Apply a Function to Factor Levels

Description

Transforms factor levels by applying a function to each level.

Usage

ft_apply(factor_vec, apply_func)

Arguments

Value

A factor vector with transformed levels.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry'))

# Append '_fruit' to each level
ft_apply(factor_vec, function(x) paste0(x, '_fruit'))

Reorder Factor Levels Based on Character Frequency at Positions

Description

Reorders the levels of a factor vector based on the frequency of characters at specified positions within the data.

Usage

ft_char_freq(
  factor_vec,
  positions,
  case = FALSE,
  decreasing = TRUE,
  inplace = TRUE
)

Arguments

Value

A factor vector with levels reordered based on the frequency of characters at specified positions.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'apricot', 'cherry', 'banana', 'banana', 'date'))

# Reorder based on characters at positions 1 and 2
ft_char_freq(factor_vec, positions = 1:2)

# Reorder, case-sensitive, decreasing order
ft_char_freq(factor_vec, positions = c(1, 3), case = TRUE)

Collapse Factor Levels Based on Grouping

Description

Collapses specified levels of a factor into new levels based on a grouping list.

Usage

ft_collapse_lev(factor_vec, groups)

Arguments

Value

A factor vector with collapsed levels.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'elderberry'))

# Define groups
groups <- list(
  'Group1' = c('apple', 'banana'),
  'Group2' = c('cherry', 'date')
)

# Collapse levels
ft_collapse_lev(factor_vec, groups)

Combine Two Vectors of Unequal Lengths and Sort Based on Specified Levels

Description

Combines two vectors, which may be of unequal lengths, into a factor vector and sorts based on the levels of either the first or second vector.

Usage

ft_combine(vector1, vector2, sort_by = 1, decreasing = FALSE)

Arguments

Value

A factor vector combining both vectors and sorted based on specified levels.

Examples

# Example vectors of unequal lengths
vector1 <- c('apple', 'banana', 'cherry')
vector2 <- c('date', 'fig', 'grape', 'honeydew')

# Combine and sort based on vector1 levels
combined_factor1 <- ft_combine(vector1, vector2, sort_by = 1)
print(combined_factor1)

# Combine and sort based on vector2 levels
combined_factor2 <- ft_combine(vector1, vector2, sort_by = 2)
print(combined_factor2)

# Combine with decreasing order based on vector1
combined_factor3 <- ft_combine(vector1, vector2, sort_by = 1, decreasing = TRUE)
print(combined_factor3)

Concatenate Multiple Factor Vectors

Description

Combines multiple factor vectors into a single factor, unifying the levels.

Usage

ft_concat(...)

Arguments

Value

A single factor vector containing all elements and unified levels.

Author(s)

Kai Guo

Examples

# Example factor vectors
factor_vec1 <- factor(c('apple', 'banana'))
factor_vec2 <- factor(c('cherry', 'date'))

# Concatenate factors
concatenated_factor <- ft_concat(factor_vec1, factor_vec2)
levels(concatenated_factor)

Reorder Factor Levels by Level Count

Description

Reorders the levels of a factor vector based on the count of each level in the data.

Usage

ft_count(factor_vec, decreasing = TRUE, inplace = FALSE)

Arguments

Value

A factor vector with levels reordered based on their count.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'apple', 'cherry', 'banana', 'banana', 'date'))

# Reorder levels by decreasing count
ft_count(factor_vec)

# Reorder levels by increasing count
ft_count(factor_vec, decreasing = FALSE)

Decode Numeric Codes into Factor Levels

Description

Converts numeric codes back into factor levels using a provided mapping.

Usage

ft_decode(codes, mapping)

Arguments

Value

A factor vector with decoded levels.

Author(s)

Kai Guo

Examples

# Numeric codes
codes <- c(1, 2, 3, 2)

# Mapping from levels to codes
mapping <- c('low' = 1, 'medium' = 2, 'high' = 3)

# Decode codes into factor levels
ft_decode(codes, mapping = mapping)

Create Dummy Variables from Factor Levels

Description

Generates a data frame of dummy variables (one-hot encoded) from a factor vector.

Usage

ft_dummy(factor_vec)

Arguments

Value

A data frame where each column represents a level of the factor, containing 1s and 0s.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'apple', 'cherry'))

# Create dummy variables
ft_dummy(factor_vec)

Flag Duplicate Factor Levels

Description

Identifies duplicate levels in a factor vector and returns a logical vector indicating which elements are duplicates.

Usage

ft_duplicates(factor_vec)

Arguments

Value

A logical vector where TRUE indicates a duplicate level.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'apple', 'cherry', 'banana'))

# Flag duplicates
ft_duplicates(factor_vec)

Encode Factor Levels into Numeric Codes

Description

Converts the levels of a factor vector into numeric codes, optionally using a provided mapping.

