,0.95,0.46,-0.15,1.19,0.61,0.50,1.19,0.87,0.37,0.55)
v45 <- c(0.67,0.59,-0.08,1.83,1.56,-0.86,1.35,0.36,0.61,0.53,0.27,-0.14,0.21,-0.25,0.66,0.15,0.01,0.48)
v46 <- c(0.56,0.29,-0.37,0.72,1.65,-0.83,0.24,0.00,0.43,0.64,-0.13,0.15,-0.91,-0.70,-0.51,-0.07,-0.12,-0.14)
v47 <- c(1.75,1.18,0.24,1.23,2.88,-0.86,1.99,1.65,1.84,1.49,1.14,-0.18,-0.18,0.26,0.35,-0.27,-0.81,0.62)
v48 <- c(-0.26,0.94,0.14,1.42,0.00,-1.34,0.87,0.57,0.00,0.00,-0.15,0.18,0.15,-0.23,1.19,1.16,-0.77,0.53)
v49 <- c(0.09,0.15,-0.77,0.70,1.69,-0.55,-0.05,0.00,0.20,0.53,-0.37,-0.10,-0.22,-0.50,0.08,0.10,-0.27,0.25)
v50 <- c(0.13,0.44,-0.67,0.89,0.00,-1.34,0.66,0.00,0.00,0.02,-0.15,-0.23,-0.93,-0.31,0.85,0.43,-0.28,0.31)
v51 <- c(-0.35,0.34,-0.88,-0.28,0.00,-1.34,-0.02,0.00,0.00,0.00,-0.15,-0.45,-1.07,-1.14,0.62,-0.16,-0.77,0.22)
v52 <- c(-0.19,-0.37,-0.44,1.66,0.59,-0.79,0.97,0.00,0.52,0.53,-0.37,-0.30,1.00,0.46,1.20,1.19,0.24,0.71)
v53 <- c(0.27,0.30,-0.82,1.29,0.98,-0.86,0.64,0.00,1.28,0.53,-0.37,-0.29,-0.35,-0.03,0.74,-0.01,-0.25,-0.02)
v54 <- c(-0.12,0.14,-0.62,1.56,1.91,-0.47,0.28,0.11,0.22,0.53,-0.24,-0.22,-0.74,-0.24,0.56,0.15,-0.57,0.18)
v55 <- c(0.17,0.45,0.28,0.71,0.00,-1.34,0.50,0.00,0.04,0.00,-0.15,-0.30,-1.07,-0.31,0.17,-0.01,0.01,0.10)
v56 <- c(0.58,0.30,-0.06,1.73,1.54,-0.52,1.52,0.00,0.58,0.53,-0.37,-0.23,0.68,0.32,1.19,0.81,0.03,0.27)
v57 <- c(0.31,-0.15,-0.96,1.13,1.55,-0.86,0.15,0.00,0.32,0.53,-0.26,-0.30,-0.81,-0.26,0.22,-0.01,-0.73,-0.05)
v58 <- c(0.50,0.23,0.02,1.51,1.59,-0.83,1.12,0.36,0.47,0.57,0.13,0.06,-0.10,-0.12,0.26,0.21,-0.22,0.25)
v59 <- c(-0.41,-0.32,-0.44,1.42,1.50,-0.36,0.63,0.00,0.41,0.53,-0.37,-0.30,-0.60,-0.26,1.09,-0.02,-1.02,0.23)
v60 <- c(0.24,-0.04,-1.06,0.32,0.00,-1.34,0.70,0.00,0.00,0.02,-0.15,-0.33,0.91,-0.01,0.52,0.62,0.01,0.58)
v61 <- c(0.71,0.89,0.40,2.15,2.22,-0.50,0.83,0.58,0.78,0.82,-0.15,0.33,0.70,0.01,0.85,0.29,0.77,1.11)
v62 <- c(0.81,0.49,-0.84,1.46,1.38,-0.55,0.60,0.39,0.52,0.63,0.06,0.27,0.54,-0.69,-0.02,0.59,-0.59,-0.01)
