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Distributes data from the Polarization in Comparative Attitudes Project. Helper functions enable data retrieval in wide and tidy formats for user-defined countries and years. Provides support for case-insensitive country names in many languages.
There are two ways to easily install this package in R. To install the stable version released to CRAN, install as normal:
install.packages("PolarCAP")
library(PolarCAP)To install the most recent development version, first ensure you have
the latest version of devtools installed:
install.packages("devtools")
library(devtools)Then, run the following code:
devtools::install_github("imehlhaff/PolarCAP")To cite PolarCAP in publications and working papers,
please use:
Mehlhaff, Isaac D. Mass Polarization across Time and Space, book manuscript (August 2023).
For BibTeX users:
@unpublished{Mehlhaff2023,
type = {Book {{Manuscript}}},
title = {Mass {{Polarization}} across {{Time}} and {{Space}}},
author = {Mehlhaff, Isaac D.},
year = {2023},
month = aug,
address = {{The University of North Carolina at Chapel Hill}}
}Most users of this package will be primarily interested in using it to easily retrieve polarization estimates for a defined set of countries and years. For example, let us take the countries and years generated by the following:
countries <- rep(c("AUS", "MEX", "USA"), each = 2)
years <- rep(c(2018, 2019), 3)
data <- as.data.frame(cbind(countries, years))One way to retrieve polarization estimates for the countries and
years generated above is to pass the vectors of countries and years to
get.PolarCAP() or melt.PolarCAP(), which
return wide and tidy data frames, respectively:
get.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"))
melt.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"))Standard errors of polarization estimates can be retrieved by adding
the optional include.se argument, which defaults to
FALSE:
get.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"), include.se = TRUE)
melt.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"), include.se = TRUE)Another way to retrieve polarization estimates for the same set of
countries and years is to return only the scalar polarization estimate
associated with each country-year. This feature is particularly useful
if a user has an imbalanced time series, would prefer to avoid merging
data frames, or is working within a dplyr pipeline:
data$ideology1 <- apply(data, 1, function(x) get.PolarCAP(countries = x[1], years = x[2], type = "ideology", value.only = TRUE))
data <- rowwise(data) %>% mutate(ideology2 = get.PolarCAP(countries = countries, years = years, type = "ideology", value.only = TRUE))
dataThe countries defined above are in ISO 3166-1 alpha-3 country code
format. This is the preferred input for *.PolarCAP().
However, these functions will accept country names in almost any
language or format and attempt to convert them to ISO3 codes by calling
to.ISO3(). *.PolarCAP() will alert the user to
any country names still unrecognized after this conversion and return
results only for those which are recognized. In addition, country codes
are case-insensitive. Thus, the following all return the same
output:
get.PolarCAP(countries = c("AUS", "MEX", "USA"), years = 2019, type = "ideology")
get.PolarCAP(countries = c("aus", "MEX", "united states"), years = 2019, type = "ideology")
get.PolarCAP(countries = c("aus", "MEX", "Stati Uniti"), years = 2019, type = "ideology")These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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