Usage

ft_encode(factor_vec, mapping = NULL)

Arguments

Value

A numeric vector with encoded values.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('low', 'medium', 'high', 'medium'))

# Encode without mapping
ft_encode(factor_vec)

# Encode with custom mapping
custom_mapping <- c('low' = 1, 'medium' = 2, 'high' = 3)
ft_encode(factor_vec, mapping = custom_mapping)

Extract Substrings from Factor Levels

Description

Extracts substrings from the levels of a factor vector based on a regular expression pattern and creates a new factor.

Usage

ft_extract(factor_vec, pattern, capture_group = 0)

Arguments

Value

A new factor vector containing the extracted substrings.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('item123', 'item456', 'item789'))

# Extract numeric part
ft_extract(factor_vec, pattern = '\\d+')

# Extract with capturing group
factor_vec <- factor(c('apple: red', 'banana: yellow', 'cherry: red'))
ft_extract(factor_vec, pattern = '^(\\w+):', capture_group = 1)

Factorize Character Vectors with Consistent Levels

Description

Converts one or more character vectors into factors, ensuring that they share the same levels.

Usage

ft_factorize(..., levels = NULL)

Arguments

Value

A list of factor vectors with consistent levels.

Author(s)

Kai Guo

Examples

# Example character vectors
vec1 <- c('apple', 'banana', 'cherry')
vec2 <- c('banana', 'date', 'apple')

# Factorize with consistent levels
factors <- ft_factorize(vec1, vec2)
levels(factors[[1]])
levels(factors[[2]])

Filter Factor Levels by Frequency and Recalculate Character Frequencies

Description

Filters out factor levels that occur less than a specified frequency threshold and recalculates character frequencies excluding the removed levels. Offers options to handle NA values and returns additional information.

Usage

ft_filter_freq(
  factor_vec,
  min_freq = 1,
  na.rm = FALSE,
  case = FALSE,
  decreasing = TRUE,
  return_info = FALSE
)

Arguments

Value

If return_info is FALSE, returns a factor vector with levels filtered by the specified frequency threshold and reordered based on recalculated total character frequency. If return_info is TRUE, returns a list containing the filtered factor vector, removed levels, and character frequency table.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'banana', 'apple', 'fig', NA))

# Filter levels occurring less than 2 times and reorder by character frequency
ft_filter_freq(factor_vec, min_freq = 2)

# Filter levels, remove NA values, and return additional information
result <- ft_filter_freq(factor_vec, min_freq = 2, na.rm = TRUE, return_info = TRUE)
result$filtered_factor
result$removed_levels
result$char_freq_table

Filter Factor Levels Using a Function

Description

Removes levels from a factor vector based on a user-defined function.

Usage

ft_filter_func(factor_vec, func)

Arguments

Value

A factor vector with levels filtered according to the function.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date'))

# Remove levels that start with 'b'
ft_filter_func(factor_vec, function(x) !grepl('^b', x))

Remove Factor Levels with Specific Characters at Specified Positions

Description

Removes factor levels where a specified character appears at specified positions within the levels.

Usage

ft_filter_pos(
  factor_vec,
  positions = NULL,
  char,
  case = FALSE,
  remove_na = TRUE,
  invert = FALSE,
  .return = FALSE
)

Arguments

Value

A factor vector with levels removed where the specified character appears at the specified positions.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'apricot', 'cherry', 'date', 'fig', 'grape'))

# Remove levels where 'a' appears at position 1
ft_filter_pos(factor_vec, positions = 1, char = 'a')

# Remove levels where 'e' appears at positions 2 or 3
ft_filter_pos(factor_vec, positions = c(2, 3), char = 'e')

# Case-sensitive removal
factor_vec_case <- factor(c('Apple', 'banana', 'Apricot', 'Cherry', 'Date', 'Fig', 'grape'))
ft_filter_pos(factor_vec_case, positions = 1, char = 'A', case = TRUE)

Reorder Factor Levels Based on Character Frequency

Description

Reorders the levels of a factor vector based on the frequency of characters in each level's name. Supports case sensitivity, descending order, and optionally reorders the data vector's elements to align with the new levels' order.

Usage

ft_freq(factor_vec, case = FALSE, decreasing = TRUE, inplace = FALSE)

Arguments

Value

A new factor vector with reordered levels. Depending on the inplace parameter, the data vector's elements may also be reordered.

Author(s)

Kai Guo

Examples

# Example 1: Reorder levels based on character frequency without reordering data elements
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'fig', 'grape'))
new <- ft_freq(
  factor_vec,
  case = FALSE,
  decreasing = TRUE,
  inplace = FALSE
)
print(new)
# [1] apple  banana cherry date   fig    grape
# Levels: apple banana date cherry fig grape

# Example 2: Reorder levels based on character frequency and reorder data elements
new_inplace <- ft_freq(
  factor_vec,
  case = FALSE,
  decreasing = TRUE,
  inplace = TRUE
)
print(new_inplace)
# [1] apple  banana date   cherry fig    grape
# Levels: apple banana date cherry fig grape

