在许多图表中按因子设置特定的形状和颜色

Question

我对这个问题很沮丧，这可能有一个非常简单的答案。我有一个大型数据集（这里只显示一小部分），其中包含来自不同深度的不同深度的变量。在散点图中，我希望每个深度的形状和颜色在所有站点（图形）上都相同，即使某些站点（图形）没有来自每个深度的数据点。

更具体地说，我希望图A中的“深度30”为绿色方块，以匹配图B中的“深度30”，尽管图A在深度为20时没有数据点。整个数据集中的深度为0,20,30,60,90和120，如图A所示。有些图形具有4或5个深度的数据。

如何手动标准化图表中显示的颜色/形状？ 我尝试为每个站点添加占位符深度（每个图形），这导致我稍后应用的线性模型出错。我也尝试使用“scale_shape_manual”和“scale_color_manual”（根据这个答案中的说明：R manually set shape by factor），但在图表中仍然有相同深度的不同形状和符号。

这是我现有的代码：

holes_SO <- read.csv(file = 'holeflux_withsoil_r_for_SO.csv', sep = ",", header = TRUE)
ro_aue_SO <- subset(holes_SO, holes_SO$field == "ROA")
ot_slope_SO <- subset(holes_SO, holes_SO$field == "OTS")

ggplot(data = ro_aue_SO, aes(x = soc_concentration_kg_m3, y = co2_flux_µmol_c_m2_s1, color = factor(depth), shape = factor(depth))) +
  geom_point(size = 4) +
  labs(x = "SOC concentration", y = "CO2 Flux") +
  labs(color="Depth", shape= "Depth") +
  ggtitle(expression('RO Aue, CO'[2]*'')) +
  geom_smooth(aes(color = factor(depth)), method=lm, se=FALSE, formula=y~x-1, fullrange = TRUE)

ggplot(data = ot_slope_SO, aes(x = soc_concentration_kg_m3, y = co2_flux_µmol_c_m2_s1, color = factor(depth), shape = factor(depth))) +
  geom_point(size = 4) +
  labs(x = "SOC concentration", y = "CO2 Flux") +
  labs(color="Depth", shape= "Depth") +
  ggtitle(expression('OT Slope, CO'[2]*'')) +
  geom_smooth(aes(color = factor(depth)), method=lm, se=FALSE, formula=y~x-1, fullrange = TRUE)

