slice() from dplyr in R – Examples

The slice() function from dplyr package is used to subset the R data.frame rows (observations) based on index/position/number and also used to drop the rows and duplicate the rows by Index. Using this doesn’t modify the columns, groups, and data frame attributes. By providing negative values it will drop the specified rows (In other words it just excludes the rows specified with a negative position).

dplyr is an R package that provides a grammar of data manipulation and provides a most used set of verbs that helps data science analysts to solve the most common data manipulation. In order to use this, you have to install it first using install.packages('dplyr') and load it using library(dplyr). In this article, you will learn the syntax of the slice() function, its arguments, and its usage with examples.

Slice VerbsDescription
slice()Slices the data.frame by row index
slice_head()Select the first rows
slice_tail()Select the last rows
slice_min()Select the minimum of a column
slice_max()Select the maximum of a column
slice_random()Select random rows
Different slice functions from dplyr package

1. Syntax of slice()

Following is the syntax of the R dplyr::slice() function.


# Syntax of slice()
slice(.data, ..., .preserve = FALSE)

Arguments

  • .data – data.frame or tibble to slice.
  • ... – Specify how you wanted to slice
  • .preserve

2. Data preparation

Let’s create an R DataFrame, run these examples and explore the output. If you already have data in CSV you can easily import CSV file to R DataFrame. Also, refer to Import Excel File into R.


# Create DataFrame
df <- data.frame(
  id = c(10,11,12,13,14,15,16,17),
  name = c('sai','ram','deepika','sahithi','kumar','scott','Don','Lin'),
  gender = c('M','M','F','F','M','M','M','F'),
  dob = as.Date(c('1990-10-02','1981-3-24','1987-6-14','1985-8-16',
                  '1995-03-02','1991-6-21','1986-3-24','1990-8-26')),
  state = c('CA','NY',NA,NA,'DC','DW','AZ','PH'),
  row.names=c('r1','r2','r3','r4','r5','r6','r7','r8')
)
df

Yields below output.


# Output
   id    name gender        dob state
r1 10     sai      M 1990-10-02    CA
r2 11     ram      M 1981-03-24    NY
r3 12 deepika      F 1987-06-14  <NA>
r4 13 sahithi      F 1985-08-16  <NA>
r5 14   kumar      M 1995-03-02    DC
r6 15   scott      M 1991-06-21    DW
r7 16     Don      M 1986-03-24    AZ
r8 17     Lin      F 1990-08-26    PH

3. Slice Rows by Index Position

Using dplyr::slice() function in R lets you select the rows (observations) from data.frame by index position (row number). This function takes the first argument as data.frame, the second argument with all indexes by comma separator you wanted to select. Refer to how to select rows from data frame for other ways of getting data from data frame.


# Load dplyr library
library('dplyr')

# Select rows 2 and 3
df2 <- df %>% slice(2,3)
df2

# Output
#   id    name gender        dob state
#r2 11     ram      M 1981-03-24    NY
#r3 12 deepika      F 1987-06-14  <NA>

4. Slice Rows by List of Index Positions

If you have a list of indexes you wanted to slice from data frame use the vector with the indexes as a second argument. The following example selects rows from indexes 2,3,5, and 6.


# Select rows from list
df2 <- df %>% slice(c(2,3,5,6))
df2

# Output
#   id    name gender        dob state
#r2 11     ram      M 1981-03-24    NY
#r3 12 deepika      F 1987-06-14  <NA>
#r5 14   kumar      M 1995-03-02    DC
#r6 15   scott      M 1991-06-21    DW

5. Slice by start and end position (by range)

It also supports range with start and end index positions separated by :. The following example slices the R data.frame rows between indexes 2 and 6 range.


# select rows by range
df2 <- df %>% slice(2:6)
df2

# Output
#   id    name gender        dob state
#r2 11     ram      M 1981-03-24    NY
#r3 12 deepika      F 1987-06-14  <NA>
#r4 13 sahithi      F 1985-08-16  <NA>
#r5 14   kumar      M 1995-03-02    DC
#r6 15   scott      M 1991-06-21    DW

6. Drop Rows

slice() function also lets you drop rows from r data frame by supplying negative index values as arguments. The first example from below demonstrates dropping by index position and the second example demonstrates dropping by the range of negative index position.


# Drop rows using slice()
df2 <- df %>% slice(-2,-3,-4,-5,-6)
df2

# Drop by range
df2 <- df %>% slice(-2:-6)
df2

# Both yields same output
#   id name gender        dob state
#r1 10  sai      M 1990-10-02    CA
#r7 16  Don      M 1986-03-24    AZ
#r8 17  Lin      F 1990-08-26    PH

7. Complete Example of slice() Function

The following is the complete example of the usage of the slice() function in R.


# Create DataFrame
df <- data.frame(
  id = c(10,11,12,13,14,15,16,17),
  name = c('sai','ram','deepika','sahithi','kumar','scott','Don','Lin'),
  gender = c('M','M','F','F','M','M','M','F'),
  dob = as.Date(c('1990-10-02','1981-3-24','1987-6-14','1985-8-16',
                  '1995-03-02','1991-6-21','1986-3-24','1990-8-26')),
  state = c('CA','NY',NA,NA,'DC','DW','AZ','PH'),
  row.names=c('r1','r2','r3','r4','r5','r6','r7','r8')
)
df

# Load dplyr library
library('dplyr')

# Select rows 2 and 3
df2 <- df %>% slice(2,3)
df2

# Select rows from list
df2 <- df %>% slice(c(2,3,5,6))
df2

# select rows by range
df2 <- df %>% slice(2:6)
df2

# Drop rows using slice()
df2 <- df %>% slice(-2,-3,-5,-6)
df2

# Drop by range
df2 <- df %>% slice(-2:-6)
df2

8. Conclusion

In this article, you have learned the slice() function of the R dplyr package. This function is used to subset the R data.frame rows based on index/position/number. Using this doesn’t modify the columns, groups, and data frame attributes. By providing negative values it will drop the specified rows (In other words it just excludes the rows specified with a negative position)

Related Articles

References

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