在分面ggplot中绘制排序值

我无法使用ggplot2绘制每个面内的排序值。在分面ggplot中绘制排序值

这里是样地 enter image description here

ggplot(data=df) + 
    geom_point(aes(y=log(count_neg,10), x= ref_name, colour=replicate)) +    
    facet_grid(condition ~ sub_groups)

我想要做的是那种由Y值每个面点。我尝试以下，但它没有工作：

ggplot(data=df) + 
    geom_point(aes(sort(y=log(count_neg,10),decreading=TRUE), 
        x= ref_name, colour=replicate)) + 
    facet_grid(condition ~ sub_groups)

原始数据在这里：

df<-structure(list(condition = structure(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, 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, 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, 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), .Label = c("N_0m", "N_10m", "N_1h", "N_24h", "N_2h", 
"N_30m", "N_48h", "N_6h", "N_8h"), class = "factor"), replicate = structure(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, 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, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", "B"), class = "factor"), 
    ref_name = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
    10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 
    22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 
    34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 
    46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 
    58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 
    70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L, 81L, 
    82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 1L, 
    2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
    15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 
    27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 
    39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 
    51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 
    63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 
    75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 
    87L, 88L, 89L, 90L, 91L, 92L), .Label = c("ERCC-00002", "ERCC-00003", 
    "ERCC-00004", "ERCC-00009", "ERCC-00012", "ERCC-00013", "ERCC-00014", 
    "ERCC-00016", "ERCC-00017", "ERCC-00019", "ERCC-00022", "ERCC-00024", 
    "ERCC-00025", "ERCC-00028", "ERCC-00031", "ERCC-00033", "ERCC-00034", 
    "ERCC-00035", "ERCC-00039", "ERCC-00040", "ERCC-00041", "ERCC-00042", 
    "ERCC-00043", "ERCC-00044", "ERCC-00046", "ERCC-00048", "ERCC-00051", 
    "ERCC-00053", "ERCC-00054", "ERCC-00057", "ERCC-00058", "ERCC-00059", 
    "ERCC-00060", "ERCC-00061", "ERCC-00062", "ERCC-00067", "ERCC-00069", 
    "ERCC-00071", "ERCC-00073", "ERCC-00074", "ERCC-00075", "ERCC-00076", 
    "ERCC-00077", "ERCC-00078", "ERCC-00079", "ERCC-00081", "ERCC-00083", 
    "ERCC-00084", "ERCC-00085", "ERCC-00086", "ERCC-00092", "ERCC-00095", 
    "ERCC-00096", "ERCC-00097", "ERCC-00098", "ERCC-00099", "ERCC-00104", 
    "ERCC-00108", "ERCC-00109", "ERCC-00111", "ERCC-00112", "ERCC-00113", 
    "ERCC-00116", "ERCC-00117", "ERCC-00120", "ERCC-00123", "ERCC-00126", 
    "ERCC-00130", "ERCC-00131", "ERCC-00134", "ERCC-00136", "ERCC-00137", 
    "ERCC-00138", "ERCC-00142", "ERCC-00143", "ERCC-00144", "ERCC-00145", 
    "ERCC-00147", "ERCC-00148", "ERCC-00150", "ERCC-00154", "ERCC-00156", 
    "ERCC-00157", "ERCC-00158", "ERCC-00160", "ERCC-00162", "ERCC-00163", 
    "ERCC-00164", "ERCC-00165", "ERCC-00168", "ERCC-00170", "ERCC-00171" 
    ), class = "factor"), count_neg = c(468869L, 34677L, 113226L, 
    23508L, 8655L, 9319L, 210L, 25675L, 928L, 53981L, 8878L, 
    22507L, 5880L, 11756L, 21688L, 95L, 2397L, 6553L, 2533L, 
    12714L, 110L, 13520L, 71598L, 3177L, 55453L, 4157L, 3391L, 
    2740L, 144203L, 52L, 10710L, 15576L, 22028L, 5328L, 42474L, 
    1906L, 2829L, 12753L, 1207L, 351477L, 28401L, 5523L, 1166L, 
    7515L, 2773L, 17744L, 757L, 16316L, 16855L, 1236L, 16087L, 
    5447L, 358290L, 29127L, 34571L, 159457L, 630L, 46067L, 5977L, 
    22835L, 4014L, 111972L, 12372L, 5396L, 8183L, 1293L, 210L, 
    734814L, 10174L, 12838L, 39742L, 4259L, 35927L, 801L, 16309L, 
    16153L, 133685L, 8209L, 4331L, 5319L, 6029L, 3074L, 4768L, 
    2274L, 4958L, 9128L, 7243L, 2946L, 14718L, 20577L, 11257L, 
    78889L, 2407687L, 116262L, 52712L, 47998L, 10892L, 10124L, 
    479L, 19437L, 1257L, 61059L, 31119L, 25751L, 10645L, 14689L, 
    20248L, 92L, 3168L, 11003L, 3396L, 16732L, 176L, 29809L, 
    77936L, 12340L, 155159L, 5336L, 3818L, 3127L, 163497L, 66L, 
    14612L, 12687L, 25586L, 6996L, 25554L, 2284L, 3667L, 15745L, 
    1444L, 1033128L, 20087L, 17619L, 1412L, 11946L, 8014L, 19551L, 
    978L, 24182L, 22125L, 1717L, 14514L, 4564L, 903132L, 33653L, 
    39776L, 173518L, 796L, 35684L, 6524L, 62638L, 14418L, 398893L, 
    7938L, 6422L, 10595L, 1563L, 572L, 370134L, 10825L, 13837L, 
    17794L, 5164L, 43831L, 1114L, 17244L, 18924L, 171171L, 10228L, 
    5789L, 6847L, 6467L, 3582L, 6834L, 3084L, 7450L, 12474L, 
    6399L, 2390L, 22084L, 20090L, 7961L, 192521L), sub_groups = structure(c(4L, 
    4L, 1L, 2L, 3L, 4L, 4L, 3L, 1L, 1L, 4L, 3L, 2L, 1L, 2L, 1L, 
    2L, 2L, 3L, 3L, 4L, 2L, 4L, 3L, 4L, 4L, 2L, 2L, 3L, 3L, 3L, 
    4L, 2L, 4L, 1L, 2L, 4L, 3L, 2L, 3L, 2L, 3L, 4L, 4L, 4L, 4L, 
    1L, 3L, 1L, 4L, 1L, 1L, 2L, 1L, 3L, 3L, 2L, 1L, 2L, 3L, 4L, 
    3L, 1L, 2L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 4L, 2L, 2L, 3L, 1L, 
    3L, 1L, 2L, 2L, 1L, 1L, 3L, 2L, 4L, 3L, 4L, 3L, 4L, 4L, 1L, 
    2L, 4L, 4L, 1L, 2L, 3L, 4L, 4L, 3L, 1L, 1L, 4L, 3L, 2L, 1L, 
    2L, 1L, 2L, 2L, 3L, 3L, 4L, 2L, 4L, 3L, 4L, 4L, 2L, 2L, 3L, 
    3L, 3L, 4L, 2L, 4L, 1L, 2L, 4L, 3L, 2L, 3L, 2L, 3L, 4L, 4L, 
    4L, 4L, 1L, 3L, 1L, 4L, 1L, 1L, 2L, 1L, 3L, 3L, 2L, 1L, 2L, 
    3L, 4L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 4L, 2L, 2L, 
    3L, 1L, 3L, 1L, 2L, 2L, 1L, 1L, 3L, 2L, 4L, 3L, 4L, 3L, 4L, 
    4L, 1L, 2L), .Label = c("A", "B", "C", "D"), class = "factor")), .Names = c("condition", 
"replicate", "ref_name", "count_neg", "sub_groups"), row.names = c(NA, 
184L), class = "data.frame")

