将来自数据框的拟合数据绘制为并排条形图

时间：2014-04-17 20:19:22

标签： r ggplot2 bar-chart

我有一个来自lm子集的数据框，该子集由截距（ordenada）和为每个主题计算的斜率（velocidad1）组成。

 A
                  UT1    UT2          UT3      UT4
    ordenada   1213.8 2634.8 3.760000e+02 -11080.8
    velocidad1    1.5   -2.5 6.615954e-14     20.0
                  UT5          UT6           UT7
    ordenada   1711.8 1.739000e+03  1.800000e+01
    velocidad1   -2.5 5.039544e-14 -9.154345e-16
                  UT8   UT9   UT10  UT11   UT12
    ordenada   5659.2 -2791 3422.6 418.2 2802.2
    velocidad1   -6.0     5   -1.0  -0.5   -1.5
                       UT13   UT14      TR1     TR2
    ordenada   2.832000e+03 -411.2 -15722.0 -1105.4
    velocidad1 1.405114e-13    3.5     25.5    25.0
                        TR3   TR4    TR5          TR6
    ordenada    1.14600e+03 299.6 1943.4 6.840000e+02
    velocidad1 -5.11402e-14   2.0   -2.5 6.479414e-14
                 TR7           TR8     TR9    TR10
    ordenada   354.8  1.317000e+03 33284.6 -3742.6
    velocidad1   1.0 -3.475548e-14   -52.0     8.0
                        TR11   TR12    TR13
    ordenada    7.400000e+02 2205.4 -4542.6
    velocidad1 -8.018585e-14   -2.5     8.0
                        TR14
    ordenada    5.880000e+02
    velocidad1 -4.406498e-14


dput(A)
structure(list(UT1 = c(1213.79999999971, 1.50000000000047), UT2 = c(2634.80000000021, 
-2.50000000000033), UT3 = c(375.999999999959, 6.61595351840473e-14
), UT4 = c(-11080.8000000008, 20.0000000000013), UT5 = c(1711.80000000007, 
-2.50000000000012), UT6 = c(1738.99999999997, 5.03954433109254e-14
), UT7 = c(18.0000000000006, -9.15434469010036e-16), UT8 = c(5659.20000000026, 
-6.00000000000041), UT9 = c(-2791.00000000024, 5.00000000000039
), UT10 = c(3422.59999999968, -0.99999999999948), UT11 = c(418.199999999958, 
-0.499999999999932), UT12 = c(2802.20000000017, -1.50000000000028
), UT13 = c(2831.99999999991, 1.40511433073812e-13), UT14 = c(-411.200000000294, 
3.50000000000048), TR1 = c(-15722.0000000017, 25.5000000000028
), TR2 = c(-1105.40000000264, 25.0000000000043), TR3 = c(1146.00000000003, 
-5.11402035568996e-14), TR4 = c(299.599999999803, 2.00000000000032
), TR5 = c(1943.40000000013, -2.50000000000021), TR6 = c(683.99999999996, 
6.47941413997612e-14), TR7 = c(354.800000000011, 0.999999999999982
), TR8 = c(1317.00000000002, -3.47554781454658e-14), TR9 = c(33284.6000000025, 
-52.000000000004), TR10 = c(-3742.60000000058, 8.00000000000094
), TR11 = c(740.00000000005, -8.0185853149896e-14), TR12 = c(2205.40000000021, 
-2.50000000000034), TR13 = c(-4542.60000000042, 8.00000000000067
), TR14 = c(588.000000000027, -4.40649812201441e-14)), .Names = c("UT1", 
"UT2", "UT3", "UT4", "UT5", "UT6", "UT7", "UT8", "UT9", "UT10", 
"UT11", "UT12", "UT13", "UT14", "TR1", "TR2", "TR3", "TR4", "TR5", 
"TR6", "TR7", "TR8", "TR9", "TR10", "TR11", "TR12", "TR13", "TR14"
), row.names = c("ordenada", "velocidad1"), class = "data.frame")