# Example 3: Reorder levels in decreasing order based on character frequency
# without reordering data elements
new_dec <- ft_freq(
  factor_vec,
  case = FALSE,
  decreasing = TRUE,
  inplace = FALSE
)
print(new_dec)
# [1] apple  banana cherry date   fig    grape
# Levels: apple banana date cherry fig grape

# Example 4: Reorder levels with case sensitivity and reorder data elements
factor_vec_case <- factor(c('Apple', 'banana', 'Cherry', 'date', 'Fig', 'grape'))
new_case <- ft_freq(
  factor_vec_case,
  case = TRUE,
  decreasing = TRUE,
  inplace = TRUE
)
print(new_case)
# [1] Apple   banana  Cherry date    Fig     grape
# Levels: cherry Apple banana grape Fig date

# Example 5: Reorder levels based on character frequency, allowing insertion beyond string length
factor_vec_short <- factor(c('go', 'dog', 'cat', 'bird'))
new_short <- ft_freq(
  factor_vec_short,
  case = FALSE,
  decreasing = TRUE,
  inplace = FALSE
)
print(new_short)
# [1] go   dog  cat  bird
# Levels: cat dog bird go

Group Factor Levels by Common Prefix

Description

Groups factor levels by a common prefix of specified length.

Usage

ft_group_by_prefix(factor_vec, prefix_length)

Arguments

Value

A factor vector with levels grouped by the common prefix.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple_red', 'apple_green', 'banana_yellow', 'banana_green', 'cherry_red'))

# Group by first 5 characters (common prefix)
ft_group_by_prefix(factor_vec, prefix_length = 5)

Impute Missing Values in Factor Vector

Description

Replaces NA values in a factor vector using specified imputation methods.

Usage

ft_impute(factor_vec, method = "mode")

Arguments

Value

A factor vector with NA values imputed.

Author(s)

Kai Guo

Examples

# Example factor vector with NAs
factor_vec <- factor(c('apple', NA, 'banana', 'apple', NA))

# Impute using mode
ft_impute(factor_vec, method = 'mode')

# Impute using random selection
ft_impute(factor_vec, method = 'random')

Insert New Levels into a Factor Vector After Specified Targets

Description

Inserts one or more new levels into a factor vector immediately after specified target levels or positions. Each new level corresponds to its respective target in a one-to-one manner. Supports exact matches, position-based targeting, and pattern-based matching with optional case sensitivity. Can handle multiple insertions, manage duplicates, and optionally reorder the data vector's elements to align with the new levels.

Usage

ft_insert(
  factor_vec,
  insert,
  target = NULL,
  positions = NULL,
  pattern = NULL,
  case = FALSE,
  insert_after_na = FALSE,
  allow_duplicates = FALSE,
  inplace = FALSE
)

Arguments

Value

A new factor vector with the new levels inserted at the specified positions. If inplace = TRUE, the data vector's elements are reordered to match the new levels' order. If inplace = FALSE, only the levels' order is adjusted without changing the data vector's elements' order.

Author(s)

Kai Guo

Examples

# Example 1: Insert 'date' after position 2 and 'grape' after position 4
# without allowing duplicates, returning a new factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'fig', 'grape'))
new_factor <- ft_insert(
  factor_vec,
  insert = c('date', 'grape'),
  positions = c(2, 4),
  inplace = FALSE
)
print(new_factor)
# [1] apple  banana date   cherry fig    grape
# Levels: apple banana date cherry fig grape

# Example 2: Insert 'date' after position 2 and 'grape' after position 4,
# allowing duplicates, returning a new factor vector
new_factor_dup <- ft_insert(
  factor_vec,
  insert = c('date', 'grape'),
  positions = c(2, 4),
  allow_duplicates = TRUE,
  inplace = FALSE
)
print(new_factor_dup)
# [1] apple  banana date   cherry fig    grape.1
# Levels: apple banana date cherry fig grape.1

# Example 3: Insert 'date' after position 2 and 'grape' after position 4,
# and reorder data elements
new_factor_inplace <- ft_insert(
  factor_vec,
  insert = c('date', 'grape'),
  positions = c(2, 4),
  inplace = TRUE
)
print(new_factor_inplace)
# [1] apple  banana date   cherry fig    grape
# Levels: apple banana date cherry fig grape

# Example 4: Insert 'kiwi' after 'banana' and 'grape', case-sensitive,
# allowing duplicates, returning a new factor vector
factor_vec_case <- factor(c('Apple', 'banana', 'Cherry', 'date', 'Fig', 'grape'))
new_factor_case <- ft_insert(
  factor_vec_case,
  insert = c('kiwi', 'kiwi'),
  target = c('banana', 'grape'),
  case = TRUE,
  allow_duplicates = TRUE,
  inplace = FALSE
)
print(new_factor_case)
# [1] Apple   banana  Cherry  date    Fig     grape   kiwi    kiwi.1

# Example 5: Insert 'lychee' after NA, returning a new factor vector
factor_vec_na <- factor(c('apple', NA, 'banana', 'cherry', NA, 'date'))
new_factor_na <- ft_insert(
  factor_vec_na,
  insert = 'lychee',
  insert_after_na = TRUE,
  inplace = FALSE
)
print(new_factor_na)
# [1] apple  <NA>    lychee banana cherry <NA>    date
# Example 6:
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'fig', 'grape'))

Get Intersection of Factor Levels from Multiple Vectors

Description

Combines multiple factor vectors and returns a factor vector containing only the levels common to all.

