R 带条件的几何点颜色分配_R_Ggplot2_Colors

R 带条件的几何点颜色分配

r colors

R 带条件的几何点颜色分配,r,ggplot2,colors,R,Ggplot2,Colors,我有以下和平的准则： ggplot(data = afirmaciones[afirmaciones$prueba==x, ], aes(x = 1, y = Afirmacion_d)) + geom_point(size = 20, stroke = 5, aes(col

我有以下和平的准则：

ggplot(data = afirmaciones[afirmaciones$prueba==x,
                                     ], 
                 aes(x = 1, 
                     y = Afirmacion_d)) +
    geom_point(size = 20, 
               stroke = 5,
               aes(color = porcentaje),
               show.legend = F) + facet_wrap(~agregacion) +
    geom_text(aes(label = porcentaje),
              color = "white",
              size = 8) +
    theme(
      panel.background = element_rect(color = "#575756",
                                      size = 1.1,
                                      linetype = "solid",
                                      fill = "white"),
      panel.grid.major.y = element_line(size = 0.1,
                                        linetype = "dotted",
                                        color = "#575756"),
      axis.title = element_blank(),
      axis.text.x = element_blank(),
      strip.background = element_rect(fill = "white"),
      strip.text = element_text(colour = "#575756",
                                size = 20),
      axis.text.y = element_text(color = "#575756",
                                 size = 22)
    )

返回以下绘图：

我想根据变量“porcentaje”的数量给每个气泡上色。然而，我有一些特定的颜色在头脑中，我想气泡是彩色的，如果变量“porcentaje”落入一个特定的间隔。我想到的第一件事是生成一个变量“colors”，如果变量跟随变量，则该变量具有相同的颜色，然后使用

scale\u color\u手动（values=afirmaciones[afirmaciones$prueba==x，“colors”]）

将其添加到最后，但它不起作用。每种颜色的条件如下所示：

afirmaciones$colores <- NA
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje < 20,"colores"] <-  "#74ad68"
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje > 20 &
               afirmaciones$porcentaje < 40,"colores"] <-  "#e0e165"
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje > 40 &
               afirmaciones$porcentaje < 70,"colores"] <-  "#de9452"
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje > 70,"colores"] <-  "#cb4c43"

afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje < 20,"colores"] <-  "#74ad68"
afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje > 20 &
               afirmaciones$porcentaje < 40,"colores"] <-  "#e0e165"
afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje > 40 &
               afirmaciones$porcentaje < 70,"colores"] <-  "#de9452"
afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje > 70,"colores"] <-  "#cb4c43"

afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje<=-5,"colores"] <- "#74ad68"

afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje>-5 &
               afirmaciones$porcentaje<=-0.1,"colores"] <- "#e0e165"

afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje>-0.1 &
               afirmaciones$porcentaje<=4.9,"colores"] <- "#de9452"
afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje>5,"colores"] <- "#cb4c43"

亲切问候。

这有点老套，但我认为这正是您所要寻找的（以

prueba==“ensamblaje”

为例）：

pal40&afirmaciones$porcentaje<70~“#de9452”，
正确~“#cb4c43”
)
ggplot（数据=afirmaciones[afirmaciones$prueba==“ensamblaje”，
], 
aes（x=1，
y=一个单位（单位：d））+
几何点（尺寸=20，
冲程=5，
aes（颜色=玻璃钢），
show.legend=F）+facet_wrap（~agregacion）+
比例\颜色\手动（值=pal，限制=pal）+
geom_文字（aes（标签=瓷器），
color=“白色”，
尺寸=8）+
主题(
panel.background=element_rect（color=“#575756”，
尺寸=1.1，
linetype=“solid”，
fill=“white”），
panel.grid.major.y=元素线（尺寸=0.1，
linetype=“虚线”，
color=“#575756”），
axis.title=元素_blank（），
axis.text.x=元素_blank（），
strip.background=element_rect（fill=“white”），
strip.text=element_text（color=“#575756”，
尺寸=20），
axis.text.y=元素_文本（color=“#575756”，
尺寸=22）
)

