Problem Set 2

packages <- c("tidyverse", "fst", "modelsummary", "viridis", "kableExtra", "flextable", "officer")

new_packages <- packages[!(packages %in% installed.packages()[,"Package"])]
if(length(new_packages)) install.packages(new_packages)

lapply(packages, library, character.only = TRUE)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ lubridate 1.9.2     ✔ tidyr     1.3.0
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## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
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## [11] "dplyr"        "purrr"        "readr"        "tidyr"        "tibble"      
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## [21] "utils"        "datasets"     "methods"      "base"

gss <- load("gss2022.RData")
gss <- df

Task 1: Data Cleaning and Recoding

Objective: Clean and recode the variables to ensure they are ready for analysis. Recode polviews into three categories: “Liberal”, “Moderate”, and “Conservative”. Clean sex, degree, and race but retain the relevant categories.

gss <- gss %>%
  mutate(polviews = case_when(
    polviews %in% c("Extremely liberal", "Liberal", "Slightly liberal") ~ "Liberal",
    polviews %in% c("Moderate, middle of the road") ~ "Moderate",
    polviews %in% c("Slightly conservative", "Conservative", "Extremely conservative") ~ "Conservative",
    TRUE ~ NA_character_ 
  ))

gss <- gss %>%
  filter(!is.na(sex), !is.na(degree), !is.na(race)) %>%
  mutate(
    sex = factor(sex, levels = c("Male", "Female")),
    degree = factor(degree, levels = c("Less than high school", "High school", "Junior college", "Bachelor's", "Graduate")),
    race = factor(race, levels = c("White", "Black", "Other"))
  )