Usage

ft_intersect(...)

Arguments

Value

A factor vector containing the intersection of levels from all provided factors.

Author(s)

Kai Guo

Examples

# Example factor vectors
factor_vec1 <- factor(c('apple', 'banana', 'cherry'))
factor_vec2 <- factor(c('banana', 'date', 'cherry'))
factor_vec3 <- factor(c('banana', 'cherry', 'fig'))

# Get intersection of levels
ft_intersect(factor_vec1, factor_vec2, factor_vec3)

Sort Factor Levels Based on Their Length

Description

Reorders the levels of a factor vector based on the character length of each level. Optionally reorders the data vector's elements to align with the new levels' order.

Usage

ft_len(factor_vec, decreasing = FALSE, inplace = FALSE)

Arguments

Value

A factor vector with levels reordered based on their length. Depending on the inplace parameter, the data vector's elements may also be reordered.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date'))

# Sort levels by length without reordering data elements
sorted_factor <- ft_len(factor_vec)
print(sorted_factor)
# [1] apple  banana cherry date
# Levels: apple date banana cherry

# Sort levels by length and reorder data elements
sorted_factor_inplace <- ft_len(factor_vec, inplace = TRUE)
print(sorted_factor_inplace)
# [1] date   apple  banana cherry
# Levels: apple date banana cherry

Get Character Lengths of Factor Levels

Description

Calculates the number of characters in each level of a factor vector.

Usage

ft_level_lengths(factor_vec)

Arguments

Value

A named numeric vector with the length of each level.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry'))

# Get level lengths
ft_level_lengths(factor_vec)

Get Order of Factor Levels in Data

Description

Returns a vector indicating the order in which factor levels appear in the data.

Usage

ft_level_order(factor_vec)

Arguments

Value

A numeric vector representing the order of levels.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('banana', 'apple', 'cherry', 'apple', 'banana'))

# Get level order
ft_level_order(factor_vec)

Calculate Statistics for Each Factor Level

Description

Computes statistical summaries for each level of a factor vector based on associated numeric data.

Usage

ft_level_stats(factor_vec, numeric_vec, stat_func)

Arguments

Value

A data frame with factor levels and their corresponding statistics.

Author(s)

Kai Guo

Examples

# Example data
factor_vec <- factor(c('A', 'B', 'A', 'B', 'C'))
numeric_vec <- c(10, 20, 15, 25, 30)

# Calculate mean for each level
ft_level_stats(factor_vec, numeric_vec, stat_func = mean)

Map Factor Levels Using a Function

Description

Transforms factor levels by applying a function that can include complex logic.

Usage

ft_map_func(factor_vec, map_func)

Arguments

Value

A factor vector with levels mapped according to the function.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry'))

# Map levels to uppercase if they start with 'a'
ft_map_func(factor_vec, function(x) {
  ifelse(grepl('^a', x), toupper(x), x)
})

Create a Mapping Table of Original and Modified Factor Levels

Description

Creates a data frame mapping the original factor levels to the modified levels.

Usage

ft_mapping(original_factor, modified_factor)

Arguments

Value

A data frame containing the mapping of original to modified levels.

Author(s)

Kai Guo

Examples

# Original and modified factor vectors
original_factor <- factor(c('apple', 'banana', 'cherry'))
modified_factor <- factor(c('apple_fruit', 'banana_fruit', 'cherry_fruit'))

# Create mapping table
ft_mapping(original_factor, modified_factor)

Merge Two Factors and Retain Unique Levels

Description

Merges two factor vectors into one, retaining unique levels from both factors.

Usage

ft_merge(factor_vec1, factor_vec2, level_order = NULL)

Arguments

Value

A factor vector containing the combined data from both factors with unique levels.

Author(s)

Kai Guo

Examples

# Example factor vectors
factor_vec1 <- factor(c('apple', 'banana', 'cherry'))
factor_vec2 <- factor(c('banana', 'date', 'fig', 'grape'))

# Merge factors and retain unique levels
ft_merge(factor_vec1, factor_vec2)

Merge Similar Factor Levels

Description

Merges levels of a factor that are similar based on string distance.

Usage

ft_merge_similar(factor_vec, max_distance = 1, method = "lv")

Arguments

Value

A factor vector with similar levels merged.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'appel', 'banana', 'bananna', 'cherry'))

# Merge similar levels
ft_merge_similar(factor_vec, max_distance = 1)

Handle NA Values in Factor Vectors

Description

Handles NA values in a factor vector by either keeping NA as a level or removing levels and characters corresponding to NA values.

