Torvaney

Torvaney

library(rvest)
library(stringr)

webpage <- read_html("https://en.wikipedia.org/wiki/Magic_8-Ball")

# Find the answers
answers <- 
  webpage %>% 
  html_nodes("dd") %>% 
  html_text() %>% 

Torvaney

(defn print-log
  [x]
  (do
    (if (not (nil? x)) (println x))
    x))

Torvaney

tau <- function(hg, ag, home_rates, away_rates, rho) {
  case_when(
    (hg == 0) && (ag == 0) ~ 1 - home_rates * away_rates * rho,
    (hg == 0) && (ag == 1) ~ 1 + home_rates * rho,
    (hg == 1) && (ag == 0) ~ 1 + away_rates * rho,
    (hg == 1) && (ag == 1) ~ 1 - rho,
    TRUE ~ 1
  )
}

Torvaney

# CF: www.coursera.org/learn/ml-clustering-and-retrieval/lecture/aZCHX/optional-improving-efficiency-through-multiple-tables
tibble(x = seq(0, 0.20, 0.001)) %>% 
  crossing(h = 1:4) %>% 
  mutate(single = 1 - (1-x)^h -h*x*(1-x)^(h-1),
         multiple = (1 - (1-x)^h)^(h+1),
         n_lines = h + 1) %>% 
  gather(key, value, -x, -h, -n_lines) %>% 
  ggplot(aes(x = x, y = value, 
             colour = key, group = key)) +
  geom_path() +

Torvaney

library(tidyverse)
library(rgdal)
library(plotKML)

#Set input and output directories
os50_contours_dir <- here::here("~/Downloads/contours/")
output_dir <- here::here("~/Downloads/kml/")

#Load all shapefiles in input directory
shape_filenames <- list.files(os50_contours_dir, "*line.shp")

Torvaney

library(tidyverse)

shot_counts <- read_csv(here::here("data/shot_counts.csv"))

# Interpolate points
shot_counts_tween <- shot_counts %>% 
  filter(season < 2018) %>% 
  group_by(season) %>% 
  arrange(desc(count)) %>% 
  mutate(rank = row_number()) %>% 

Torvaney

This gist contains some useful stuff for profiles.

Currently:

• bash
• R
• Visual Studio code

---

Torvaney

library(tidyverse)

stirling_formula <- function(n) sqrt(2*pi*n)*(n / exp(1))^n

x <- 1:10

breaks_log10 <- 1:10 %>% 
  map_dbl(~ 10^.x) %>% 
  map(~ .x*(1:10)) %>% 
  unlist()

Torvaney

log <- function(f, ...) {
  function_name <- as.character(substitute(f))
  
  dots <- list(...)
  args <- paste0(dots, collapse = ",")
  
  function_result <- f(...)
  print(stringr::str_glue("{function_name}({args}) -> {function_result}"))
  
  function_result