我已经挣扎了几个小时，但我敢肯定这很简单。
我有一个数据集，您可以通过从此处底部的混乱中复制和粘贴来复制它。
它开始看起来像这样
> head(mydata)
POSITION W_MEAN T_MEAN W_STDEV T_STDEV COUNT POSCAT
1 1 108.36 109.37 5.02 4.61 117 START
2 2 107.31 109.32 4.50 3.67 167 START
3 3 108.82 109.72 4.62 4.70 162 START
4 4 109.73 111.17 3.90 3.29 154 START
5 5 109.69 111.16 4.31 4.41 163 START
6 6 110.23 111.69 4.71 3.68 159 START
POSCAT 是我根据职位分配的类别。1-40 = 开始，41-120 = 中间，121+ = 结束。
我为整个数据框制作了一个很好的直方图，使用
m <- ggplot(mydata, aes(x=T_MEAN))
m + geom_histogram(aes(y = ..density..)) + geom_density()
但我想使用 POSCAT 在 START、MIDDLE 和 END 上刻面直方图，所以我试过这个
m <- ggplot(mydata, aes(x=T_MEAN))
m + geom_histogram(aes(y = ..density..)) + geom_density()
m + facet_grid(~ POSCAT)
它给了我这个错误
错误：绘图中没有图层
我究竟做错了什么？
谢谢您的帮助！
mydata <-结构（列表（位置= c（1、2、3、4、5、6、7、8、9、10、11、12、13、14、15、16、17、18、19、20 , 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45 , 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 , 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95 , 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120 , 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145 , 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163), W_MEAN = c(108.36, 107.31, 73,82, 10) 109.69、110.23、109.64、109.69、110.81,109.89,110.41,110.34,111.18,110.39,111.18,110.59,110.69,110.5,111.5,111.33,111.05,111.78,111.59,111.94,111.4,112.09,111.74,112.09,111.74,112.23,112.08,112.68,112.08,112.68,112.73,112.72,112.73,112.72,112.11,112.72,112.11， 112.36,112.25,112.65,112.57,112.86,112.3,112.74,1132.8,112.47,112.78,112.92，112.24,112.8,112.92,112.36,112.88,112.86,112.78,1133.14,112.78,1133.14,112.97,112.84,112.41,112.94,112.41,112.94,112.52,112.94,112.52,112.94,112.52,112.94,112.52,112.94,112.52,112.94,112.52,112.94,112.52,112.94,112.52,112.94,112.52,112.94,112.52,112.63， 113.19,112.71,1132.89,112.83,113.15,112.51,112.81,112.72,112.2,113.04,111.49,113.06,112.48,112.82,112,112.62,112.24,112.8,112.41,112.67,112.75,11121,112.52,111.88,112.52,111.88,112.58， 111.08,112.58,113.01,112.15,112.32,112.06,112.32,112.06,112.38,1112.11,112.33,211.57,112.33,112.03,111.97,111.99,111.94,112.29,111.43,111.72,111.73,112.08,111.45,112.08,111.45,111.56,111.79,111.56,111.79， 111.07、111.35、111.29、111。35,110.93,110.87,110.64,110.74,110.52,110.39,110.14,109.91,110.95,110.85,111.08,110.49,110.81,109.8,110.8,110.14,109.95,110.46,110.5,110.46,110.5,110.53,110.74,110.39,109.5,110.39,109.5,110.39,109.5,110.28， 110.46,110.57,110.22,110.42,110.2,110.16,110.04,110.52,110.79,109.43,110.55,110.35,110.66,110.05,110.73,110.48,110.73,109.8,110.95,110.33,110.8,110.7,110.3,110.26,110.7,110.5,110.28,110.39， 110.73,109.96），T_MEAN = C（109.37,109.32,111.16,111.69,111.6,111.59,112.07,111.78,112.01,112.16,112.43,112.23,112.43,112.23,112.17,112.6,112.48,112.45,113.4,113.02,113.08 ，113.2,113.41,113.38,113.41,113.64,113.5,114.1,113.97,114.2，114.42,114.37,114.06,114.07,114.06,114.25,114.06,114.25,114.1,114.57,114.4,114.25,114.97,114.4,114.64,114.4,114.64,114.29,114.3,114.29,114.3,114.29,114.3,114.5 , 114.5, 114.45,114.48,114.89,114.46,114.77,114.76,114.3,114.47,114.4,114.61,114.25,114.5,114.73,114.73,114.42,114.34,114.52,114.39,114.43,114.02,114.23,113.8,114.4,114,113.8,114.4,114.17,114.35,114.03， 114.29,114.44,114.19,114.27,114.22,114.25,113.9,113.84,113.99,113.82,113.32,113.93,114.26,114.04,114.4,114.06,113.96,113.97,114.05,113.72,113.94,113.51,113.97,113.51,113.97,113.64,113.54， 113.57,113.78,113.59,113.01,113.5,113.43,113.44,113.02,113.4,1133.6,112.97,112.65,112.95,112.99,112.51,112.45,112.26,112.51,112.09,111.86,111.8,111.68,112.46,112.33,112.46,112.33,112.67， 112.02,112.36,111.46,111.88,111.76,111.28,111.97,112.05,112.1,112.25,111.69,11128,111.87,111.85,111.98,111.77,111.8,111.77,111.8,111.78,111.72,111.78,111.72,111.47,111.72,111.47,1112.01,111.47,112.01,112.22,112.01,112.22,112.01,112.22,112.95，112.06,111.87,1112.02,111.63,111.95,112.08,112,111.48,112.11,111.5,111.85,112.03,111.87,111.53,111.8,111.73,111.44），W_stdev = C（5.02,4.5,4.62,3.9,4.31,4.71 ，3.89,4.59,4.24,4.08,4.19,3.66,3.66,3.93,3.79,3.62,3.67,3.74,3.4,3.74,3.3,3.34,2.98,3.69,3.55,3118,31.12,3.28,3.58,3.57,3.81 , 3.14, 3.45, 3.59, 3.81, 3.82, 3.22, 3.37, 3, 3.09, 3.07, 2.96, 2.86, 2.83, 2.72, 2.91, 2.77, 3.17, 3.57, 3.11, 3, 3, 3.6, 3.14, 3..9 ，3.21,2.99,3.39,2.99,3.39,3.41,3.12,3.39,3.09,3.16,3.22,2.79,3.02,3.27,4.09,3.02,3.15,2.98,3.13,3.3,3.07,3.07,3.26,3.15,3.35 , 3.23, 3.47, 3.65, 2.79, 2.78, 3.3, 3.08, 2.91, 2.76, 2.91, 3.05, 3.24, 3.28, 2.84, 2.76, 2.72, 2.97, 3.44, 2.75, 2.96, 3.11, 3.18, 2.96, 3.18, .74, 2.89, 3.51, 3.54, 3.75, 3.36, 3.73, 3.34, 3.64, 3.81, 3.27, 3.87, 3.62, 3.8, 3.36, 3.25, 3.41, 3.33, 3.52, 3.57, 3.76, 3.57, 3.76, 3.57, 3.76, 3.57 3.14,3.53,3.26,3.38,4.39,3.13,3.18,3.13,3.61,3.72,3.47,3.52,3.77,3.26,3.55,3.98,3.63,3.54,3.47,3.42,3.33,3.73,3.04,3.51,3.04， 3.63, 2.98, 3.22, 3.47, 3.62, 3.74, 2.9, 4.18), T_STDEV = c(4.61, 3.67, 4.7, 3.29, 4.41, 3.68, 3.19, 3.56, 3.19, 3.43, 2.14, 2.3, 3.5, 3.14, 2.3, 3, 3 , 2.78, 2.65, 2.56, 2.75, 2.84, 2.52, 2.66, 2.56, 2.56, 2.47, 2.39, 2.61, 2.44, 2.62, 2.4, 2.46, 2.28, 2.39, 2.5, 2.3, 2.4, 2.4, 2.4, 2.4,. ，2.38,2.28,2.32,2.36,2.39,2.13,2.18,2.56,2.44,2.23,2.8,2.41,2.19,2.59,2.44,2.58,2.49,2.28,2.37,2.35,2.28,2.47,2.25,2.3,2.47,2.25,2.71,2.33 , 2.42, 2.58, 2.14, 2.4, 2。48, 3.08, 2.33, 2.33, 2.36, 2.33, 2.53, 2.51, 2.62, 2.6, 2.45, 2.51, 2.55, 2.67, 2.81, 2.32, 2.2, 2.59, 2.53, 2.28, 2.27,,, 2.49, 2.49, 2.49 2.49,2.35,2.37,2.57,2.85,2.4,2.77,2.98,2.45,2.67,2.56,3.15,2.74,2.87,2.96,3.41,3.04,3.25,3.02,3.49,3.42,2.97,3.66,3.46,3.62， 3.22、3.16、3.41、3.26、3.35、3.34、3.79、3.65、3.53、3.09、2.95、3.1、3.2、3.04、3.33、4.14、3.01、2.92、3.07、3.31、6、3.77、8、3... 