这是我的数据的dput（），名为“holes_SO”：

structure(list(sample_id = structure(c(1L, 2L, 3L, 4L, 10L, 11L, 
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 
25L, 26L, 29L, 30L, 31L, 32L, 27L, 28L, 33L, 36L, 37L, 38L, 39L, 
34L, 35L, 5L, 6L, 7L, 8L, 9L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 
47L, 48L, 49L, 50L, 51L, 52L, 53L), .Label = c("OTS1-0", "OTS1-30", 
"OTS1-60", "OTS1-90", "OTS10-0", "OTS10-20", "OTS10-30", "OTS10-60", 
"OTS10-90", "OTS2-0", "OTS3-0", "OTS3-30", "OTS3-60", "OTS3-90", 
"OTS4-0", "OTS5-0", "OTS5-30", "OTS5-60", "OTS5-90", "OTS6-0", 
"OTS7-0", "OTS7-20", "OTS7-30", "OTS7-60", "OTS7-90", "OTS8-0", 
"OTS8-120A", "OTS8-120B", "OTS8-20", "OTS8-30", "OTS8-60", "OTS8-90", 
"OTS9-0", "OTS9-120A", "OTS9-120B", "OTS9-20", "OTS9-30", "OTS9-60", 
"OTS9-90", "ROA1-0", "ROA1-30", "ROA1-60", "ROA1-90", "ROA2-0", 
"ROA2-30", "ROA3-0", "ROA3-30", "ROA3-60", "ROA3-90", "ROA4-0", 
"ROA4-30", "ROA4-60", "ROA4-90"), class = "factor"), site = 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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L), .Label = c("OT", "RO"), class = "factor"), field = 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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L), .Label = c("OTS", "ROA"), class = "factor"), 
    hole_number = c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L, 4L, 5L, 
    5L, 5L, 5L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 
    8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 
    1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L), 
    depth = c(0L, 30L, 60L, 90L, 0L, 0L, 30L, 60L, 90L, 0L, 0L, 
    30L, 60L, 90L, 0L, 0L, 20L, 30L, 60L, 90L, 0L, 20L, 30L, 
    60L, 90L, 120L, 120L, 0L, 20L, 30L, 60L, 90L, 120L, 120L, 
    0L, 20L, 30L, 60L, 90L, 0L, 30L, 60L, 90L, 0L, 30L, 0L, 30L, 
    60L, 90L, 0L, 30L, 60L, 90L), co2_flux_µmol_c_m2_s1 = c(1.710293078, 
    0.30924686, 0.36469938, 0.227477037, 1.254479063, 0.752737414, 
    2.257215969, 11.50282226, 3.566654093, 0.69900321, 1.591361818, 
    13.92149665, 22.73002129, 22.45049, 1.109443533, 7.406644295, 
    7.855618003, 17.78010488, 6.471314337, 5.315970134, 6.347455312, 
    11.54719043, 10.11479135, 11.47752926, 2.805488908, 5.222756475, 
    4.377681384, 7.173613131, 14.51864231, 9.729229653, 4.564367185, 
    10.17710718, 7.70956059, 4.382202183, 3.321182297, 3.858269154, 
    7.542932281, 19.88469738, 10.55216436, 3.572542676, 6.530127468, 
    10.78088543, 12.82422246, 3.093747739, 6.956941294, 3.316715055, 
    8.781949843, 7.684561849, 6.142716566, 2.69743231, 9.67046938, 
    7.018872033, 9.475929618), soc_concentration_kg_m3 = c(16.57, 
    1.28, 1.86, 1.63, 16.88, 16.8, 6.59, 5.7, 1.33, 15, 15.67, 
    3.8, 3.95, 3.95, 17.17, 20.5, 21.1, 4.94, 4.27, 2.43, 14.9, 
    16.52, 4.12, 4.59, 4.59, 4.24, 4.24, 15.36, 15.93, 15.93, 
    7.14, 7.14, 3.87, 3.87, 19.21, 20.24, 6.45, 5, 4.85, 40, 
    7.78, 7.78, 3.6, 41.25, 23, 36.67, 23.04, 12.4, 3.33, 35.71, 
    9.66, 12.31, NA)), .Names = c("sample_id", "site", "field", 
"hole_number", "depth", "co2_flux_µmol_c_m2_s1", "soc_concentration_kg_m3"
), class = "data.frame", row.names = c(NA, -53L))

我很感激任何帮助！

Answer 1

如果您在下方添加标有#####的行，则会有效。如果在分割数据帧之前将holes设置为一个因子，则两个子集中的每一个都将保留全部因子级别。然后，您必须告诉ggplot不要在color和shape比例中删除未使用的因子级别。

holes_SO$depth <- factor(holes_SO$depth) ###############
ro_aue_SO <- subset(holes_SO, holes_SO$field == "ROA")
ot_slope_SO <- subset(holes_SO, holes_SO$field == "OTS")

ggplot(data = ro_aue_SO, aes(x = soc_concentration_kg_m3, y = co2_flux_µmol_c_m2_s1, color = depth, shape = depth)) +
  geom_point(size = 4) +
  labs(x = "SOC concentration", y = "CO2 Flux") +
  labs(color="Depth", shape= "Depth") +
  scale_color_discrete(drop=FALSE) + ##################
  scale_shape_discrete(drop=FALSE) + ##################
  ggtitle(expression('RO Aue, CO'[2]*'')) +
  geom_smooth(aes(color = depth), method=lm, se=FALSE, formula=y~x-1, fullrange = TRUE)

ggplot(data = ot_slope_SO, aes(x = soc_concentration_kg_m3, y = co2_flux_µmol_c_m2_s1, color = depth, shape = depth)) +
  geom_point(size = 4) +
  labs(x = "SOC concentration", y = "CO2 Flux") +
  labs(color="Depth", shape= "Depth") +
  scale_color_discrete(drop=FALSE) + ###################
  scale_shape_discrete(drop=FALSE) + ###################
  ggtitle(expression('OT Slope, CO'[2]*'')) +
  geom_smooth(aes(color = depth), method=lm, se=FALSE, formula=y~x-1, fullrange = TRUE)