To remove unnecessary spaces, use the str_squish function. The str_squish function is included in the stringr package of the R programming language and performs the function of removing leading, trailing, and intervening whitespace from a string. To remove unnecessary spaces, let's check the concept and main uses of the str_squish function.

Original Korean article: str_squish function to remove unnecessary spaces

1. The concept of str_squish

str_squish() removes unnecessary spaces at the beginning and end of the target string, and reduces consecutive spaces within the string to a single space. For example, if you have a string called “Hello World”, applying the str_squish() function will convert it to “Hello World”.

# stringr example example
library(stringr)

# example
str_squish("   Hello   World  ")
# example: "Hello World"

2. Main usage

Basic usage

• str_squish(string)

string: target string

1) Apply to vector

The str_squish function can also be applied to string vectors. In this case, the function is applied to each string element.

# example
str_squish(c("   Hello  ", "  World  "))
# example: "Hello" "World"

2) Apply to data frame

The str_squish function with the dplyr package allows you to apply a function to specific columns in a data frame.

# dplyr example example
library(dplyr)

# example example example
df <- data.frame(name = c("  Alice  ", "  Bob  ", "  Carol  "),
                 age = c(30, 40, 50))

# str_squish example
df <- df %>%
  mutate(name = str_squish(name))

# example example
print(df)

3. Conclusion

The str_squish() function is a very useful tool when squeezing text data. This function simplifies complex string processing tasks. It is often used in data analysis or text mining tasks, so it is a good idea to learn how to use this function.

To download the R program, you can click the download link on the R program's official website (https://www.r-project.org/).

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Practical Use Cases for str_squish()

In real text analysis projects, unnecessary spaces often appear when data is copied from web pages, spreadsheets, survey answers, PDF extractions, or manually typed forms. A string may look clean on the screen, but it can contain repeated spaces, tabs, or line-break-like spacing that makes grouping, joining, filtering, or tokenizing less reliable.

The value of str_squish() is that it solves two problems at once. First, it removes leading and trailing whitespace. Second, it compresses repeated internal whitespace into a single normal space. This makes the function especially useful before comparing labels, cleaning names, standardizing categories, or preparing text for tokenization.

When to Use It in an R Workflow

• Before using text as a key for joins or matching.
• Before counting unique values in a survey or category column.
• Before tokenizing Korean or English text for text mining.
• Before exporting cleaned data to a report or dashboard.

A practical rule is simple: if a text column came from outside your own controlled data pipeline, normalize whitespace early. That small cleaning step can prevent confusing duplicate categories and unexpected mismatches later in the analysis.

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This article is an English translation and global-reader adaptation of the Korean post “str_squish function to remove unnecessary spaces.” It preserves the original article’s main explanation, examples, and practical context.

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