benjamin-chan

pal <- c("#005595",  # Medium Electric Blue
         "#5E7F24",  # Sap Green           
         "#D87E1A",  # Ochre               
         "#007FAD",  # Celadon Blue        
         "#A01C3F",  # Deep Carmine        
         "#F2F2F2",  # Anti-Flash White    
         "#949494",  # Spanish Gray        
         "#606060",  # Granite Gray        
         # Sequential Blue
         "#6799BF", "#4779B1", "#005595", "#00406F", "#002B4A",

benjamin-chan

# US Census ACS 5-year API documentation: https://www.census.gov/data/developers/data-sets/acs-5year.html
# tidycensus documentation: https://walker-data.com/tidycensus/

Sys.getenv("CENSUS_API_KEY")  # load pre-installed Census API key

getACSbyZCTA <- function(lookup, table = NULL, variables = NULL, dataset = "acs5/profile", year = 2021) {
  require(magrittr)
  require(dplyr)
  require(tidyr)
  require(tidycensus)

benjamin-chan

search <- function(file, str) {
  text <- readLines(file.path(path, file), warn = FALSE)
  df <- data.frame(file = file,
                   line = 1:length(text),
                   regex = str,
                   result = grepl(str, text),
                   text)
  df[df$result == TRUE, ]
}

benjamin-chan

# Reference: https://www.bls.gov/developers/api_r.htm
library(magrittr)
library(dplyr)
library(devtools)
install_github("mikeasilva/blsAPI")  # https://github.com/mikeasilva/blsAPI
library(rjson)
library(blsAPI)

payload <- list("seriesid" = c("CUUR0000SA0L1E"),
                "startyear" = 2016,

benjamin-chan

c(rgb( 26,  26,  26, maxColorValue = 255),
  rgb( 51,  51,  51, maxColorValue = 255),
  rgb( 77,  77,  77, maxColorValue = 255),
  rgb(102, 102, 102, maxColorValue = 255),
  rgb(127, 127, 127, maxColorValue = 255),
  rgb(153, 153, 153, maxColorValue = 255),
  rgb(179, 179, 179, maxColorValue = 255),
  rgb(204, 204, 204, maxColorValue = 255),
  rgb(230, 230, 230, maxColorValue = 255))

benjamin-chan

library(magrittr)
library(dplyr)

c("Alice",
  "Bob",
  "Carol",
  "Dave") %>%
  unique() %>%
  sample(1e6, replace = TRUE) %>%
  data.frame(names = .) %>%

benjamin-chan

library(magrittr)
library(readr)
library(tidyr)
library(censusapi)

name <- "acs/acs5"  # See https://api.census.gov/data.html for list of tables for the name argument for listCensusMetadata()
vintage <- 2012

metadata <-
  listCensusMetadata(name = name, vintage = vintage) %>%

benjamin-chan

# Ref: https://en.wikipedia.org/wiki/Birthday_problem
# Ref: https://www.scientificamerican.com/article/bring-science-home-probability-birthday-paradox/
library(magrittr)
library(dplyr)
people <- 23
simulations <- 1e5
expand.grid(id = 1:people,
            sim = 1:simulations) %>%
  mutate(bday = sample(365, simulations * people, replace = TRUE)) %>%
  group_by(sim) %>%

benjamin-chan

library(magrittr)
library(dplyr)
buildSample <- function(hosp, pop = 500, samp = 100) {
  data.frame(hosp = hosp,
             id = sample(pop, samp, replace = TRUE),
             stringsAsFactors = FALSE) %>%
    mutate(z = rnorm(nrow(.)))
}
df1 <- buildSample("A")
df2 <- buildSample("B")

benjamin-chan

to bcd:continue
  start_mazegaze
end

to bcd:instructions
  cs right 90 label "every_command_will_start_with_BCD:_or_will_be_a_random_series_of_letters. wait 275 cs right 90 label "Dont_be_confused_by_this._it's_for_programming_reasons. wait 275 cs right 90 label "the_computer_will_show_you_a_maze_for_several_seconds. wait 275 cs right 90 label "then_it_will_ask_you_how_to_solve_the_maze. wait 275 cs right 90 label "Solve_it_right_or_you'll_have_to_start_over. wait 275 cs right 90 label "type_BCD:continue
end

to bcd:start
  cs bk 100 fd 160 pu fd 40 pd rt 90 fd 80 pu fd 40 pd fd 80 rt 90 fd 200 rt 90 fd 200 rt 90 fd 160 rt 90 fd 40 bk 40 rt 90 fd 80 lt 90 fd 40 lt 90 fd 80 lt 90 fd 40 rt 90 pu fd 40 rt 90 fd 80 rt 90 pd fd 160 rt 90 fd 40 pu bk 80 rt 90 pd fd 120 rt 90 fd 40 rt 90 fd 120 rt 90 fd 40 rt 90 fd 120 lt 90 fd 40 rt 90 fd 40 pu fd 40 rt 90 fd 10 pd label "s wait 375 cs