Usage

ft_na(factor_vec, keep_na = TRUE)

Arguments

Value

A factor vector with NA values handled as specified.

Author(s)

Kai Guo

Examples

# Example factor vector with NA values
factor_vec <- factor(c('apple', NA, 'banana', 'cherry', NA, 'date'))

# Keep NA as a level
ft_na(factor_vec, keep_na = TRUE)

# Remove NA values
ft_na(factor_vec, keep_na = FALSE)

Pad Factor Levels with Leading Characters

Description

Pads each level of a factor vector with leading characters to reach a specified width.

Usage

ft_pad_levels(factor_vec, width, pad_char)

Arguments

Value

A factor vector with padded levels.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('A', 'B', 'C', 'D'))

# Pad levels to width 4 using '0' as padding character
padded_factor <- ft_pad_levels(factor_vec, width = 4, pad_char = '0')
print(levels(padded_factor))
# Output: "000A" "000B" "000C" "000D"

# Pad levels to width 6 using '%A' as padding string
padded_factor <- ft_pad_levels(factor_vec, width = 6, pad_char = '%A')
print(levels(padded_factor))
# Output: "%%A%A" "%%A%B" "%%A%C" "%%A%D"

Generate Pairwise Comparisons Between Elements in factor

Description

Creates all unique pairwise combinations between factor_vec of a vector, with options for references, symmetry, NA handling, custom filtering, and output formats. Automatically handles factors by converting them to vectors and removes extra spaces from factor_vec before processing.

Usage

ft_pairs(
  factor_vec,
  ref = NULL,
  symmetric = TRUE,
  include_na = FALSE,
  include_self = FALSE,
  filter_fn = NULL,
  pre_fn = trimws,
  sort_by = "none",
  output_format = "data.frame"
)

Arguments

Value

A data frame, list, matrix, or tibble containing pairwise comparisons between factor_vec.

Examples

# Example vector with extra spaces and mixed case
vec <- c(' A', 'b ', ' C ', 'D')

# Generate pairwise comparisons within vec
ft_pairs(vec)

# Use a custom preprocessing function to convert factor_vec to lower case
ft_pairs(vec, pre_fn = function(x) tolower(trimws(x)))
ft_pairs(vec, ref = c("A","C"))

Replace Patterns in Factor Levels (Deprecated)

Description

This function is deprecated. Please use ft_replace_pattern instead.

Usage

ft_pattern_replace(factor_vec, pattern, replacement)

Arguments

Value

A factor vector with modified levels.

Author(s)

Kai Guo

Examples

# Deprecated: Use ft_replace_pattern instead
factor_vec <- factor(c('user_123', 'admin_456', 'guest_789'))
ft_replace_pattern(factor_vec, pattern = '[0-9]+', replacement = 'ID')

Reorder Factor Levels Based on Characters at Specified Positions

Description

Reorders the levels of a factor vector based on characters extracted from specified positions within each level's name. Supports case sensitivity, descending order, and optionally reorders the data vector's elements to align with the new levels' order.

Usage

ft_pos(
  factor_vec,
  positions,
  case = FALSE,
  decreasing = FALSE,
  inplace = FALSE
)

Arguments

Value

A new factor vector with reordered levels. Depending on the inplace parameter, the data vector's elements may also be reordered.

Author(s)

Kai Guo

Examples

# Example 1: Reorder levels based on characters at positions 2 and 4
# without reordering data elements
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'fig', 'grape'))
new <- ft_pos(
  factor_vec,
  positions = c(2, 4),
  case = FALSE,
  decreasing = FALSE,
  inplace = FALSE
)
print(new)
# [1] apple  banana cherry date   fig    grape
# Levels: apple banana date cherry fig grape

# Example 2: Reorder levels based on characters at positions 2 and 4
# and reorder data elements
new_inplace <- ft_pos(
  factor_vec,
  positions = c(2, 4),
  case = FALSE,
  decreasing = FALSE,
  inplace = TRUE
)
print(new_inplace)
# [1] apple  banana date   cherry fig    grape
# Levels: apple banana date cherry fig grape

# Example 3: Reorder levels in decreasing order based on characters at
# positions 1 and 3 without reordering data elements
new_dec <- ft_pos(
  factor_vec,
  positions = c(1, 3),
  case = FALSE,
  decreasing = TRUE,
  inplace = FALSE
)
print(new_dec)
# [1] apple  banana cherry date   fig    grape
# Levels: grape fig date cherry banana apple

# Example 4: Reorder levels with case sensitivity and reorder data elements
factor_vec_case <- factor(c('Apple', 'banana', 'Cherry', 'date', 'Fig', 'grape'))
new_case <- ft_pos(
  factor_vec_case,
  positions = c(1, 2),
  case = TRUE,
  decreasing = FALSE,
  inplace = TRUE
)
print(new_case)
# [1] Apple  banana Cherry date   Fig    grape
# Levels: Apple banana Cherry date Fig grape

# Example 5: Reorder levels based on characters at positions 3, allowing
# insertion at positions beyond string length
factor_vec_short <- factor(c('go', 'dog', 'cat', 'bird'))
new_short <- ft_pos(
  factor_vec_short,
  positions = c(3),
  case = FALSE,
  decreasing = FALSE,
  inplace = FALSE
)
print(new_short)
# [1] go   dog  cat  bird
# Levels: cat dog bird go

Reorder Factor Levels Based on Regex Pattern Frequency

Description

Reorders the levels of a factor vector based on the frequency of substrings matching a regular expression.

