Ploting正确的颜色与ggplot和geom_map

我呼吁区域这个数据帧：Ploting正确的颜色与ggplot和geom_map

     id   Growth interv color 
1    ALENTEJO CENTRAL 479.11 (475,500] yellow 
2    ALENTEJO LITORAL 530.23 (525, Inf] green4 
3      ALGARVE 470.91 (450,475] red 
4     ALTO ALENTEJO 499.72 (475,500] yellow 
5     ALTO MINHO 519.31 (500,525] green 
6     ALTO TÂMEGA 460.50 (450,475] red 
7 ÁREA METROPOLITANA DE LISBOA 494.05 (475,500] yellow 
8 ÁREA METROPOLITANA DO PORTO 497.15 (475,500] yellow 
9       AVE 484.41 (475,500] yellow 
10    BAIXO ALENTEJO 461.79 (450,475] red 
11     BEIRA BAIXA 511.19 (500,525] green 
12 BEIRAS E SERRA DA ESTRELA 503.52 (500,525] green 
13      CÁVADO 486.08 (475,500] yellow 
14      DOURO 509.93 (500,525] green 
15    LEZÍRIA DO TEJO 514.67 (500,525] green 
16     MÉDIO TEJO 504.39 (500,525] green 
17      OESTE 488.85 (475,500] yellow 
18     R. A. AÇORES 461.74 (450,475] red 
19    R. A. MADEIRA 490.16 (475,500] yellow 
20    REGIÃO DE AVEIRO 490.46 (475,500] yellow 
21   REGIÃO DE COIMBRA 502.82 (500,525] green 
22    REGIÃO DE LEIRIA 507.60 (500,525] green 
23    TÂMEGA E SOUSA 452.97 (450,475] red 
24  TERRAS DE TRÁS-OS-MONTES 454.03 (450,475] red 
25    VISEU DÃO LAFÕES 514.99 (500,525] green

，我试图用这个代码绘制在最后一栏的颜色地图（地区$颜色）：

niv_leg=c("<450","]450; 475]", "]475;500]","]500; 525]", ">525") 
colors = c("red4", "red", "yellow", "green", "green4") 

prtnutsiii = ggplot()+ 
    geom_polygon(data = mapaf, aes(x=long, y = lat, group = group), fill = NA, colour="darkgray", size=0.25)+ 
    coord_equal() 

growth = prtnutsiii + 
    geom_map(data = regional, map = mapaf, aes(map_id = id, fill = color),colour="darkgray", size = 0.25) + 
    theme(legend.title = element_blank()) 
    scale_fill_manual(values = colors,labels = niv_leg) 
pisamathg + theme(legend.position = "left")

我得到这个地图：

但我面临两个问题，我不能数字出来：

我只得到4个标签图例（他们应该是5）
颜色不正确ploted在所有不同的“ID”的区域...

的“身份证”在mapaf匹配区域数据框中的“id”，所以我不知道为什么它不工作...任何帮助将不胜感激。

PS：SHP文件（mapaf）我使用的是在这里：https://dl.dropboxusercontent.com/u/112525/mapaf.txt

这是dput（地区）：

structure(list(id = c("ALENTEJO CENTRAL", "ALENTEJO LITORAL", 
"ALGARVE", "ALTO ALENTEJO", "ALTO MINHO", "ALTO TÂMEGA", "ÁREA METROPOLITANA DE LISBOA", 
"ÁREA METROPOLITANA DO PORTO", "AVE", "BAIXO ALENTEJO", "BEIRA BAIXA", 
"BEIRAS E SERRA DA ESTRELA", "CÁVADO", "DOURO", "LEZÍRIA DO TEJO", 
"MÉDIO TEJO", "OESTE", "R. A. AÇORES", "R. A. MADEIRA", "REGIÃO DE AVEIRO", 
"REGIÃO DE COIMBRA", "REGIÃO DE LEIRIA", "TÂMEGA E SOUSA", "TERRAS DE TRÁS-OS-MONTES", 
"VISEU DÃO LAFÕES"), MATHMEAN = c(479.11, 530.23, 470.91, 499.72, 
519.31, 460.5, 494.05, 497.15, 484.41, 461.79, 511.19, 503.52, 
486.08, 509.93, 514.67, 504.39, 488.85, 461.74, 490.16, 490.46, 
502.82, 507.6, 452.97, 454.03, 514.99), interv = structure(c(3L, 
5L, 2L, 3L, 4L, 2L, 3L, 3L, 3L, 2L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 
2L, 3L, 3L, 4L, 4L, 2L, 2L, 4L), .Label = c("[-Inf,450]", "(450,475]", 
"(475,500]", "(500,525]", "(525, Inf]"), class = "factor"), color = structure(c(3L, 
5L, 2L, 3L, 4L, 2L, 3L, 3L, 3L, 2L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 
2L, 3L, 3L, 4L, 4L, 2L, 2L, 4L), .Label = c("red4", "red", "yellow", 
"green", "green4"), class = "factor")), .Names = c("id", "MATHMEAN", 
"interv", "color"), row.names = c(NA, -25L), class = "data.frame")

来源

2016-08-24 JPMD

尝试'scale_fill_identity（）' – hrbrmstr

你应该也真的简化了多边形。这是一个高层次的choropleth，你会加快渲染 – hrbrmstr

谢谢hrbrmstr。添加'scale_fill_identity（）'给我正确的颜色。但是我放松了定制的传说...会看看帮助，看看是否有解决方法？我确实使用'fortify'来简单地显示地图数据......你是指别的东西？ – JPMD

尝试增加：

names(colors) <- niv_leg

之前致电ggplot。如果没有名字，映射顺序可能会不同，这就是导致你问题的原因（我相信）。我也会尝试运行它，而不是先设置标签以确保它们按照相同的顺序进行。

如果您添加代码以读取您的数据（例如，使用dput）以及如何加载/准备shapefile，我可以直接使用解决方案。

来源

2016-08-24 18:19:54

感谢您的快速回复马克。我将添加输入 – JPMD

从此文件加载形状文件：https://dl.dropboxusercontent.com/u/112525/PRT__NUTS_ALL.shp，此代码为'mapa <-readShapeSpatial（file。选择（））'然后'地图@数据$ ID = $区域ID mapaf =设防（地图，区域=“ID”）' – JPMD

@JPMD甚至更好，有几个正方形模拟这个或使用的数据集自带与R在一个最小的，可重现的例子。 –

继@hrbrmstr的建议，我相信我有一个工作的解决方案：添加

scale_fill_identity("Média", labels = niv_leg, breaks = colors, 
        guide = "legend")

的geo_map(...)

后某处谢谢大家的反馈。我只是想知道为什么scale_fill_manual弄乱了颜色...我想这是解释颜色作为一个因素，而不是真正的颜色名称...

来源

2016-08-24 20:57:37 JPMD

Ploting正确的颜色与ggplot和geom_map

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