Format Numbers as Percentages in R

Formatting numbers as percentages is a common task when working with numeric data in R, especially when the goal is to present results in a more readable and understandable manner. This is a versatile skill that can significantly enhance the presentation of your data, making it more accessible to varied audiences. In this comprehensive guide, we’ll explore different methods for achieving this in R.

Understanding Percentages

Percentages represent a part of a whole and are a way to express fractions, ratios, or proportions out of 100. Representing numbers as percentages can make data more relatable and easily comparable, particularly when working with varying scales or magnitudes.

1. Basic Formatting using scales Library

The scales library in R provides a convenient percent() function to format numeric vectors as percentages effortlessly. The percent() function is versatile, allowing for adjustments like controlling the number of decimal places.

library(scales)

values <- c(0.123, 0.555, 0.879)

# Formatting with one decimal place
formatted_values_one_decimal <- percent(values, accuracy = 0.1)

# Formatting with two decimal places
formatted_values_two_decimals <- percent(values, accuracy = 0.01)

Here, formatted_values_one_decimal would hold “12.3%”, “55.5%”, “87.9%”, and formatted_values_two_decimals would hold “12.30%”, “55.50%”, “87.90%”.

2. Application in DataFrames:

Converting numerical values to percentages within a dataframe can be achieved by applying the percent function directly to a dataframe column.

library(scales)
library(dplyr)

df <- data.frame(
  Value = c(0.123, 0.555, 0.879)
)

df <- df %>%
  mutate(Percentage_One_Decimal = percent(Value, accuracy = 0.1),
         Percentage_Two_Decimals = percent(Value, accuracy = 0.01))
print(df)

Output:

  Value Percentage_One_Decimal Percentage_Two_Decimals
1 0.123                  12.3%                  12.30%
2 0.555                  55.5%                  55.50%
3 0.879                  87.9%                  87.90%

In this revised dataframe, Percentage_One_Decimal column will contain percentages with one decimal place, and Percentage_Two_Decimals column will contain percentages with two decimal places.

3. Custom Formatting using sprintf :

The sprintf() function is valuable when a customized format string is desired, providing flexibility in defining the format of the resulting string.

values <- c(0.123, 0.555, 0.879)
formatted_values_one_decimal <- sprintf("%.1f%%", values * 100)
formatted_values_two_decimals <- sprintf("%.2f%%", values * 100)

4. Using knitr for Table Outputs:

The kable function from the knitr package is excellent for representing data in tables, with columns containing percentages being formatted using the percent function.

library(knitr)
library(scales)

df <- data.frame(Values = c(0.123, 0.555, 0.879))
df$Values <- percent(df$Values, accuracy = 0.1)

kable(df)

Output:

|Values |
|:------|
|12.3%  |
|55.5%  |
|87.9%  |

5. Advanced Formatting with formattable :

The formattable package provides a plethora of formatting options, including formatting percentages, for enhancing the representation of data frames and tables.

library(formattable)

values <- c(0.123, 0.555, 0.879)
formatted_values <- percent(values, digits = 2)  # For two decimal places
print(formatted_values)

Output:

[1] 12.30% 55.50% 87.90%

Conclusion:

Understanding how to appropriately format numbers as percentages in R is pivotal for data analysis and presentation. By using the percent function and manipulating the accuracy parameter or employing other methods such as sprintf or the formattable package, users can attain optimal, tailored representations of percentages, aiding in conveying clearer, more precise insights. Whether embedded within data frames, represented in tables using knitr, or customized using sprintf, well-formatted percentages elevate the clarity and comprehensibility of your data presentations and communications.