v63 <- c(-0.03,0.18,-0.66,0.46,0.57,-0.54,0.30,0.20,0.13,0.25,-0.14,-0.59,-0.91,-0.67,0.16,0.04,-0.61,-0.04)
v64 <- c(0.59,0.00,-1.04,1.17,0.54,-0.51,0.59,0.20,0.28,0.57,-0.59,0.19,0.76,-0.26,0.23,0.95,-0.32,0.04)
v65 <- c(-0.06,0.28,-0.72,-0.28,0.00,-1.34,0.19,0.00,0.00,0.02,-0.15,-0.17,-1.07,-0.96,0.12,-0.19,-0.77,-0.12)
v66 <- c(0.04,0.45,-0.64,1.04,0.00,-1.34,0.59,0.00,0.00,0.01,-0.15,-0.21,-1.07,-0.89,0.49,-0.18,-0.72,0.28)
v67 <- c(0.72,0.98,0.94,2.55,1.61,-0.14,0.36,0.16,0.39,0.56,-0.15,0.25,0.22,0.19,0.90,0.90,0.26,0.73)
v68 <- c(-0.28,0.09,-0.49,1.49,1.24,-0.86,0.21,0.00,0.11,0.53,-0.37,-0.24,-0.49,-0.34,0.82,-0.07,-1.02,0.29)
v69 <- c(0.10,-0.23,-0.99,1.07,0.83,-0.86,-0.01,0.00,0.06,0.53,-0.37,-0.30,-0.45,-0.37,0.73,-0.15,-1.02,-0.08)
v70 <- c(0.58,0.35,-0.26,1.12,1.75,-0.26,0.63,0.10,0.64,0.64,0.18,0.27,0.09,-0.41,0.64,0.21,-0.02,0.35)
v71 <- c(0.16,0.26,-0.88,1.01,0.77,-0.86,0.12,0.00,0.29,0.53,-0.37,-0.30,-0.19,-0.85,0.78,-0.24,-0.99,0.15)
v72 <- c(0.27,0.36,-0.30,1.21,1.55,-0.64,0.60,0.00,0.35,0.56,-0.15,-0.03,-0.35,-0.08,0.99,0.35,-0.97,0.21)
v73 <- c(0.81,0.88,-0.25,1.21,2.28,-0.08,1.02,1.15,1.10,1.07,0.96,0.57,0.47,-0.35,0.55,-0.32,-0.13,0.34)
v74 <- c(0.25,0.98,0.01,0.43,1.93,-1.34,0.57,0.00,0.00,0.00,-0.15,-0.34,0.13,-0.20,1.19,0.79,0.33,0.45)
v75 <- c(0.11,0.51,-0.59,1.43,0.57,-0.54,0.53,-0.06,0.43,0.25,-0.14,0.37,-0.12,-0.07,1.21,-0.19,-0.15,0.35)
v76 <- c(-0.11,0.07,-0.77,0.68,0.57,-0.54,0.18,-0.06,0.13,0.25,-0.14,-0.59,-0.91,-0.73,0.97,-0.02,-0.61,0.11)
v77 <- c(0.48,0.48,0.01,1.55,1.17,-1.34,0.35,0.07,0.20,0.34,-0.15,-0.09,0.67,0.17,0.49,0.31,-0.07,0.68)
v78 <- c(-0.31,-0.07,-1.04,-0.28,0.00,-1.34,0.44,0.00,0.00,0.00,-0.15,-0.25,-1.07,-1.16,-0.04,-0.42,-0.77,-0.05)
v79 <- c(-0.07,0.28,-0.81,-0.28,0.00,-1.34,0.56,0.00,0.00,0.00,-0.15,-0.38,0.51,-0.35,0.14,0.87,-0.77,0.22)
v80 <- c(0.18,0.39,0.52,1.71,0.00,-1.34,0.27,0.94,1.47,0.20,-0.15,0.09,0.73,0.15,0.31,0.16,-0.77,0.12)
