slice_min: Get Rows with minimum values of a column

dplyr slice_min()

Published

November 3, 2023

In this tutorial, we will learn how to get rows with lowest values of a column from a data frame in R. We will use dplyr’s slice_min() function to select rows with lowest values for a column in a data frame. We will also use slice_min() function in dplyr to find the bottom n rows with lowest or min values for a variable.

dplyr’s slice_min(): Rows with lowest values for a column

library(tidyverse)
library(palmerpenguins)

To illustrate how slice_min() works, let us simplify our penguins data by selecting just a few columns with no missing values. We will also add row number using dplyr’s row_number() to quickly find which rows we have selected.

penguins %
  drop_na() %>%
  select(species, sex, body_mass_g, flipper_length_mm) %>%
  mutate(row_id = row_number())

Our data looks like this.

penguins %>% head()

# A tibble: 6 × 5
  species sex    body_mass_g flipper_length_mm row_id
                            
1 Adelie  male          3750               181      1
2 Adelie  female        3800               186      2
3 Adelie  female        3250               195      3
4 Adelie  female        3450               193      4
5 Adelie  male          3650               190      5
6 Adelie  female        3625               181      6

dplyr’s slice_min(): Get the row(s) with minimum value for a column

To find the row with the lowest value of a column, we use slice_min() with the column name and n = 1 as arguments. In our example below, we use slice_min() to get the row with lowest or body mass in our penguins data.

penguins %>%
  slice_min(body_mass_g, n =1)

# A tibble: 1 × 5
  species   sex    body_mass_g flipper_length_mm row_id
                              
1 Chinstrap female        2700               192    304

dplyr’s slice_min(): Get bottom 2 rows with minimum values for a column

With slice_min() we can the get the bottom two rows with minimum or lowest values for a column by specifying n=2 in the argument. For example, when we use n = 2 with body mass column as arguments to slice_min(), we get the bottom two rows containing lowest body mass.

penguins %>%
  slice_min(body_mass_g, n = 2)

# A tibble: 3 × 5
  species   sex    body_mass_g flipper_length_mm row_id
                              
1 Chinstrap female        2700               192    304
2 Adelie    female        2850               181     53
3 Adelie    female        2850               184     59

dplyr’s slice_min(): Get bottom n rows with minimum values for a column

Similarly we can get the bottom n rows with lowest values for a column, by specifying an value for n we want.

penguins %>%
  slice_min(body_mass_g, n = 10)

# A tibble: 10 × 5
   species   sex    body_mass_g flipper_length_mm row_id
                               
 1 Chinstrap female        2700               192    304
 2 Adelie    female        2850               181     53
 3 Adelie    female        2850               184     59
 4 Adelie    female        2900               187     49
 5 Adelie    female        2900               178     93
 6 Adelie    female        2900               188    111
 7 Chinstrap female        2900               187    288
 8 Adelie    female        2925               193     99
 9 Adelie    female        3000               185     40
10 Adelie    female        3000               192    139

You might want to check out the tutorial on using dplyr’s slice_max() to get the top n rowsfor a specific column.

--- title: "slice_min: Get Rows with minimum values of a column" date: 2023-11-03 categories: ['dplyr slice_min()'] format: html: code-fold: false code-tools: true --- In this tutorial, we will learn how to get rows with lowest values of a column from a data frame in R. We will use dplyr's slice_min() function to select rows with lowest values for a column in a data frame. We will also use slice_min() function in dplyr to find the **bottom n rows** with lowest or min values for a variable. ![dplyr's slice_min(): Rows with lowest values for a column](https://rstats101.com/wp-content/uploads/2023/10/dplyr_slice_min.png) dplyr's slice_min(): Rows with lowest values for a column ```r library(tidyverse) library(palmerpenguins) ``` To illustrate how slice_min() works, let us simplify our penguins data by selecting just a few columns with no missing values. We will also [add row number using dplyr's row_number()](https://rstats101.com/dplyr-row_number-add-unique-row-number-to-a-dataframe/) to quickly find which rows we have selected. ```r penguins % drop_na() %>% select(species, sex, body_mass_g, flipper_length_mm) %>% mutate(row_id = row_number()) ``` Our data looks like this. ```r penguins %>% head() # A tibble: 6 × 5 species sex body_mass_g flipper_length_mm row_id 1 Adelie male 3750 181 1 2 Adelie female 3800 186 2 3 Adelie female 3250 195 3 4 Adelie female 3450 193 4 5 Adelie male 3650 190 5 6 Adelie female 3625 181 6 ``` ### dplyr's slice_min(): Get the row(s) with minimum value for a column To find the row with the lowest value of a column, we use slice_min() with the column name and n = 1 as arguments. In our example below, we use slice_min() to get the row with lowest or body mass in our penguins data. ```r penguins %>% slice_min(body_mass_g, n =1) # A tibble: 1 × 5 species sex body_mass_g flipper_length_mm row_id 1 Chinstrap female 2700 192 304 ``` ### dplyr's slice_min(): Get bottom 2 rows with minimum values for a column With slice_min() we can the get the bottom two rows with minimum or lowest values for a column by specifying n=2 in the argument. For example, when we use n = 2 with body mass column as arguments to slice_min(), we get the bottom two rows containing lowest body mass. ```r penguins %>% slice_min(body_mass_g, n = 2) # A tibble: 3 × 5 species sex body_mass_g flipper_length_mm row_id 1 Chinstrap female 2700 192 304 2 Adelie female 2850 181 53 3 Adelie female 2850 184 59 ``` ### dplyr's slice_min(): Get bottom n rows with minimum values for a column Similarly we can get the bottom n rows with lowest values for a column, by specifying an value for n we want. ```r penguins %>% slice_min(body_mass_g, n = 10) # A tibble: 10 × 5 species sex body_mass_g flipper_length_mm row_id 1 Chinstrap female 2700 192 304 2 Adelie female 2850 181 53 3 Adelie female 2850 184 59 4 Adelie female 2900 187 49 5 Adelie female 2900 178 93 6 Adelie female 2900 188 111 7 Chinstrap female 2900 187 288 8 Adelie female 2925 193 99 9 Adelie female 3000 185 40 10 Adelie female 3000 192 139 ``` You might want to check out the tutorial on using [dplyr's slice_max() to get the top n rows ](https://rstats101.com/slice_max-get-rows-with-max-values-of-variable/)for a specific column.