Removing Rows Using dplyr
The dplyr package provides a more readable and efficient way to perform data manipulation tasks, including filtering based on count.
1. Using group_by() and filter()
You can use the group_by() function to group the data by the specific column and then use filter() along with n() to filter out the rows based on the count.
# Load dplyr package
library(dplyr)
# Set the threshold for minimum count
threshold <- 4
# Filter the data frame to keep only rows with categories meeting the threshold
filtered_data <- data %>%
group_by(category) %>%
filter(n() >= threshold) %>%
ungroup()
# Display the filtered data frame
print(filtered_data)
Output:
# A tibble: 4 × 3
id category value
<int> <chr> <dbl>
1 2 B 15
2 5 B 15
3 8 B 15
4 9 B 15
2. Using add_count()
The add_count() function is a convenient way to add a count column to the data frame, which can then be used to filter rows.
# Load dplyr package
library(dplyr)
# Set the threshold for minimum count
threshold <- 4
# Add count column and filter the data frame
filtered_data <- data %>%
add_count(category) %>%
filter(n >= threshold) %>%
select(-n)
# Display the filtered data frame
print(filtered_data)
Output:
id category value
1 2 B 15
2 5 B 15
3 8 B 15
4 9 B 15
How to Remove rows based on count of a specific value in R?
Data cleaning is an essential step in data analysis, and removing rows based on specific criteria is a common task. One such criterion is the count of a specific value in a column. This article will guide you through the process of removing rows from a data frame in R based on the count of a specific value using various methods, including base R functions and dplyr.
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