Centering Stacked Percent Bar Chart Labels: A Deep Dive into ggplot2

In recent years, data visualization has become an essential tool for communicating insights and trends in various fields. One common type of chart used for displaying categorical data is the stacked bar chart. When creating a stacked bar chart with percentages, it’s often desirable to include labels that provide context about each category. However, centering these labels within the bars can be challenging.

In this article, we’ll explore how to center stacked percent bar chart labels using ggplot2. We’ll cover the necessary steps, including calculating positions for text labels, determining which categories should have labels, and avoiding overlapping labels. By following these guidelines, you’ll be able to create well-structured and informative visualizations that effectively communicate your data insights.

Understanding Stacked Bar Charts

Before diving into label placement, it’s essential to understand how stacked bar charts work. In a stacked bar chart, multiple categories are displayed on top of each other, creating a layered effect. The height of each segment represents the value for that particular category. When using percentages, the height is scaled to represent a proportion of the total.

The Challenge with Centering Labels

When trying to center labels within stacked bars, two main issues arise:

1. Label Overlap: As the number of categories increases, so does the likelihood of overlapping labels. This can make it difficult for viewers to understand the data.
2. Label Positioning: Even if you manage to place labels in a way that minimizes overlap, positioning them within the bars can be tricky.

Calculating Positions for Text Labels

To avoid label overlap and ensure proper placement within the bars, we need to calculate their positions. One common approach is to use the cumulative sum of the values in each bar segment, which helps center the labels.

Here’s how you can do it using ggplot2 version 2 or later:

ggplot(df.summary, aes(x=reorder(Brand, USD, function(x) + sum(x)), y=percent, fill=Category)) +
  geom_bar(stat="identity", width = .7, colour="black", lwd=0.1) +
  geom_text(aes(label=ifelse(percent >= 0.07, paste0(sprintf("%.0f", percent*100),"%"),""),
                position=position_stack(vjust=0.5), colour="white") +
  coord_flip() +
  scale_y_continuous(labels = percent_format()) +
  labs(y="", x="")

In this code snippet:

• We use position_stack with a vjust value of 0.5 to center the labels vertically.
• The ifelse statement determines whether to display a label for each category based on its percentage value.

Handling Older Versions of ggplot2

If you’re using an older version of ggplot2, you’ll need to calculate the position manually. Here’s how:

# Calculate percentages and label positions
df.summary = df %>% group_by(Brand, Category) %>% 
  summarise(USD = sum(USD)) %>%   # Within each Brand, sum all values in each Category
  mutate(percent = USD/sum(USD),
         pos = cumsum(percent) - 0.5*percent)

ggplot(df.summary, aes(x=reorder(Brand,USD,function(x)+sum(x)), y=percent, fill=Category)) +
  geom_bar(stat='identity',  width = .7, colour="black", lwd=0.1) +
  geom_text(aes(label=ifelse(percent >= 0.07, paste0(sprintf("%.0f", percent*100),"%"),""),
                y=pos), colour="white") +
  coord_flip() +
  scale_y_continuous(labels = percent_format()) +
  labs(y="", x="")

In this code snippet:

• We calculate the position of each label using cumsum and subtract half of its value to center it.
• The rest of the code remains the same.

Avoiding Overlapping Labels

To avoid overlapping labels, we can use a threshold percentage. In this case, let’s assume that labels for categories with percentages less than 7% shouldn’t be displayed. We’ll add an ifelse statement to achieve this:

ggplot(df.summary, aes(x=reorder(Brand, USD, function(x) + sum(x)), y=percent, fill=Category)) +
  geom_bar(stat="identity", width = .7, colour="black", lwd=0.1) +
  geom_text(aes(label=ifelse(percent >= 0.07, paste0(sprintf("%.0f", percent*100),"%"),""),
                position=position_stack(vjust=0.5), colour="white") +
  coord_flip() +
  scale_y_continuous(labels = percent_format()) +
  labs(y="", x="")

In this code snippet:

• The ifelse statement checks if the percentage is greater than or equal to 7%. If true, it displays the label; otherwise, an empty string ("") is used.

Conclusion

Creating stacked bar charts with percentages can be a useful way to display categorical data. By following the steps outlined in this article, you’ll be able to center your labels and avoid overlapping issues. Remember to consider the threshold percentage when determining which categories should have labels displayed. With practice and patience, you’ll become proficient in creating informative and visually appealing visualizations using ggplot2.

Last modified on 2023-07-03