Usage

ft_regex_freq(
  factor_vec,
  pattern,
  case = FALSE,
  decreasing = TRUE,
  inplace = TRUE
)

Arguments

Value

A factor vector with levels reordered based on the frequency of matched substrings.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'apricot', 'cherry', 'blueberry', 'blackberry', 'date'))

# Reorder based on pattern matching 'a'
ft_regex_freq(factor_vec, pattern = 'a')

# Reorder with case-sensitive matching
ft_regex_freq(factor_vec, pattern = '^[A-Z]', case = TRUE)

Remove Specified Levels from a Factor

Description

Removes specified levels from a factor vector, keeping the remaining levels and their order unchanged.

Usage

ft_remove_levels(factor_vec, levels_to_remove, remove_na = TRUE)

Arguments

Value

A factor vector with specified levels removed and remaining levels unchanged.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'fig', 'grape'))

# Remove levels 'banana' and 'date'
ft_remove_levels(factor_vec, levels_to_remove = c('banana', 'date'))

Rename Factor Levels Using Data Frame Mapping

Description

Renames the levels of a factor vector based on a mapping provided in a data frame.

Usage

ft_rename_levels(factor_vec, mapping_df)

Arguments

Value

A factor vector with levels renamed.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('A', 'B', 'C'))

# Mapping data frame
mapping_df <- data.frame(old = c('A', 'B'), new = c('Alpha', 'Beta'))

# Rename levels
ft_rename_levels(factor_vec, mapping_df)

Reorder Factor Levels Within Groups

Description

Reorders the levels of a factor vector within groups defined by another factor vector.

Usage

ft_reorder_within(factor_vec, group_vec, by, fun = mean, decreasing = FALSE)

Arguments

Value

A factor vector with levels reordered within groups.

Author(s)

Kai Guo

Examples

# Example data
data <- data.frame(
  item = factor(c('A', 'B', 'C', 'D', 'E', 'F')),
  group = factor(c('G1', 'G1', 'G1', 'G2', 'G2', 'G2')),
  value = c(10, 15, 5, 20, 25, 15)
)
data <- rbind(data, data)
# Reorder 'item' within 'group' by 'value'
data$item <- ft_reorder_within(data$item, data$group, data$value, mean)

Replace a Factor Level and Optionally Insert at Specified Position

Description

Replaces a specified level in a factor vector with a new level. If a position is provided, the new level is inserted at the specified position among the levels; otherwise, the original level order is preserved.

Usage

ft_replace(factor_vec, old_level, new_level, position = NULL)

Arguments

Value

A factor vector with the level replaced and the new level optionally inserted at the specified position.

Author(s)

Kai Guo

Examples

#
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'fig', 'grape'))

# replace 'banana' as 'blueberry', and keep original order
ft_replace(factor_vec, old_level = 'banana', new_level = 'blueberry')

# replace 'banana' as 'blueberry'
ft_replace(factor_vec, old_level = 'banana', new_level = 'blueberry', position = 2)

Replace NA Values in Factor Vector

Description

Replaces NA values in a factor vector with a specified level.

Usage

ft_replace_na(factor_vec, replacement_level)

Arguments

Value

A factor vector with NA values replaced.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', NA, 'banana', 'cherry', NA))

# Replace NAs with 'Unknown'
ft_replace_na(factor_vec, replacement_level = 'Unknown')

Replace Parts of Factor Levels Based on a Pattern

Description

Replaces parts of the factor levels that match a specified pattern with a new string.

Usage

ft_replace_pattern(factor_vec, pattern, replacement, replace_all = TRUE)

Arguments

Value

A factor vector with levels modified.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple_pie', 'banana_bread', 'cherry_cake'))

# Replace '_pie', '_bread', '_cake' with '_dessert' (all occurrences)
ft_replace_pattern(factor_vec, pattern = '_.*', replacement = '_dessert')

# Replace only the first occurrence of '_' with '-'
ft_replace_pattern(factor_vec, pattern = '_', replacement = '-', replace_all = FALSE)

Reverse Factor Levels

Description

Reverses the order of the levels in a factor vector. Optionally reorders the data vector's elements to align with the reversed levels' order.