3.31, 4.18, 3.74, 3.6, 3.4, 3.34, 3.23, 3.58, 3.02, 3.27, 2.97, 3.68, 2.92, 3.31, 3.36, 3.52, 3.69, 3.51, 4.27), COUNT = c(117, 457, 1) , 163, 159, 164, 170, 171, 170, 168, 170, 163, 166, 172, 173, 173, 166, 173, 163, 177, 174, 175, 173, 175, 170, 165, 172, 175 , 176, 174, 175, 174, 168, 174, 171, 174, 175, 176, 170,171, 168, 171, 165, 171, 170, 170, 174, 173, 174, 158, 170, 168, 170, 168, 169, 174, 171, 166, 168, 169, 172, 158, 163, 173, 167、172、167、169、168、166、165、171、158、158、170、174、173、169、164、168、174、168、169、170、174、174、171、159、161、 169, 163, 169, 169, 164, 172, 171, 164, 170, 165, 161, 162, 165, 163, 166, 169, 173, 168, 169, 165, 169, 166, 163, 170, 171, 172, 169, 169, 166, 163, 168, 166, 168, 168, 172, 171, 172, 168, 172, 164, 169, 169, 170, 172, 171, 167, 161, 166, 170, 170, 172, 169, 173, 160, 168, 161, 171, 173, 171, 166, 158, 170, 167, 166, 169, 169, 159, 160, 157, 150, 159, 146, 88), POSCAT = c （“开始”，“开始”，“开始”，“开始”，“开始”，“开始”，“开始”，“开始”，“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始” "、"开始"、"开始"、"开始"、"开始"、"开始"、"开始"、"开始"、"开始"、"开始"、"开始"、"开始"、"开始"、 “开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“开始”、“中间”、“中间”、“中间”、“中间”、“中间”、“中间” ”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中” “, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中” ", "中间", "中间", "中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中”、“中” , “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”, “中”、“中”、“中”、“中”、“中”、“尾”、“尾”、“尾”、“尾”、“尾”、“尾”、“尾”、“尾” 、“结束”、“结束”、“结束”、“结束”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END” 、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“ END", "END", "END", "END", "END", "END")), .Names = c("POSITION", "W_MEAN", "T_MEAN", "W_STDEV", "T_STDEV", "COUNT", "POSCAT"), row.names = c(NA, 163L), class = "data.frame")END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END” ，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”）） , .Names = c("POSITION", "W_MEAN", "T_MEAN", "W_STDEV", "T_STDEV", "COUNT", "POSCAT"), row.names = c(NA, 163L), class = "data 。框架”）END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END” ，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”，“END”）） , .Names = c("POSITION", "W_MEAN", "T_MEAN", "W_STDEV", "T_STDEV", "COUNT", "POSCAT"), row.names = c(NA, 163L), class = "data 。框架”）END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END” , "END")), .Names = c("POSITION", "W_MEAN", "T_MEAN", "W_STDEV", "T_STDEV", "COUNT", "POSCAT"), row.names = c(NA, 163L ), class = "data.frame")END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END”、“END” , "END")), .Names = c("POSITION", "W_MEAN", "T_MEAN", "W_STDEV", "T_STDEV", "COUNT", "POSCAT"), row.names = c(NA, 163L ), class = "data.frame")名称= c（NA，163L），类=“data.frame”）名称= c（NA，163L），类=“data.frame”）