Homework
Jaya Charlicombe
2023-11-01
Mission 1:
Launch a new R project and R markdown file. Name it “Lastname_Firstname_Project_202”. Set up your environment with packages you will use.
packages <- c("tidyverse", "modelsummary", "forcats", "RColorBrewer",
"fst", "viridis", "knitr", "rmarkdown", "ggridges", "viridis", "questionr", "flextable", "infer")
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 ──
## ✔ dplyr 1.1.3 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
## Loading required package: viridisLite
##
##
## Attaching package: 'flextable'
##
##
## The following object is masked from 'package:purrr':
##
## compose## [[1]]
## [1] "lubridate" "forcats" "stringr" "dplyr" "purrr" "readr"
## [7] "tidyr" "tibble" "ggplot2" "tidyverse" "stats" "graphics"
## [13] "grDevices" "utils" "datasets" "methods" "base"
##
## [[2]]
## [1] "modelsummary" "lubridate" "forcats" "stringr" "dplyr"
## [6] "purrr" "readr" "tidyr" "tibble" "ggplot2"
## [11] "tidyverse" "stats" "graphics" "grDevices" "utils"
## [16] "datasets" "methods" "base"
##
## [[3]]
## [1] "modelsummary" "lubridate" "forcats" "stringr" "dplyr"
## [6] "purrr" "readr" "tidyr" "tibble" "ggplot2"
## [11] "tidyverse" "stats" "graphics" "grDevices" "utils"
## [16] "datasets" "methods" "base"
##
## [[4]]
## [1] "RColorBrewer" "modelsummary" "lubridate" "forcats" "stringr"
## [6] "dplyr" "purrr" "readr" "tidyr" "tibble"
## [11] "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
## [16] "utils" "datasets" "methods" "base"
##
## [[5]]
## [1] "fst" "RColorBrewer" "modelsummary" "lubridate" "forcats"
## [6] "stringr" "dplyr" "purrr" "readr" "tidyr"
## [11] "tibble" "ggplot2" "tidyverse" "stats" "graphics"
## [16] "grDevices" "utils" "datasets" "methods" "base"
##
## [[6]]
## [1] "viridis" "viridisLite" "fst" "RColorBrewer" "modelsummary"
## [6] "lubridate" "forcats" "stringr" "dplyr" "purrr"
## [11] "readr" "tidyr" "tibble" "ggplot2" "tidyverse"
## [16] "stats" "graphics" "grDevices" "utils" "datasets"
## [21] "methods" "base"
##
## [[7]]
## [1] "knitr" "viridis" "viridisLite" "fst" "RColorBrewer"
## [6] "modelsummary" "lubridate" "forcats" "stringr" "dplyr"
## [11] "purrr" "readr" "tidyr" "tibble" "ggplot2"
## [16] "tidyverse" "stats" "graphics" "grDevices" "utils"
## [21] "datasets" "methods" "base"
##
## [[8]]
## [1] "rmarkdown" "knitr" "viridis" "viridisLite" "fst"
## [6] "RColorBrewer" "modelsummary" "lubridate" "forcats" "stringr"
## [11] "dplyr" "purrr" "readr" "tidyr" "tibble"
## [16] "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
## [21] "utils" "datasets" "methods" "base"
##
## [[9]]
## [1] "ggridges" "rmarkdown" "knitr" "viridis" "viridisLite"
## [6] "fst" "RColorBrewer" "modelsummary" "lubridate" "forcats"
## [11] "stringr" "dplyr" "purrr" "readr" "tidyr"
## [16] "tibble" "ggplot2" "tidyverse" "stats" "graphics"
## [21] "grDevices" "utils" "datasets" "methods" "base"
##
## [[10]]
## [1] "ggridges" "rmarkdown" "knitr" "viridis" "viridisLite"
## [6] "fst" "RColorBrewer" "modelsummary" "lubridate" "forcats"
## [11] "stringr" "dplyr" "purrr" "readr" "tidyr"
## [16] "tibble" "ggplot2" "tidyverse" "stats" "graphics"
## [21] "grDevices" "utils" "datasets" "methods" "base"
##
## [[11]]
## [1] "questionr" "ggridges" "rmarkdown" "knitr" "viridis"
## [6] "viridisLite" "fst" "RColorBrewer" "modelsummary" "lubridate"
## [11] "forcats" "stringr" "dplyr" "purrr" "readr"
## [16] "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
## [21] "graphics" "grDevices" "utils" "datasets" "methods"
## [26] "base"
##
## [[12]]
## [1] "flextable" "questionr" "ggridges" "rmarkdown" "knitr"
## [6] "viridis" "viridisLite" "fst" "RColorBrewer" "modelsummary"
## [11] "lubridate" "forcats" "stringr" "dplyr" "purrr"
## [16] "readr" "tidyr" "tibble" "ggplot2" "tidyverse"
## [21] "stats" "graphics" "grDevices" "utils" "datasets"
## [26] "methods" "base"
##
## [[13]]
## [1] "infer" "flextable" "questionr" "ggridges" "rmarkdown"
## [6] "knitr" "viridis" "viridisLite" "fst" "RColorBrewer"
## [11] "modelsummary" "lubridate" "forcats" "stringr" "dplyr"
## [16] "purrr" "readr" "tidyr" "tibble" "ggplot2"
## [21] "tidyverse" "stats" "graphics" "grDevices" "utils"
## [26] "datasets" "methods" "base"setwd("C:/Users/jpcha/Desktop/SOC202")
library(fst)
ess <- read_fst ("All-ESS-Data.fst")Mission 2:
Filter to your country of interest and save the dataset.
