rasmusab

year,category,prize,motivation,prize_share,laureate_id,laureate_type,full_name,birth_date,birth_city,birth_country,gender,organization_name,organization_city,organization_country,death_date,death_city,death_country
1901,Chemistry,The Nobel Prize in Chemistry 1901,in recognition of the extraordinary services he has rendered by the discovery of the laws of chemical dynamics and osmotic pressure in solutions,1/1,160,Individual,Jacobus H. van 't Hoff,1852-08-30,Rotterdam,the Netherlands,male,Berlin University,Berlin,Germany,1911-03-01,Berlin,Germany
1901,Literature,The Nobel Prize in  Literature 1901,"in special recognition of his poetic composition, which gives evidence of lofty idealism, artistic perfection and a rare combination of the qualities of both heart and intellect",1/1,569,Individual,Sully Prudhomme,1839-03-16,Paris,France,male,NA,NA,NA,1907-09-07,Châtenay,France
1901,Medicin,The Nobel Prize in Physiology or Medicine 1901,"for his work on serum therapy, especially its application against diphtheria, b

rasmusab

# This R script pulls down information on all Nobel prize winners
# from the official Nobel Prize API and selects a subset of this 
# information that is then saves to a CSV-file.
# By Rasmus Bååth, 2020, in the public domain.

library(tidyverse)
library(httr)

nobel_response <- GET("http://api.nobelprize.org/2.0/laureates?limit=100000&format=json")
nobel_raw <- as_tibble(content(nobel_response, simplifyVector = TRUE, flatten = TRUE)$laureates)

rasmusab

library(DT)
library(glue)
library(tidyverse)

package_names <- tidyverse:::core

tidyverse_functions <- map_dfr(package_names, function(package_name) {
  tibble(
    Package = package_name,
    Function = as.character(lsf.str(glue("package:{Package}"))),

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