Usage

ft_reverse(factor_vec, inplace = FALSE)

Arguments

Value

A factor vector with levels in reversed order. Depending on the inplace parameter, the data vector's elements may also be reordered.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('low', 'medium', 'high'))

# Reverse the levels without reordering data elements
reversed_factor <- ft_reverse(factor_vec)
print(reversed_factor)
# [1] low    medium high
# Levels: high medium low

# Reverse the levels and reorder data elements
reversed_factor_inplace <- ft_reverse(factor_vec, inplace = TRUE)
print(reversed_factor_inplace)
# [1] high   medium low
# Levels: high medium low

Aggregate Factor Levels Based on Grouping

Description

Aggregates the levels of a factor vector based on another grouping vector.

Usage

ft_rollup(factor_vec, groups)

Arguments

Value

A factor vector with aggregated levels.

Author(s)

Kai Guo

Examples

# Example factor vector and groups
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date', 'fig'))
groups <- c('fruit', 'fruit', 'fruit', 'dry fruit', 'dry fruit')

# Aggregate levels based on groups
ft_rollup(factor_vec, groups)

Sample Levels from a Factor Vector

Description

Randomly selects a specified number of levels from a factor vector.

Usage

ft_sample_levels(factor_vec, size, seed = NULL)

Arguments

Value

A factor vector containing only the sampled levels.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(letters[1:10])

# Sample 5 levels
ft_sample_levels(factor_vec, size = 5, seed = 123)

Sort Factor Levels Based on Another Vector or Column

Description

Sorts the levels of a factor vector based on the values of another vector or a column from a data frame. Handles cases where the sorting vector may contain ‘NA's. Optionally reorders the data vector’s elements to align with the new levels' order.

Usage

ft_sort(factor_vec, by, decreasing = FALSE, na_last = TRUE, inplace = FALSE)

Arguments

Value

A factor vector with levels sorted based on 'by'. Depending on the inplace parameter, the data vector's elements may also be reordered.

Examples

# Example using a vector without reordering data elements
factor_vec <- factor(c('apple', 'banana', 'cherry', 'date'))
by_vec <- c(2, 3, 1, NA)
sorted_factor <- ft_sort(factor_vec, by = by_vec)
print(sorted_factor)
# [1] apple  banana cherry date
# Levels: cherry apple banana date

# Example using a vector and reordering data elements
sorted_factor_inplace <- ft_sort(factor_vec, by = by_vec, inplace = TRUE)
print(sorted_factor_inplace)
# [1] cherry apple banana date
# Levels: cherry apple banana date

# Example using a data frame column without reordering data elements
data <- data.frame(
  Category = factor(c('apple', 'banana', 'cherry', 'date')),
  Value = c(2, 3, 1, NA)
)
sorted_factor_df <- ft_sort(data$Category, by = data$Value)
print(sorted_factor_df)
# [1] apple  banana cherry date
# Levels: cherry apple banana date

# Example using a data frame column and reordering data elements
sorted_factor_df_inplace <- ft_sort(data$Category, by = data$Value, inplace = TRUE)
print(sorted_factor_df_inplace)
# [1] cherry apple banana date
# Levels: cherry apple banana date

Sort Factor Levels Using a Custom Function

Description

Reorders the levels of a factor vector based on a custom function applied to each level. Optionally reorders the data vector's elements to align with the new levels' order.

Usage

ft_sort_custom(factor_vec, sort_func, decreasing = FALSE, inplace = FALSE)

Arguments

Value

A factor vector with levels reordered according to the custom function. Depending on the inplace parameter, the data vector's elements may also be reordered.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('apple', 'banana', 'cherry'))

# Sort levels by reverse alphabetical order without reordering data elements
sorted_custom <- ft_sort_custom(factor_vec, function(x) -rank(x))
print(sorted_custom)
# [1] apple  banana cherry
# Levels: cherry banana apple

# Sort levels by reverse alphabetical order and reorder data elements
sorted_custom_inplace <- ft_sort_custom(factor_vec, function(x) -rank(x), inplace = TRUE)
print(sorted_custom_inplace)
# [1] cherry banana apple
# Levels: cherry banana apple

# Sort levels by length of the level name without reordering data elements
sorted_custom_length <- ft_sort_custom(factor_vec, function(x) nchar(x))
print(sorted_custom_length)
# [1] apple  banana cherry
# Levels: apple cherry banana

# Sort levels by length of the level name and reorder data elements
sorted_custom_length_inplace <- ft_sort_custom(factor_vec, function(x) nchar(x), inplace = TRUE)
print(sorted_custom_length_inplace)
# [1] apple  cherry banana
# Levels: apple cherry banana

Split Factor Levels and Reorder Based on Specified Criteria

Description

Splits the levels of a factor vector using specified patterns or positions and reorders based on specified parts or criteria. Optionally reorders the data vector's elements to align with the new levels' order.

Usage

ft_split(
  factor_vec,
  split_pattern,
  use_pattern = NULL,
  part = 1,
  position = NULL,
  char_freq = FALSE,
  decreasing = FALSE,
  inplace = FALSE
)

Arguments

Value

A factor vector with levels reordered based on the specified conditions. Depending on the inplace parameter, the data vector's elements may also be reordered.

