Improving Data Presentation: Using ggplot To Visually Present Tabular Data

A well-constructed plot can be more effective than a table in communicating key points of what authors seem to communicate about their data. This is especially true for showing comparisons or trends.

Below we demonstrate how to take information from a table and depict it in a plot using ggplot2.

The example is from Bergin, A. E. (1991). Values and religious issues in psychotherapy and mental health. American Psychologist, 46(4), 394-403. We used Table 2, Religious Preferences of Professional Groups Versus The Public At Large.

We started by putting the data from Table 2 into a .csv file in Excel. We then uploaded the data into R and named the dataset “Spirituality”.

Spirituality <- read.csv("~/Desktop/Percent_Professionals.csv")

We viewed the data using the head() and tail() functions to make sure it looked like we wanted it to.

head(Spirituality)

##       Religion Prof Percent
## 1   Protestant  MFT      49
## 2       Jewish  MFT      12
## 3     Catholic  MFT      14
## 4 Nonreligious  MFT      15
## 5        Other  MFT       9
## 6   Protestant   SW      40

tail(Spirituality)

##        Religion    Prof Percent
## 25        Other   Total       8
## 26   Protestant General      57
## 27       Jewish General       2
## 28     Catholic General       2
## 29 Nonreligious General       9
## 30        Other General       4

And we created factors to re-order the variables so they matched the order in Table 2.

Spirituality$Prof2 <- factor(Spirituality$Prof, c("MFT", "SW", "Psychiatrist", 
    "Psychologist", "Total", "General"))
Spirituality$Religion2 <- factor(Spirituality$Religion, c("Protestant", "Jewish", 
    "Catholic", "Nonreligious", "Other"))

We opened the packages ggplot2 and RColorBrewer. (If you haven't installed these packages before, you'll need to do that first.)

library(ggplot2)
library("RColorBrewer")

And now to the fun part! We used the code below to plot the Spirituality data. You will see that we used geom_point and geom_line to specify the type of plot we wanted (i.e., a scatterplot with lines connecting each point).

We did the following:

• Increased the size of the points
• Set the aesthetics of lines so they connected based on religous groups
• Changed the background to black and white and font size to 14 for visual clarity
• Rotated the axis of the labels
• Changed the titles of the labels for the x-axis and the legend
• Used the scale_color_brewer() function to change the color palette

## Make Plot
ggplot(data = Spirituality, aes(x = Spirituality$Prof2, y = Percent, color = Spirituality$Religion2)) + 
    geom_point(size = 3) + geom_line(aes(group = Spirituality$Religion2), names.arg = (c)) + 
    theme_bw(14) + theme(axis.text.x = element_text(angle = -45, hjust = 0)) + 
    labs(x = "Mental Health Professionals vs. General Population", color = "Religious Preference") + 
    scale_color_brewer(palette = "Set1")

We hope this was helpful for all of you. Happy plotting and good luck!