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################################################################################
#                                                    
# ikashnitsky.github.io 2017-06-30
# Produce an RGB coded map of pop structures at NUTS-3 level
# Ilya Kashnitsky, ilya.kashnitsky@gmail.com
#                                                  
################################################################################

# load required packages
library(tidyverse)      # data manipulation and viz

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## Helper function to preview ggplots
## thanks to @tjmahr for sharing!
ggpreview <- function (..., device = "png") {
    fname <- tempfile(fileext = paste0(".", device))
    ggplot2::ggsave(filename = fname, device = device, ...)
    system2("open", fname)
    invisible(NULL)
}  

## install pacman if you don't have it

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#' A pipable if statement
#'
#' This function allows to create an if statement that can be used within a pipable workflow
#'
#' @importFrom magrittr %>%
#' @importFrom rlang parse_expr
#' @param .data tibble
#' @param condition logical test
#' @param call a formula descibing a pipe to be evaluated if condition is \code{code}
#' @examples

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library(dplyr)

do_if <- function(.data, condition, call){
  
  if(condition){
    .x <- .data
    
    call_str <- call %>%
      as.character %>%
      .[2] 

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####-- Install/Load Packages --####

#install.packages("pacman")
pacman::p_load(tidyverse, tabulizer, lubridate)

####-- Get Intel Report and extract Tables --####

# Location of Intel Report pdf file
location <- 'https://intelligence.house.gov/uploadedfiles/20191203_-_full_report___hpsci_impeachment_inquiry_-_20191203.pdf'

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# Install these packages if you don't have them yet
# if (!require("pacman")) install.packages("pacman")
pacman::p_load(tidyverse, egg, gridExtra, grid, patchwork)


## Function to fix panel width and add "buffers" for right-alignment
## based on: https://gist.github.com/baptiste/eadeecd7d3756a7f294eb3cade8b0b17
facet_cleaner <- function(p, panel_size = 5, panel_height = 1) {
  p %>% 
    egg::set_panel_size(

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library(tidyverse)
library(lavaan)

measurement_invariance <- function(model, data, group, fit_measures) {
  
  ## Configural Model
  model1 <- cfa(model = model, data = data, group = group)
  ## Weak/metric invariance
  model2 <- cfa(model = model, data = data, group = group, group.equal=c("loadings"))
  ## Strong/scalar invariance

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library(tidyverse)
library(ggbeeswarm)
library(ggthemes)
library(glue)

elex <- read_csv("https://raw.githubusercontent.com/favstats/USElection2020-NYT-Results/master/data/latest/presidential.csv")

elex %>% 
  mutate(votes_perc = votes/sum(votes)) %>% 
  mutate(abs_margin2020 = abs(margin2020)) %>% 

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paadc_ids_2021_01_22 <- old_data%>% 
  # distinct(paadc) %>% 
  mutate(impressionTime = lubridate::ymd_hms(impressionTime)) %>% 
  group_by(paadc) %>% 
  filter(impressionTime == min(impressionTime)) %>% 
  ungroup() %>% 
  distinct(paadc, .keep_all = T)  %>%
  arrange(impressionTime) %>% 
  mutate(firstImpressionTime = as.character(impressionTime)) %>% 
  select(paadc, firstImpressionTime) %>% 

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  mutate(type = case_when(
    type == "Regio" ~ "Local Politics",
    type == "Rest" ~ "Party Youth Organization/Dutch Politicians (Other)",
    type == "Kandidaat" ~ "Dutch Politician",
    type == "Landelijk" ~ "Dutch National Party"
  ))