rasmusab

# Prior to the tutorial make sure that the script below runs without error on your R installation.
# You first need to install the following packages:
# install.packages(c("rstanarm", "prophet", "CausalImpact", "rstan"))

library(rstanarm)
library(prophet)
library(CausalImpact)
library(rstan)
library(ggridges)

rasmusab

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
 in 
----> 1 device_attack_result.count()
      2 
      3 
      4 

/usr/lib/spark/python/pyspark/sql/dataframe.py in count(self)
    520         2

rasmusab

rasmusab

# Prior to the tutorial make sure that the script below runs without error on your R installation.
# You first need to install the follwoing packages:
# install.packages(c("rstanarm", "prophet", "CausalImpact"))

library(rstanarm)
library(prophet)
library(CausalImpact)

# This will test that rstanarm works
# Don't be alarmed if you get a warning about "divergent transitions "

rasmusab

# A barely tested R script that takes a backgammon match in any format 
# gnubg can read, analyzes the match and returns a data frame with the analysis
# It requires that gnubg is readily available on the command line.

library(tidyverse)
library(jsonlite)
library(glue)

analyze_bg_match <- function(match_fname, match_format = "auto") {
  gnubg_analysis_fname = tempfile()

rasmusab

rasmusab

rasmusab

rasmusab

library(tidyverse)
library(purrr)
library(rstan)

### Defining the data ###
#########################
bumblebees <- c(1, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
                1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
                0, 0, 1, 0, 0, 0, 0, 0, 0)
toddler_steps <- c(26, 16, 37, 101, 12, 122, 90, 55, 56, 39, 55, 15, 45, 8)

rasmusab

# fuzzycolor() takes a vector of color names and matches it against the
# xkcdcolors list of color names using edit distance. fuzzycolor() always
# returns a vector of hex color strings, perhaps the ones you wanted...
fuzzycolor <- function(color_names) {
  library(xkcdcolors)
  names_distance <- adist(color_names, xcolors(), ignore.case = TRUE, partial = TRUE)
  xkcd_colors <- xcolors()[ apply(names_distance, 1, which.min) ]
  hex_colors <- name2color(xkcd_colors)
  names(hex_colors) <- xkcd_colors
  hex_colors