我的目标是在同一图表中获得第二行（A [2，]）中按组分组的数据（包含UT1，UT2 ...和TR的UT）的条形图。我正在尝试做一些ggplot，但一直都在失败。基本图形中的绘图错误或边距错误没有任何图层。

输出应该如下所示

enter image description here

我知道答案是在重塑包中，但我希望还有另一种方法可以做到这一点。

提前谢谢。

3 个答案:

答案 0 :(得分：2)

使用base图片：

# convert the one-row data frame to a two-row matrix
m <- matrix(unlist(df[2, ]), nrow = 2, byrow = TRUE)

# plot
barplot(m, beside = TRUE, col = c("blue", "red"), names.arg = seq_len(ncol(m)))

enter image description here

可能添加一个图例：

legend("topright", legend = c("UT", "TR"), fill = c("blue", "red"))

答案 1 :(得分：1)

编辑：评论中每个请求未使用reshape 

library(ggplot2)
plot_data <- data.frame(names(A), t(A[2,]))
names(plot_data) <- c("variable", "value")
plot_data$group <- grepl("^TR", plot_data$variable)
plot_data$variable <- gsub("[^0-9]", "", as.character(plot_data$variable))
plot_data$variable <- factor(plot_data$variable, 
                             unique(sort(as.numeric(plot_data$variable))))
p <- ggplot(aes(y = value, x = variable, fill = group), data = plot_data)
p + geom_bar(stat = "identity", position = "dodge")

答案 2 :(得分：1)

这是包含完整数据集的另一个选项。不确定这对你有用。 我使用了reshape2，它实际上更容易。您只需要melt(yourdataframe)，对于您的特定情况，不需要在融合函数参数中指定任何其他内容。

require("ggplot2")
require("reshape2")

A <- df
df1 <- melt(df[1,])
df1$origen <- "ORDENADA"
df2 <- melt(df[2,])
df2$origen <- "VELOCIDAD"
identical(df1$variable,df2$variable)

df3 <- rbind(df1,df2)
df3$group <- ifelse(grepl("^TR", df3$variable) == TRUE, "TR", "UT")
df3$vble <- gsub("[^0-9]", "", as.character(df3$variable))
df3$vble <- factor(df3$vble, levels = as.numeric(unique(df3$vble)))

ggplot(aes(y = value, x = vble, fill = group), data = df3) +
  geom_bar(stat = "identity", position = "dodge") +
  facet_grid(origen ~ ., scales = "free")

enter image description here

使用函数

prepare <- function(data){
  data1 <- melt(data[1,])
  data1$origen <- "ORDENADA"
  data2 <- melt(data[2,])
  data2$origen <- "VELOCIDAD"
  identical(data1$variable,data2$variable)
  data3 <- rbind(data1,data2)
  data3$group <- ifelse(grepl("^TR", data3$variable) == TRUE, "TR", "UT")
  data3$vble <- gsub("[^0-9]", "", as.character(data3$variable))
  data3$vble <- factor(data3$vble, levels = as.numeric(unique(data3$vble)))
  return(data3)
}

prepare(df)

#This would work, but is a bit manual for many plots:

ggplot(aes(y = value, x = vble, fill = group), data = prepare(df)) +
      geom_bar(stat = "identity", position = "dodge") +
      facet_grid(origen ~ ., scales = "free")


plot_fun <- function(data){
  p <- ggplot(data, aes_string(x = "vble", y = "value", fill = "group"))
  p <- p + geom_bar(stat = "identity", position = "dodge")
  p <- p + facet_grid(origen ~ ., scales = "free")
  suppressWarnings(print(p))
}

plot_fun(prepare(df))

我猜你可以循环以便使用相同的绘图功能绘制几个数据帧。 我想你可能会更多地满足你的需求，但这可以让你开始

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