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rggplot2axis-labelsviolin-plot

Violin plot of ggplot2 is not in order as in dataset on x-axis

I created the violin plot using below code, But on the x-axis, Models name are not in order as in the data set (i.e. "Observed", "SVM", "Grid_SVM", "MARS", "Grid_Mars", "RF", "Grid_RF"). Where the edit is required in the code?

ggplot(df1, aes(x = Model, y = Pb), cex.lab = 18, cex.axis=18) +
  geom_violin(trim=FALSE, fill = "palegreen") +
  geom_boxplot(width = .12, fill = "orange", outlier.color = "orange", outlier.size = 2) + 
  labs(title = "Pb Adsorption distribution by Models over testing phase") + xlab("Models") + ylab("Pb Adsorption distribution")+ theme_classic() +
  theme(
  plot.title = element_text(size = 12, colour = "black", face = "bold"), #for Main Title
  axis.title.x = element_text(size = 12, colour = "black", face = "bold"), #for axix title
  axis.title.y = element_text(size = 12, colour = "black", face = "bold"),
  axis.text.x = element_text(face="bold", color="darkblue", size=12, angle=0), #for axis tick
  axis.text.y = element_text(face="bold", color="black", size=12, angle=0))
Solution

  • By default, ggplot2 plots character vectors in alphabetical order. To place a specified order to your plot, simply use dplyr and create the column as a factor() and specify the levels you desire. Then ggplot2 should plot it as you want.

    Edit #1 One way is to modify the df1 data frame separately from your string of ggplot2 commands. You can do this as

    df1 <- df1 %>%
  mutate( Model=factor(Model,levels=c("Observed", "SVM", "Grid_SVM", "MARS", "Grid_Mars", "RF", "Grid_RF")) )

    And then call your string of ggplot2 commands as you have posted above.

    Edit #2 (from comments below)

    If you want to pipe everything through and do everything in one shot, try

    df1 %>%
  mutate( Model=factor(Model,levels=c("Observed", "SVM", "Grid_SVM", "MARS", "Grid_Mars", "RF", "Grid_RF")) ) %>%
  ggplot( aes(x = Model, y = Pb), cex.lab = 18, cex.axis=18) +
  geom_violin(trim=FALSE, fill = "palegreen") +
  geom_boxplot(width = .12, fill = "orange", outlier.color = "orange", outlier.size = 2) + 
  labs(title = "Pb Adsorption distribution by Models over testing phase") + xlab("Models") + ylab("Pb Adsorption distribution")+ theme_classic() +
  theme(
  plot.title = element_text(size = 12, colour = "black", face = "bold"), #for Main Title
  axis.title.x = element_text(size = 12, colour = "black", face = "bold"), #for axix title
  axis.title.y = element_text(size = 12, colour = "black", face = "bold"),
  axis.text.x = element_text(face="bold", color="darkblue", size=12, angle=0), #for axis tick
  axis.text.y = element_text(face="bold", color="black", size=12, angle=0))

    The original suggestion was to overwrite the data. Then generate the plot in a new chain.

    df1 <- df1 %>%
  mutate( Model=factor(Model,levels=c("Observed", "SVM", "Grid_SVM", "MARS", "Grid_Mars", "RF", "Grid_RF")) )

ggplot( df1, aes(x = Model, y = Pb), cex.lab = 18, cex.axis=18) +
  geom_violin(trim=FALSE, fill = "palegreen") +
  geom_boxplot(width = .12, fill = "orange", outlier.color = "orange", outlier.size = 2) + 
  labs(title = "Pb Adsorption distribution by Models over testing phase") + xlab("Models") + ylab("Pb Adsorption distribution")+ theme_classic() +
  theme(
  plot.title = element_text(size = 12, colour = "black", face = "bold"), #for Main Title
  axis.title.x = element_text(size = 12, colour = "black", face = "bold"), #for axix title
  axis.title.y = element_text(size = 12, colour = "black", face = "bold"),
  axis.text.x = element_text(face="bold", color="darkblue", size=12, angle=0), #for axis tick
  axis.text.y = element_text(face="bold", color="black", size=12, angle=0))

    Either of the above will work.