来源

2012-07-23 Abhi

您的原始数据代码不起作用。 – 2012-07-23 21:17:21

@panda：现在试试..我已经删除了其他列，使其更紧凑。希望它适合你。 – Abhi 2012-07-23 21:30:07

另外我只是复制粘贴dput（df）..可能是格式化越来越乱了。 – Abhi 2012-07-23 21:35:59

试试这个：

df$ref_name <- reorder(df$ref_name,-log(df$count_neg,10))  

ggplot(data=df) + 
    geom_point(aes(y=log(count_neg,10), x= ref_name, colour=replicate)) +    
    facet_grid(condition ~ sub_groups)

，或者如果你想相反顺序省略减号。这会通过（全局）y值对x轴进行排序。如果您打算单独订购每个方面，那会稍微复杂一些，部分原因是因为它会使图表更加混乱。

来源

2012-07-23 22:43:19 joran

感谢编辑我的问题和修复df：1）请你帮我理解你是如何修复dput输出的。这将有助于未来。 2）重新排序后，我认为情节看起来更好，但我有一个问题。基于log（count_neg）的ref_name的全局重新排序是如何在一个方面级别得到纠正的。另外，如果我排序ggplot，aes部分中的值。它不以同样的方式工作。我想我对ggplot有关价值到审美的映射有些困惑。非常感谢 – Abhi 2012-07-23 23:15:30

（1）我所做的只是通过选择并单击“{}”按钮来格式化它，（2）可能是因为从面板到面板的排序相当一致，但如果仔细观察，您会看到（3）简单的算术变换在'aes'内部是非常安全的，但是一般来说你应该对数据帧进行修改。 – joran 2012-07-23 23:56:35

感谢..for 2）任何方式，我们可以在方面水平然后排序。我想确保每个方面严格按顺序排列。我尝试使用plyr，但力度工作。基本上我想通过（条件，复制，子组，count_neg）和count_neg按条件，复制，子组的降序排列数据帧......有意义吗？ – Abhi 2012-07-24 00:00:40

在分面ggplot中绘制排序值

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