Plot fitted data from data frame as side-by-side barplot - r

Question

I have a data frame that comes from a lm subset composed of the intercept (ordenada) and the slope (velocidad1) calculated for each subject.
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")
My goal is to get a barplot of the data in second row ( A[2,] ) splitting by group (UT which contains UT1,UT2... and TR) in the same graph. I am trying to do some ggplot but keep failing over and over again. I get no layers in plot error or margin error in base graphics.
The output should look like this
I KNOW the answer is in the reshape package but I wish there's another way to do that.
Thank you in advance.

Answer 1

Using base graphics:
# 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)))
Possibly add a legend:
legend("topright", legend = c("UT", "TR"), fill = c("blue", "red"))

Answer 2

EDIT: Not using reshape per request in comments
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")

Answer 3

Here is another option that incorporates your complete dataset. Not sure if this is usefull for you.
I've used reshape2, it's actually easier. You just have to melt(yourdataframe), for your particular case there is no need to specify anything else in the melt function arguments.
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$vble)))
ggplot(aes(y = value, x = vble, fill = group), data = df3) +
geom_bar(stat = "identity", position = "dodge") +
facet_grid(origen ~ ., scales = "free")
Using Functions
prepare <- function(data){
data1 <- melt(data[1,])
data1$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))
I guess you could loop in order to plot several data frames using the same plot function.
I guess you could probably addapt it more to your needs, but this can get you started