Filtering to Spain:
spain_data <- ess %>%
filter(cntry == "ES")Saving the dataset:
write_fst(spain_data, "C:/Users/jpcha/Desktop/SOC202/spain_data.fst") getwd()## [1] "C:/Users/jpcha/Desktop/SOC202/Charlicombe_Jaya_Project_202"Mission 3:
Clean your environment and load in the filtered dataset.
Cleaning the environment:
rm(list=ls()); gc()## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 1258863 67.3 2128442 113.7 2128442 113.7
## Vcells 2128849 16.3 1256994057 9590.2 1357137685 10354.2Loading in my filtered dataset:
df <- read_fst("C:/Users/jpcha/Desktop/SOC202/spain_data.fst")Mission 4:
Produce and save a data summary output.
3 variables I’m using:
ilglpst - Participated in illegal protest activities last 12 months. 1 = yes, 2 = no, 7 = refusal, 8 = don’t know, 9 = no answer.
pbldmna - Taken part in public demonstration last 12 months. 1 = yes, 2 = no, 7 = refusal, 8 = don’t know, 9 = no answer.
sgnptit - Signed petition last 12 months. 1 = yes, 2 = no, 7 = refusal, 8 = don’t know, 9 = no answer.
df$year <- NA
replacements <- c(2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, 2020)
for(i in 1:10){
df$year[df$essround == i] <- replacements[i]
}
spain_data <- df
spain_data_table_subset <- spain_data %>%
mutate(
ilglpst = ifelse(ilglpst %in% c(7, 8, 9), NA, ilglpst),
pbldmna = ifelse(pbldmna %in% c(7, 8, 9), NA, pbldmna),
sgnptit = ifelse(sgnptit %in% c(7, 8, 9), NA, sgnptit),
)
summary_table <- datasummary_skim(spain_data_table_subset %>% select(ilglpst, pbldmna, sgnptit), output = "flextable")## Warning: The histogram argument is only supported for (a) output types "default",
## "html", "kableExtra", or "gt"; (b) writing to file paths with extensions
## ".html", ".jpg", or ".png"; and (c) Rmarkdown, knitr or Quarto documents
## compiled to PDF (via kableExtra) or HTML (via kableExtra or gt). Use
## `histogram=FALSE` to silence this warning.summary_table
| Unique (#) | Missing (%) | Mean | SD | Min | Median | Max |
|---|---|---|---|---|---|---|---|
ilglpst | 3 | 91 | 2.0 | 0.1 | 1.0 | 2.0 | 2.0 |
pbldmna | 3 | 88 | 1.8 | 0.4 | 1.0 | 2.0 | 2.0 |
sgnptit | 3 | 0 | 1.7 | 0.4 | 1.0 | 2.0 | 2.0 |
spain_data_v2 <- spain_data_table_subset %>%
rename(
`Participated in illegal protest activities in last 12 months` = ilglpst,
`Participated in public demonstration in last 12 months` = pbldmna,
`Signed petition in last 12 months` = sgnptit
)summary_table_v2 <- datasummary_skim(spain_data_v2 %>% select(`Participated in illegal protest activities in last 12 months`,`Participated in public demonstration in last 12 months`, `Signed petition in last 12 months`), output = "flextable")## Warning: The histogram argument is only supported for (a) output types "default",
## "html", "kableExtra", or "gt"; (b) writing to file paths with extensions
## ".html", ".jpg", or ".png"; and (c) Rmarkdown, knitr or Quarto documents
## compiled to PDF (via kableExtra) or HTML (via kableExtra or gt). Use
## `histogram=FALSE` to silence this warning.summary_table_v2<- add_header_lines(summary_table_v2, values = "Table 1: Descriptive Statistics for outcome variables")
summary_table_v2Table 1: Descriptive Statistics for outcome variables | |||||||
|---|---|---|---|---|---|---|---|
| Unique (#) | Missing (%) | Mean | SD | Min | Median | Max |
Participated in illegal protest activities in last 12 months | 3 | 91 | 2.0 | 0.1 | 1.0 | 2.0 | 2.0 |
Participated in public demonstration in last 12 months | 3 | 88 | 1.8 | 0.4 | 1.0 | 2.0 | 2.0 |
Signed petition in last 12 months | 3 | 0 | 1.7 | 0.4 | 1.0 | 2.0 | 2.0 |
flextable::save_as_docx(summary_table_v2, path = "ip_summary_table_v2.docx",
width = 7.0, height = 7.0)Saved.
Mission 6:
Save a plot as a PDF.
avg_ilglpst_by_year <- aggregate(ilglpst ~ year + sgnptit, data=spain_data_table_subset, mean)
p1 <- ggplot(avg_ilglpst_by_year, aes(x=year, y=ilglpst, color=as.factor(sgnptit))) +
geom_line(aes(group=sgnptit)) +
labs(title="Mean of Illegal Protest Participation by Survey Year",
subtitle = "for those who signed a petition in the last 12 months vs. not in Spain",
x="Survey Year",
y="Average Illegal Protest Participation") +
scale_color_discrete(name="Signed a Petition", labels=c("No", "Yes")) +
theme_minimal()
p1## `geom_line()`: Each group consists of only one observation.
## ℹ Do you need to adjust the group aesthetic?
ggsave(filename = "plot1.pdf", plot = p1, device = "pdf", width = 6, height = 4)## `geom_line()`: Each group consists of only one observation.
## ℹ Do you need to adjust the group aesthetic?Saved.