DavZim

power <- function(x, power) {
  return(x^power)
}

foo <- function(x, ...) {
  cat("You just called 'foo'\n")
  power(x, ...)
}

################################################################################
# Goal of this short script is to show the basic inner workings of the
# tidyAnimatedVerbs package.


library(tidyverse)
library(gganimate)

# load all functions from the tidyAnimatedVerbs package

library(imager)          # for loading and plotting of the PNG file
library(glue)            # for string parsing
library(png)             # alternative for image loading

take_screenshot <- function(file = "screenshot.png", force_imagemagick = FALSE) {
  
  if (Sys.info()[["sysname"]] == "Linux" && 
      as.numeric(system("cat /var/log/dpkg.log | grep scrot | wc -l", intern = TRUE)) > 0 &&
      !force_imagemagick) {

library(tidyverse) # for data manipulation
library(rvest)     # for web scraping of the bundeswahlleiter
library(GGally)    # for the correlelogram

#' Downloads the data from the Bundeswahlleiter
#' 
#' @param url the url to download, used internally only as the function calls itself recursively, the url is the url for the respective page,
#' i.e., https://www.bundeswahlleiter.de/europawahlen/2019/ergebnisse/bund-99/land-2.html or
#' https://www.bundeswahlleiter.de/europawahlen/2019/ergebnisse/bund-99/land-8/kreis-8435.html

	#include <stdlib.h>
	#include <stdio.h>

	// samples the height of one structure for a given maximum height (H)
	int sample_height(int maxHeight) {
	int height = 0;
	while (rand() % 2 == 1 & height < maxHeight) {
	height++;
	}
	return height;

	# create some random data
	set.seed(123)
	x <- rpois(100, lambda = 100)

	# approach 1: hard to compare due to different aspect ratios
	hist(x, breaks = c((min(x) - 1):(1 + max(x))))
	plot(table(x), main = "Barplot of x")

	# approach 2: easier to compare
	library(dplyr)

	``` r
	library(extrafont)
	#> Registering fonts with R
	# font_install('fontcm') # try this if its not working
	suppressMessages(loadfonts())
	# check that the LM Roman fonts are installed with
	"CM Roman" %in% fonts()
	#> [1] TRUE

	# main script ============

	# set parameters for the dataset
	possible_values <- c(1:10, 99, NA)
	n_rows <- 1000
	n_cols <- 10

	col_names <- letters[1:n_cols]

	# create a matrix with the sampled data, that will be transformed into a data.frame in the next step
	mwe_matrix <- matrix(sample(possible_values, n_rows * n_cols, replace = T),
	nrow = n_rows, ncol = n_cols)

	``` r
	library(ggplot2) # data vis
	library(dplyr) # data manipulation
	#>
	#> Attaching package: 'dplyr'
	#> The following objects are masked from 'package:stats':
	#>
	#> filter, lag
	#> The following objects are masked from 'package:base':
	#>

	``` r
	library(tidyverse)

	df <- data_frame(x = 1:3, y = c("A", "B", "C"))

	df %>%
	mutate(
	new_y = case_when(
	y == "A" ~ "Alice",
	y == "B" ~ "Bob",