CRAN-R_RefreshPart8

This post just follows the previews refresh7.

WORKING WITH FACTORS

Factor manipulation

Examples

# gender factor

gender_vector <- c("Male", "Female", "Female", "Male", "Male")

# Define factor_gender_vector using 'factor()'

factor_gender_vector <- factor(gender_vector)

factor_gender_vector

# animal factor

animals_vector <- c("Elephant", "Giraffe", "Donkey", "Horse")

factor_animals_vector <- factor(animals_vector)

factor_animals_vector

# temperature factor

temperature_vector <- c("High", "Low", "High","Low", "Medium")

# ordered factors

factor_temperature_vector <- factor(temperature_vector, order = TRUE, levels = c("Low", "Medium", "High"))

factor_temperature_vector

# Code to form the factor vector

survey_vector <- c("M", "F", "F", "M", "M")

factor_survey_vector <- factor(survey_vector)

# Specify the levels of 'factor_survey_vector'

levels(factor_survey_vector) <- c("Female", "Male")

factor_survey_vector

# Type your code here for 'survey_vector'

summary(survey_vector)

# Type your code here for 'factor_survey_vector'

summary(factor_survey_vector)

# Male

factor_survey_vector[1]

# Female

factor_survey_vector[2]

# Create 'speed_vector'

speed_vector <- c("Fast", "Slow", "Slow", "Fast", "Ultra-fast")

speed_character_vector <- c("Slow", "Fast", "Ultra-fast")

# Add your code below

factor_speed_vector <- factor(speed_vector, order = TRUE, levels = speed_character_vector)

factor_speed_vector

# R prints automagically in the right order

summary(factor_speed_vector)

# Is data analyst 2 faster than data analyst 5?

compare_them <- factor_speed_vector[2] > factor_speed_vector[5] 

compare_them