11.9 Chapter 11 Review Questions
require(coursekata)
# data prep - rename
college_recent_grads$totalgrads <- college_recent_grads$total
college_recent_grads$p25th_income <- college_recent_grads$p25th
college_recent_grads$median_income <- college_recent_grads$median
college_recent_grads$p75th_income <- college_recent_grads$p75th
# create new engineering variable
college_recent_grads <- mutate(college_recent_grads, engineering = ifelse(major_category == "Engineering", "TRUE", "FALSE"))
# create STEM variable
college_recent_grads <- mutate(college_recent_grads, STEM = ifelse(major_category == "Engineering" | major_category == "Biology & Life Science" | major_category == "Computers & Mathematics" |major_category == "Physical Sciences", "TRUE", "FALSE"))
# data prep
collegegrads <- select(college_recent_grads, major, major_category, engineering, STEM, totalgrads, employed_fulltime, unemployment_rate, p25th_income, median_income, p75th_income)
collegegrads$median_income <- collegegrads$median_income/1000
# Run the following code
gf_histogram(~median_income, data = collegegrads) %>%
gf_facet_grid(STEM ~ .) %>%
gf_labs(x = "Median Income (in thousands of dollars)")CK Code: C2_Code_Review1_01
require(coursekata)
# data prep - rename
college_recent_grads$totalgrads <- college_recent_grads$total
college_recent_grads$p25th_income <- college_recent_grads$p25th
college_recent_grads$median_income <- college_recent_grads$median
college_recent_grads$p75th_income <- college_recent_grads$p75th
# create new engineering variable
college_recent_grads <- mutate(college_recent_grads, engineering = ifelse(major_category == "Engineering", "TRUE", "FALSE"))
# create STEM variable
college_recent_grads <- mutate(college_recent_grads, STEM = ifelse(major_category == "Engineering" | major_category == "Biology & Life Science" | major_category == "Computers & Mathematics" |major_category == "Physical Sciences", "TRUE", "FALSE"))
# data prep
collegegrads <- select(college_recent_grads, major, major_category, engineering, STEM, totalgrads, employed_fulltime, unemployment_rate, p25th_income, median_income, p75th_income)
collegegrads$median_income <- collegegrads$median_income/1000
# Run your code hereCK Code: C2_Code_Review1_02
require(coursekata)
# data prep - rename
college_recent_grads$totalgrads <- college_recent_grads$total
college_recent_grads$p25th_income <- college_recent_grads$p25th
college_recent_grads$median_income <- college_recent_grads$median
college_recent_grads$p75th_income <- college_recent_grads$p75th
# create new engineering variable
college_recent_grads <- mutate(college_recent_grads, engineering = ifelse(major_category == "Engineering", "TRUE", "FALSE"))
# create STEM variable
college_recent_grads <- mutate(college_recent_grads, STEM = ifelse(major_category == "Engineering" | major_category == "Biology & Life Science" | major_category == "Computers & Mathematics" |major_category == "Physical Sciences", "TRUE", "FALSE"))
# data prep
collegegrads <- select(college_recent_grads, major, major_category, engineering, STEM, totalgrads, employed_fulltime, unemployment_rate, p25th_income, median_income, p75th_income)
collegegrads$median_income <- collegegrads$median_income/1000
# Run your code hereCK Code: C2_Code_Review1_03