Introduction

Filtering data frames in R is a common task in data analysis. Often we want to subset a data frame to only keep rows that meet certain criteria. A useful filtering technique is keeping rows where a column value falls between two specified values.

In this post, we’ll walk through how to filter rows in R where a column value is between two values using base R syntax.

Filtering with bracket notation

One way to filter rows is by using bracket notation [] and specifying a logical vector.

Let’s create a sample data frame:

df <- data.frame(
  id = 1:10,
  value = c(5, 3, 6, 9, 2, 4, 7, 1, 8, 10)
)

We can filter df to only keep rows where value is between 5 and 8 with:

df[df$value >= 5 & df$value <= 8,]

  id value
1  1     5
3  3     6
7  7     7
9  9     8

This filters for rows where value is greater than or equal to 5 df$value >= 5 AND less than or equal to 8 df$value <= 8. The comma after the logical vector tells R to return the filtered rows.

Filtering with subset()

Another option is using the subset() function:

subset(df, value >= 5 & value <= 8)

  id value
1  1     5
3  3     6
7  7     7
9  9     8

subset() takes a data frame as the first argument, then a logical expression similar to the bracket notation.

Additional examples

We can filter on different columns and value ranges:

# id between 3 and 7
df[df$id >= 3 & df$id <= 7,] 

  id value
3  3     6
4  4     9
5  5     2
6  6     4
7  7     7

# value less than 5
subset(df, value < 5)

  id value
2  2     3
5  5     2
6  6     4
8  8     1

It’s also possible to filter rows outside a range by flipping the logical operators:

# id NOT between 3 and 7
df[!(df$id >= 3 & df$id <= 7),]

   id value
1   1     5
2   2     3
8   8     1
9   9     8
10 10    10

# value greater than 5  
subset(df, value > 5) 

   id value
3   3     6
4   4     9
7   7     7
9   9     8
10 10    10

Summary

Filtering data frames where a column is between two values is straightforward in R. The key steps are:

• Use bracket notation df[logical,] or subset(df, logical)
• Create a logical expression with & and >=, <= operators
• Specify the column name and range of values to filter between

I encourage you to try filtering data frames on your own! Subsetting by logical expressions is an important skill for efficient R programming.