v-dem data in r

To work with the Varieties of Democracy (V-Dem) dataset in R, you can follow these steps:

  1. Download the V-Dem data in CSV format from the V-Dem website.
  2. Load the CSV file into R using the read.csv() function.
  3. Make sure you have the necessary packages installed (tidyverse, dplyr, broom, and janitor), as they will be useful for data wrangling and analysis.
  4. Clean and wrangle the data to suit your research question. This may involve filtering out unnecessary columns, renaming columns, and changing data types.
  5. Perform any necessary data analysis using the tidyverse and other related packages. This may include data visualization, descriptive statistics, and regression analysis.

Here is an example code block to get you started:

main.r
library(tidyverse) # Load tidyverse package
library(dplyr) # Load dplyr package
library(broom) # Load broom package
library(janitor) # Load janitor package

# Load V-Dem data
vDemData <- read.csv("path/to/vdem_data.csv")

# Clean and wrangle data
vDemDataClean <- vDemData %>%
  select(-c(country_name, country_text_id, year)) %>% # Remove unnecessary columns
  rename(country = country_name_short, region = region_name, year = `year.year`) %>% # Rename columns
  mutate_at(vars(-c(country, region, year)), as.numeric) %>% # Convert data types to numeric
  clean_names() # Clean variable names

# Perform data analysis
# For example, plot Freedom of Association by Region
vDemDataClean %>%
  group_by(region) %>%
  summarise(mean_association = mean(free_association, na.rm = TRUE)) %>%
  ggplot(aes(x = region, y = mean_association)) +
  geom_col() +
  labs(title = "Mean Freedom of Association by Region", x = "Region", y = "Mean Freedom of Association")
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