v81 <- c(0.88,0.86,-0.16,1.42,1.90,-0.54,0.84,1.02,0.98,0.97,0.78,0.22,0.22,-0.42,0.34,0.23,0.02,0.42)
v82 <- c(0.50,0.37,-0.06,0.29,1.88,-0.54,0.29,0.45,0.34,0.49,0.16,-0.09,0.18,-0.72,0.31,-0.02,-0.48,0.25)
v83 <- c(0.30,0.60,-0.49,0.81,0.57,-0.54,0.53,0.48,0.45,0.62,0.25,0.02,-0.17,-0.65,0.05,0.41,-0.45,0.51)
v84 <- c(-0.05,-0.12,-0.87,1.57,0.54,-0.86,1.02,0.00,0.06,0.53,-0.37,-0.30,0.28,0.35,1.20,0.98,-0.73,0.33)
v85 <- c(-0.28,-0.89,-1.31,0.91,0.54,-0.44,0.30,0.20,0.28,0.57,-0.59,-0.35,0.76,-0.19,0.47,-0.15,-0.81,0.18)
v86 <- c(-0.39,0.02,-0.36,0.96,0.57,-0.54,0.32,0.20,0.13,0.25,-0.14,-0.41,-0.70,-0.47,1.07,0.16,-0.61,0.03)
v87 <- c(-0.03,0.32,-0.75,0.28,0.57,-0.54,0.46,-0.06,0.13,0.32,-0.14,-0.28,0.44,-0.47,0.21,-0.19,-0.61,0.26)
v88 <- c(-0.05,0.06,-0.83,0.38,0.57,-0.54,0.30,-0.06,0.13,0.25,-0.12,-0.59,-0.07,-0.73,0.13,-0.26,-0.52,-0.01)
v89 <- c(-0.52,0.15,-0.13,1.34,0.00,-1.34,0.40,0.00,0.00,0.00,-0.15,-0.27,0.73,-0.47,0.92,0.35,-0.77,0.16)
v90 <- c(0.41,0.44,-0.51,1.59,1.79,-0.54,0.18,0.35,0.37,0.56,0.24,-0.06,-0.10,-0.38,0.43,-0.20,-0.29,0.18)
v91 <- c(0.44,0.56,-0.20,1.46,1.96,-0.54,0.91,0.69,0.13,0.25,-0.07,-0.59,0.34,0.63,0.80,0.14,-0.61,0.49)
v92 <- c(0.09,0.04,-0.20,1.35,0.82,-0.54,0.51,0.26,0.13,0.25,-0.14,-0.45,1.66,0.00,0.63,0.45,-0.61,0.13)
v93 <- c(0.13,0.41,-0.72,0.41,0.57,-0.54,0.49,0.33,0.34,0.42,-0.14,-0.16,-0.08,-0.38,0.38,-0.16,-0.11,0.31)
v94 <- c(-0.35,0.08,-0.66,0.68,0.57,-0.54,0.36,-0.06,0.13,0.25,-0.14,-0.59,0.37,-0.52,1.17,0.28,-0.52,-0.05)
v95 <- c(-0.08,0.05,0.71,1.61,0.00,-1.34,0.66,0.00,0.00,0.00,-0.15,-0.32,-0.46,-0.52,0.70,0.00,0.18,0.82)
v96 <- c(-0.01,-0.89,-1.14,1.61,0.54,-0.51,0.66,0.20,0.28,0.57,-0.59,0.02,1.74,1.06,0.78,0.54,0.15,0.47)
)
#plots
par(mar=c(1,2,2,1))
layout(matrix(1:18, ncol=2))
lapply(1:18, functoin(i){radarchart(rbind(rep(1,6), rep(0,6), dd[i, -1]))})
有人可以指出错误的位置吗？或者只是建议一种替代方法，以便在雷达图中获得这些数据。
欢迎您提出意见和建议，
此致 RAV