ProgramGuruTo collapse factor levels in R, you can use the `fct_collapse` function from the `forcats` package. This function allows you to group existing levels of a factor into new combined levels, making it easier to analyze or visualize data.
In this example,
age_groups which contains the values 'Young', 'Middle', 'Old', and 'Elderly'. This vector represents different age groups.factor() function to convert the age_groups vector into a factor. We assign the result to a variable named age_factor. The factor() function automatically identifies the unique levels of the vector.fct_collapse() function from the `forcats` package to collapse the levels of the age_factor into fewer groups. In this example, we group 'Young' and 'Middle' into a new level 'Young-Middle' and 'Old' and 'Elderly' into a new level 'Old-Elderly'. We assign the result to a variable named collapsed_age_factor.collapsed_age_factor to the console to verify the new levels.library(forcats)
age_groups <- c('Young', 'Middle', 'Old', 'Elderly', 'Young', 'Old')
age_factor <- factor(age_groups)
collapsed_age_factor <- fct_collapse(age_factor,
'Young-Middle' = c('Young', 'Middle'),
'Old-Elderly' = c('Old', 'Elderly'))
print(collapsed_age_factor)[1] Young-Middle Young-Middle Old-Elderly Old-Elderly Young-Middle Old-Elderly Levels: Young-Middle Old-Elderly
In this example,
product_categories which contains the values 'Electronics', 'Furniture', 'Clothing', 'Food', and 'Electronics'. This vector represents different product categories.factor() function to convert the product_categories vector into a factor. We assign the result to a variable named product_factor. The factor() function automatically identifies the unique levels of the vector.fct_collapse() function from the `forcats` package to collapse the levels of the product_factor into fewer groups. In this example, we group 'Electronics' and 'Furniture' into a new level 'Non-Consumable' and 'Clothing' and 'Food' into a new level 'Consumable'. We assign the result to a variable named collapsed_product_factor.collapsed_product_factor to the console to verify the new levels.library(forcats)
product_categories <- c('Electronics', 'Furniture', 'Clothing', 'Food', 'Electronics')
product_factor <- factor(product_categories)
collapsed_product_factor <- fct_collapse(product_factor,
'Non-Consumable' = c('Electronics', 'Furniture'),
'Consumable' = c('Clothing', 'Food'))
print(collapsed_product_factor)[1] Non-Consumable Non-Consumable Consumable Consumable Non-Consumable Levels: Non-Consumable Consumable
In this example,
survey_responses which contains the values 'Strongly Agree', 'Agree', 'Neutral', 'Disagree', and 'Strongly Disagree'. This vector represents different levels of agreement in a survey.factor() function to convert the survey_responses vector into a factor. We assign the result to a variable named response_factor. The factor() function automatically identifies the unique levels of the vector.fct_collapse() function from the `forcats` package to collapse the levels of the response_factor into fewer groups. In this example, we group 'Strongly Agree' and 'Agree' into a new level 'Positive', 'Neutral' remains as it is, and 'Disagree' and 'Strongly Disagree' into a new level 'Negative'. We assign the result to a variable named collapsed_response_factor.collapsed_response_factor to the console to verify the new levels.library(forcats)
survey_responses <- c('Strongly Agree', 'Agree', 'Neutral', 'Disagree', 'Strongly Disagree')
response_factor <- factor(survey_responses)
collapsed_response_factor <- fct_collapse(response_factor,
'Positive' = c('Strongly Agree', 'Agree'),
'Negative' = c('Disagree', 'Strongly Disagree'))
print(collapsed_response_factor)[1] Positive Positive Neutral Negative Negative Levels: Positive Neutral Negative
In this tutorial, we learned How to Collapse Factor Levels in R language with well detailed examples.