Torvaney

library(tidyverse)


answers <- 
  read_csv("https://git.io/fjoZ2") %>% 
  mutate(rounded = round(pick_a_random_number_from_1_10)) %>%
  filter(!is.na(rounded))

modulo_rng <- function(n, data) {
  data %>% 

Torvaney

'''
How many turns does it take to complete a game of Concentration?
https://en.wikipedia.org/wiki/Concentration_(game)

With perfect memory and strategy, for a game of n pairs, this converges to
(approximately) 1.61n moves.
https://www.jstor.org/stable/10.4169/amer.math.monthly.120.09.787

What about with imperfect memory?
'''

Torvaney

library(tidyverse)

year <- 2019
start_date <- lubridate::date(str_glue("{year}-01-01"))  # there must be a better way??


month_colours <- c(
  "January"   = "#a5cdff",
  "February"  = "#c9e1ff",
  "March"     = "#b2edb6",

Torvaney

import os
import urllib.request

import bs4
import progressbar
import requests

URL = 'http://esperantofre.com/zagreb/zagreba.htm'
IMG_DIR = os.path.join(os.path.dirname(__file__), 'zagreba-metodo')

Torvaney

library(tidyverse)

# https://math.stackexchange.com/questions/35791/birthday-problem-expected-number-of-collisions
exp_collisions <- function(n, d) {
  n * (1 - (1 - (1 / d)) ^ (n - 1))
}

tibble(n = 1:80) %>% 
  mutate(collisions = exp_collisions(n, 365)) %>% 
  ggplot(aes(x = n, y = collisions)) +

Torvaney

library(tidyverse)
library(rvest)

url <- "https://en.wikipedia.org/wiki/List_of_minimum_annual_leave_by_country"

clean_colnames <-
  . %>% 
  str_to_lower() %>% 
  str_remove_all("\\[.*\\]") %>% 
  str_remove_all("\\(.*\\)") %>% 

Torvaney

suppressPackageStartupMessages({                                           
  library(tidyverse)                                                         
  library(sf)                                                                
})                                                                         

# c.f. http://web.mit.edu/tee/www/bertrand/problem.html                    

chord_length <- function(theta) {                                          
  2 * sin(theta / 2)                                                         
}                                                                          

Torvaney

lower_bound <- function(d) {
  (1 - sqrt(1 - 2*d)) / 2
}

upper_bound <- function(d) {
  (1 + sqrt(1 - 2*d)) / 2
}

tibble(d = seq(0, 0.5, 0.001),
       lower = lower_bound(d),

Torvaney

to_clipboard <- function(data) {
  clip <- pipe("pbcopy", "w")                       
  write.table(data, file = clip, row.names = FALSE)                               
  close(clip)
}

Torvaney

benchmark <-
  games %>%
  mutate(
    outcome = case_when(
      hgoals > agoals  ~ "home_win",
      agoals > hgoals  ~ "away_win",
      hgoals == agoals ~ "draw"
    )
  ) %>%
  count(outcome) %>%