Rasmus Bååth rasmusab

## botty-app.html
<!--
  This is a fun and friendly chatbot UI that uses the ChatGPT API.
  It features
  * A retro-styled CRT screen UI
  * A ASCII face that changes based on the bot's current emotion
  * Some light sound effects when the bot is responding
  * Persistent chat history using localStorage
  * All in one single HTML file

  To get going you need a ChatGPT API key to assign to the `openai_api_key` variable.

## hello.Rnw
\documentclass{article}
\begin{document}

<<echo=FALSE,results=tex>>=
cat('\\section{hi}\n')
@


<<echo=FALSE>>=
library(xtable)

## make-iba-cocktails-pdf-gif-datatable.R
# This script takes the scraped IBA cocktails dataset found here:
# https://github.com/rasmusab/iba-cocktails
# And produces a four page PDF with all the IBA cocktails and animated GIFs that
# loops through these, as well.

library(tidyverse)
library(glue)
library(ggtext)
library(gridExtra)

## chat-gtp-api-call.R
# How to call the new (as of 2023-03-01) ChatGTP API from R
# Get your API key over here: https://platform.openai.com/
api_key <- "sk-5-your-actual-api-key-Fvau6" # Don't share this! 😅

library(httr)
library(stringr)

# Calls the ChatGTP API with the given promps and returns the answer
ask_chatgtp <- function(prompt) {
  response <- POST(

## bowling-t-test.R
bowling_animation_urls <- c(
  "0.01" = "https://i.imgur.com/Kn8CQbj.gif",
  "0.05" = "https://i.imgur.com/HFTKdDL.gif",
  "0.1" = "https://i.imgur.com/8Sw54Mz.gif",
  "1" = "https://i.imgur.com/kjROdhj.gif"
)

# We need to download the animations to the session temp dirercorty to display
# them in the Rstudio Viever pane
bowling_animation_html <- sapply(bowling_animation_urls, function(url) {

## pokemon.csv

          
            #
            Name
            Type 1
            Type 2
            Total
            HP
            Attack
            Defense
            Sp. Atk
            Sp. Def
            Speed
            Generation
            Legendary

            
              1
              Bulbasaur
              Grass
              Poison
              318
              45
              49
              49
              65
              65
              45
              1
              False

            
              2
              Ivysaur
              Grass
              Poison
              405
              60
              62
              63
              80
              80
              60
              1
              False

            
              3
              Venusaur
              Grass
              Poison
              525
              80
              82
              83
              100
              100
              80
              1
              False

            
              3
              VenusaurMega Venusaur
              Grass
              Poison
              625
              80
              100
              123
              122
              120
              80
              1
              False

            
              4
              Charmander
              Fire
              
              309
              39
              52
              43
              60
              50
              65
              1
              False

            
              5
              Charmeleon
              Fire
              
              405
              58
              64
              58
              80
              65
              80
              1
              False

            
              6
              Charizard
              Fire
              Flying
              534
              78
              84
              78
              109
              85
              100
              1
              False

            
              6
              CharizardMega Charizard X
              Fire
              Dragon
              634
              78
              130
              111
              130
              85
              100
              1
              False

            
              6
              CharizardMega Charizard Y
              Fire
              Flying
              634
              78
              104
              78
              159
              115
              100
              1
              False

## nobel.csv
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

## get_nobel_data.R
# 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)

## tidyverse_in_a_table.R
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}"))),

## bayescamp_get_up_to_speed_with_bayes_test_script.R
# 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)
	<!--
	This is a fun and friendly chatbot UI that uses the ChatGPT API.
	It features
	* A retro-styled CRT screen UI
	* A ASCII face that changes based on the bot's current emotion
	* Some light sound effects when the bot is responding
	* Persistent chat history using localStorage
	* All in one single HTML file

	To get going you need a ChatGPT API key to assign to the `openai_api_key` variable.
	\documentclass{article}
	\begin{document}

	<<echo=FALSE,results=tex>>=
	cat('\\section{hi}\n')
	@


	<<echo=FALSE>>=
	library(xtable)
	# This script takes the scraped IBA cocktails dataset found here:
	# https://github.com/rasmusab/iba-cocktails
	# And produces a four page PDF with all the IBA cocktails and animated GIFs that
	# loops through these, as well.

	library(tidyverse)
	library(glue)
	library(ggtext)
	library(gridExtra)
	# How to call the new (as of 2023-03-01) ChatGTP API from R
	# Get your API key over here: https://platform.openai.com/
	api_key <- "sk-5-your-actual-api-key-Fvau6" # Don't share this! 😅

	library(httr)
	library(stringr)

	# Calls the ChatGTP API with the given promps and returns the answer
	ask_chatgtp <- function(prompt) {
	response <- POST(
	bowling_animation_urls <- c(
	"0.01" = "https://i.imgur.com/Kn8CQbj.gif",
	"0.05" = "https://i.imgur.com/HFTKdDL.gif",
	"0.1" = "https://i.imgur.com/8Sw54Mz.gif",
	"1" = "https://i.imgur.com/kjROdhj.gif"
	)

	# We need to download the animations to the session temp dirercorty to display
	# them in the Rstudio Viever pane
	bowling_animation_html <- sapply(bowling_animation_urls, function(url) {
#	Name	Type 1	Type 2	Total	HP	Attack	Defense	Sp. Atk	Sp. Def	Speed	Generation	Legendary
1	Bulbasaur	Grass	Poison	318	45	49	49	65	65	45	1	False
2	Ivysaur	Grass	Poison	405	60	62	63	80	80	60	1	False
3	Venusaur	Grass	Poison	525	80	82	83	100	100	80	1	False
3	VenusaurMega Venusaur	Grass	Poison	625	80	100	123	122	120	80	1	False
4	Charmander	Fire		309	39	52	43	60	50	65	1	False
5	Charmeleon	Fire		405	58	64	58	80	65	80	1	False
6	Charizard	Fire	Flying	534	78	84	78	109	85	100	1	False
6	CharizardMega Charizard X	Fire	Dragon	634	78	130	111	130	85	100	1	False
6	CharizardMega Charizard Y	Fire	Flying	634	78	104	78	159	115	100	1	False
	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
	# 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)
	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}"))),
	# 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)