Customizing the Legend Labels in ggord

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In this article, we will explore how to change the order of legend labels in the ggord function from R. The ggord function is used to plot the results of linear discriminant analysis (LDA), and it provides a legend that lists the model output in alphabetical order by default.

Understanding the Legend Labels

The legend labels in ggord are based on the factor levels extracted from the LDA model. The levels argument is used to specify the level names for each factor, but this does not allow us to change the order of the legend labels directly.

Exploring Alternatives

As mentioned in the question, one possible approach would be to reorder the factors using factors(x, levels=c()). However, since ggord reads the legend labels from the LDA model output, this approach may not work for all cases.

Using Custom Legend Labels

One alternative solution is to use custom legend labels. This can be achieved by defining a vector of custom label names and passing it to the vec_lab argument in the ggord function.

Example Code

library(ggord)
library(RColorBrewer)

# Define the custom label vector
vec_lab <- c("State 1", "State 2", "State 3")

# Plot the LDA model using ggord
ggord(ldamod2, av.nonna2$state, size=2, cols=c(high.col, low.col, medium.col),
      arrow=0.2, txt=3, vec_lab=vec_lab, grp_title="Emission State",
      max.overlaps = 8, repel=TRUE, ext=1) +
  theme(legend.position='right')+
  labs(title = "Nov 2018 - Dec 2019")+
  theme(plot.title = element_text(hjust = 0.5)) +
  annotate("text", x=-3.1, y=3.7, label= "b", col="grey30")

In this example, we define a custom vector vec_lab that contains the desired order of legend labels. We then pass this vector to the vec_lab argument in the ggord function.

Using ggplot2 for Custom Legend Labels

Another approach is to use ggplot2 instead of ggord. ggplot2 provides more flexibility when it comes to customizing legend labels. We can create a custom label vector and pass it to the scale_factor argument in the labs function.

Example Code

library(ggplot2)

# Define the custom label vector
vec_lab <- c("State 1", "State 2", "State 3")

# Plot the LDA model using ggplot2
p <- ggplot(lda_model, aes(x=state)) +
  geom_bar(stat='count', fill=high.col) +
  labs(title = "Nov 2018 - Dec 2019",
       x = "State", y = "Count",
       scale_x_names = vec_lab)

# Print the plot
print(p)

In this example, we define a custom label vector vec_lab that contains the desired order of legend labels. We then pass this vector to the scale_x_names argument in the labs function.

Conclusion

Changing the order of legend labels in ggord requires some creativity and flexibility when it comes to customizing the plot. By using custom label vectors or switching to ggplot2, we can achieve the desired result. Whether you choose to use ggord or ggplot2, there are ways to customize your plots and make them more informative.

Additional Tips

When working with large datasets, consider using dplyr for data manipulation.
Use knitr to create interactive documents that include visualizations.
Experiment with different visualization techniques to find the most effective way to communicate your results.

References

Last modified on 2023-07-02