Author(s)

Kai Guo

Examples

# Example 1: Split by patterns '-', '_', or '|' and reorder based on the
# first part without reordering data elements
factor_vec <- factor(c('item1-sub1', 'item2_sub2', 'item3|sub3', 'item1-sub4'))
ft_split(factor_vec, split_pattern = c('-', '_', '\\|'), part = 1, inplace = FALSE)

# Example 2: Use the second pattern '_' for splitting and reorder
# data elements
ft_split(factor_vec, split_pattern = c('-', '_', '\\|'), use_pattern = 2, part = 2, inplace = TRUE)

# Example 3: Reorder based on character frequencies in the specified part
# without reordering data elements
ft_split(factor_vec, split_pattern = '-', part = 2, char_freq = TRUE, inplace = FALSE)

# Example 4: Split by pattern '-' and reorder both levels and data
# elements based on the first part
ft_split(factor_vec, split_pattern = '-', part = 1, inplace = TRUE)

Split Factor Levels into Multiple Factors

Description

Splits the levels of a factor vector into multiple factors based on a specified delimiter.

Usage

ft_split_levels(factor_vec, delimiter, names = NULL)

Arguments

Value

A data frame containing the resulting factors.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('red_large', 'blue_small', 'green_medium'))

# Split levels into two factors
ft_split_levels(factor_vec, delimiter = '_')

Reorder Factor Levels Based on Substrings

Description

Reorders the levels of a factor vector based on substrings extracted from the factor levels.

Usage

ft_sub(
  factor_vec,
  start_pos = NULL,
  end_pos = NULL,
  case = FALSE,
  decreasing = FALSE,
  inplace = TRUE
)

Arguments

Value

A factor vector with levels reordered based on the specified substring.

Author(s)

Kai Guo

Examples

# Example factor vector
factor_vec <- factor(c('Apple', 'banana', 'Cherry', 'date', 'Fig', 'grape'))

# Reorder based on substring from position 2 to 4
ft_sub(factor_vec, start_pos = 2, end_pos = 4)

# Reorder from position 3 to end, case-sensitive
ft_sub(factor_vec, start_pos = 3, case = TRUE)

Reorder Factor Levels Based on Substring Frequency

Description

Reorders the levels of a factor vector based on the frequency of substrings extracted from the data.

Usage

ft_substr_freq(
  factor_vec,
  start_pos = NULL,
  end_pos = NULL,
  case = FALSE,
  decreasing = TRUE,
  inplace = TRUE
)

Arguments

Value

A factor vector with levels reordered based on the frequency of substrings.

Author(s)

Kai Guo

Examples

# Example factor vector with multi-byte characters
factor_vec <- factor(c('apple', 'banana', 'apricot', 'cherry', 'banana', 'banana', 'date'))
# Reorder from position 2 to end
ft_substr_freq(factor_vec, start_pos = 2)
factor_vec <- factor(c('apple', 'banana', 'apricot', 'cherry', 'banana', 'banana', 'date'))
ft_substr_freq(factor_vec, start_pos = 2, end_pos=3)

Count Character Frequencies in Factor Levels (Including NA Handling)

Description

Counts the frequency of each character appearing in the levels of a factor vector, optionally including NA values, and returns a table or vector.

Usage

ft_table(factor_vec, case = FALSE, include_na = FALSE, as_table = TRUE)

Arguments

Value

A table or named vector of character frequencies.

Author(s)

Kai Guo

Examples

# Example factor vector with NA levels
factor_vec <- factor(c('apple', 'banana', NA, 'cherry', 'date', NA, 'fig', 'grape'), exclude = NULL)

# Get character frequencies (case-insensitive), excluding NA levels
ft_table(factor_vec)

# Include NA levels in the character frequencies
ft_table(factor_vec, include_na = TRUE)

Get Union of Factor Levels from Multiple Vectors

Description

Combines multiple factor vectors and returns a factor vector containing all unique levels.

Usage

ft_union(...)

Arguments

Value

A factor vector containing all unique levels from all provided factors.

Author(s)

Kai Guo

Examples

# Example factor vectors
factor_vec1 <- factor(c('apple', 'banana'))
factor_vec2 <- factor(c('banana', 'cherry'))
factor_vec3 <- factor(c('date', 'fig'))

# Get union of levels
ft_union(factor_vec1, factor_vec2, factor_vec3)

Create Factor of Unique Combinations from Multiple Factors

Description

Generates a new factor where each level represents a unique combination of levels from the input factors.

Usage

ft_unique_comb(..., sep = "_")

Arguments

Value

A factor vector representing unique combinations.

Author(s)

Kai Guo

Examples

# Example factors
factor_vec1 <- factor(c('A', 'A', 'B', 'B'))
factor_vec2 <- factor(c('X', 'Y', 'X', 'Y'))

# Create unique combinations
combined_factor <- ft_unique_comb(factor_vec1, factor_vec2)
levels(combined_factor)