Running examples in 'GGally-Ex.R' failed
The error most likely occurred in:

> ### Name: ggduo
> ### Title: ggduo - A ggplot2 generalized pairs plot for two columns sets of
> ###   a data.frame
> ### Aliases: ggduo
> 
> ### ** Examples
> 
>  # small function to display plots only if it's interactive
>  p_ <- GGally::print_if_interactive
> 
>  data(baseball, package = "plyr")
> 
>  # Keep players from 1990-1995 with at least one at bat
>  # Add how many singles a player hit
>  # (must do in two steps as X1b is used in calculations)
>  dt <- transform(
+    subset(baseball, year >= 1990 & year <= 1995 & ab > 0),
+    X1b = h - X2b - X3b - hr
+  )
>  # Add
>  #  the player's batting average,
>  #  the player's slugging percentage,
>  #  and the player's on base percentage
>  # Make factor a year, as each season is discrete
>  dt <- transform(
+    dt,
+    batting_avg = h / ab,
+    slug = (X1b + 2*X2b + 3*X3b + 4*hr) / ab,
+    on_base = (h + bb + hbp) / (ab + bb + hbp),
+    year = as.factor(year)
+  )
> 
> 
>  pm <- ggduo(
+    dt,
+    c("year", "g", "ab", "lg"),
+    c("batting_avg", "slug", "on_base"),
+    mapping = ggplot2::aes(color = lg)
+  )
>  # Prints, but
>  #   there is severe over plotting in the continuous plots
>  #   the labels could be better
>  #   want to add more hitting information
>  p_(pm)
> 
> 
>  # Make a fake column that will be calculated when printing
>  dt$hit_type <- paste("hit_type:", seq_len(nrow(dt)))
> 
>  display_hit_type <- function(plot_fn, is_ratio) {
+    function(data, mapping, ...) {
+      # change the color aesthetic to fill aesthetic
+      mapping <- mapping_color_to_fill(mapping)
+ 
+      # If the y varaible is not 'hit_type', continue like normal
+      if (deparse(mapping$y) != "hit_type") {
+        p <- plot_fn(data, mapping, ...)
+        return(p)
+      }
+ 
+      # Capture any extra column names needed
+      extra_columns <- unname(unlist(lapply(
+        mapping[! names(mapping) %in% c("x", "y")],
+        deparse
+      )))
+      extra_columns <- extra_columns[extra_columns %in% colnames(data)]
+ 
+      x_name <- deparse(mapping$x)
+ 
+      # get the types of hits
+      hit_types <- c("X1b", "X2b", "X3b", "hr")
+      hit_names <- c("single", "double", "tripple", "home\nrun")
+      if (is_ratio) {
+        hit_types <- rev(hit_types)
+        hit_names <- rev(hit_names)
+      }
+ 
+      # retrieve the columns and rename them
+      data <- data[, c(x_name, hit_types, extra_columns)]
+      colnames(data) <- c(x_name, hit_names, extra_columns)
+ 
+      # melt the data to get the counts of the unique hit occurances
+      dt_melt <- reshape::melt.data.frame(data, id = c(x_name, extra_columns))
+      dt_value <- dt_melt$value
+ 
+      # Make a new data.frame with all the necessary variables repeated
+      dt_ratio <- data.frame(variable = logical(sum(dt_value)))
+      for (col in c(x_name, "variable", extra_columns)) {
+        dt_ratio[[col]] <- rep(dt_melt[[col]], dt_value)
+      }
+ 
+      # copy the old mapping and overwrite the x and y values
+      mapping_ratio <- mapping
+      mapping_ratio[c("x", "y")] <- ggplot2::aes_string(x = x_name, y = "variable")
+ 
+      # make ggplot2 object!
+      plot_fn(dt_ratio, mapping_ratio, ...)
+    }
+  }
> 
> 
>  display_hit_type_combo <- display_hit_type(ggally_facethist, FALSE)
>  display_hit_type_discrete <- display_hit_type(ggally_ratio, TRUE)
> 
>  # remove the strips, as the same information is displayed in the bottom axis area
>  pm <- ggduo(
+    dt,
+    c("year", "g", "ab", "lg"),
+    c("batting_avg", "slug", "on_base", "hit_type"),
+    columnLabelsX = c("year", "player game count", "player at bat count", "league"),
+    columnLabelsY = c("batting avg", "slug %", "on base %", "hit type"),
+    title = "Baseball Hitting Stats from 1990-1995",
+    mapping = ggplot2::aes(color = lg),
+    types = list(
+      # change the shape and add some transparency to the points
+      continuous = wrap("smooth_loess", alpha = 0.50, shape = "+"),
+      # all combinations that are continuous horizontally should have a binwidth of 15
+      comboHorizontal = wrap(display_hit_type_combo, binwidth = 15),
+      # the ratio plot should have a black border around the rects of size 0.15
+      discrete = wrap(display_hit_type_discrete, color = "black", size = 0.15)
+    ),
+    showStrips = FALSE, cardinality_threshold = NULL
+  );
> 
>  p_(pm)
> 
> 
> 
> # Example derived from:
> ## R Data Analysis Examples: Canonical Correlation Analysis.  UCLA: Statistical
> ##   Consulting Group. from http://www.ats.ucla.edu/stat/r/dae/canonical.htm
> ##   (accessed June 23, 2016).
> # "Example 1. A researcher has collected data on three psychological variables, four
> #  academic variables (standardized test scores) and gender for 600 college freshman.
> #  She is interested in how the set of psychological variables relates to the academic
> #  variables and gender. In particular, the researcher is interested in how many
> #  dimensions (canonical variables) are necessary to understand the association between
> #  the two sets of variables."
> mm <- read.csv("http://www.ats.ucla.edu/stat/data/mmreg.csv")
Warning in file(file, "rt") :
  InternetOpenUrl failed: 'Eine Umleitungsanforderung ändert eine nicht sichere in eine sichere Verbindung.'
Error in file(file, "rt") : cannot open the connection
Calls: read.csv -> read.table -> file
Execution halted