（通过更合适的缩放级别/更好的打印大小，圆圈看起来更像您想要的样子）

在

afirmaciones$prueba==x

中

x是什么？

无法复制您的代码，但我认为问题是

scale\u color\u manual

应该是

scale\u color\u identity

我同意。x应该是“prueba”的每一个类别。在图中复制的示例是

x=“razonamiento”

。您的代码似乎很好。但是，“Diferencia”的颜色不正确，因为该类别的条件不同于其余两个类别。我试图将此条件添加到您的代码中，但我无法这样做。你能帮我吗？

structure(list(agregacion = structure(c(2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L), .Label = c("SENA", "Nacional", "Diferencia"), class = "factor"), 
    Afirmacion_d = structure(c(12L, 12L, 11L, 11L, 10L, 10L, 
    9L, 9L, 8L, 8L, 7L, 7L, 6L, 6L, 12L, 12L, 3L, 3L, 2L, 2L, 
    1L, 1L, 11L, 11L, 10L, 10L, 9L, 9L, 8L, 8L, 7L, 7L, 6L, 6L, 
    5L, 5L, 4L, 4L, 12L, 12L, 11L, 11L, 10L, 10L, 12L, 12L, 11L, 
    11L, 12L, 12L, 11L, 11L, 12L, 12L, 11L, 11L, 10L, 10L, 12L, 
    11L, 10L, 9L, 8L, 7L, 6L, 12L, 3L, 2L, 1L, 11L, 10L, 9L, 
    8L, 7L, 6L, 5L, 4L, 12L, 11L, 10L, 12L, 11L, 12L, 11L, 12L, 
    11L, 10L), .Label = c("Afirmación 12", "Afirmación 11", "Afirmación 10", 
    "Afirmación 9", "Afirmación 8", "Afirmación 7", "Afirmación 6", 
    "Afirmación 5", "Afirmación 4", "Afirmación 3", "Afirmación 2", 
    "Afirmación 1"), class = "factor"), prueba = c("competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "lectura", "lectura", "lectura", "lectura", 
    "lectura", "lectura", "mantenimiento", "mantenimiento", "mantenimiento", 
    "mantenimiento", "promoción", "promoción", "promoción", "promoción", 
    "razonamiento", "razonamiento", "razonamiento", "razonamiento", 
    "razonamiento", "razonamiento", "competencias", "competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "lectura", 
    "lectura", "lectura", "mantenimiento", "mantenimiento", "promoción", 
    "promoción", "razonamiento", "razonamiento", "razonamiento"
    ), porcentaje = c("51", "53", "51", "52", "61", "62", "57", 
    "58", "47", "49", "55", "56", "48", "49", "61", "61", "49", 
    "50", "47", "48", "60", "60", "64", "65", "50", "50", "55", 
    "55", "61", "62", "41", "42", "38", "39", "36", "36", "50", 
    "50", "53", "54", "43", "43", "53", "54", "54", "55", "49", 
    "50", "50", "51", "45", "44", "48", "49", "63", "64", "57", 
    "57", "2", "1", "1", "1", "2", "1", "1", "0", "1", "1", "0", 
    "1", "0", "0", "1", "1", "1", "0", "0", "1", "0", "1", "1", 
    "1", "1", "-1", "1", "1", "0"), colores = c("#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#e0e165", "#cb4c43", "#e0e165", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#e0e165", "#de9452", "#de9452", 
    "#de9452")), row.names = c("56772", "76081", "56752", "76086", 
"56771", "76085", "56781", "76080", "56775", "76083", "56753", 
"76084", "59239", "76082", "59235", "76108", "59236", "76107", 
"56776", "76103", "56754", "76099", "56749", "76104", "59238", 
"76100", "56764", "76106", "59240", "76102", "56763", "76098", 
"56755", "76105", "56760", "76101", "59237", "76097", "56777", 
"76088", "56773", "76089", "56761", "76087", "56750", "76095", 
"56765", "76096", "56779", "76093", "56778", "76094", "56757", 
"76090", "56756", "76091", "56766", "76092", "760811", "760861", 
"760851", "760801", "760831", "760841", "760821", "761081", "761071", 
"761031", "760991", "761041", "761001", "761061", "761021", "760981", 
"761051", "761011", "760971", "760881", "760891", "760871", "760951", 
"760961", "760931", "760941", "760901", "760911", "760921"), class = "data.frame")