MattSandy

library(tidyverse)
library(jsonlite)
df <- "https://api.inc.com/rest/i5list/2021" %>%
  fromJSON() %>% 
  .$companies %>% 
  bind_rows() %>%
  unnest(article) %>%
  select(-editorsPick) %>%
  write_csv("inc.csv")

MattSandy

name,registered_voters_2020,registered_voters_2016
Aitkin,"10,840","10,090"
Anoka,"228,495","206,600"
Becker,"21,396","18,829"
Beltrami,"27,518","24,213"
Benton,"24,688","22,106"
Big Stone,"3,212","3,090"
Blue Earth,"39,978","36,184"
Brown,"16,209","15,052"
Carlton,"22,253","20,424"

MattSandy

library(tidyverse)
library(pdftools)
week <- 42
mn_counties <- c("Aitkin","Anoka","Becker","Beltrami","Benton","Big Stone","Blue Earth","Brown","Carlton","Carver","Cass","Chippewa","Chisago","Clay","Clearwater","Cook","Cottonwood","Crow Wing","Dakota","Dodge","Douglas","Faribault","Fillmore","Freeborn","Goodhue","Grant","Hennepin","Houston","Hubbard","Isanti","Itasca","Jackson","Kanabec","Kandiyohi","Kittson","Koochiching","Lac qui Parle","Lake","Lake of the Woods","Le Sueur","Lincoln","Lyon","McLeod","Mahnomen","Marshall","Martin","Meeker","Mille Lacs","Morrison","Mower","Murray","Nicollet","Nobles","Norman","Olmsted","Otter Tail","Pennington","Pine","Pipestone","Polk","Pope","Ramsey","Red Lake","Redwood","Renville","Rice","Rock","Roseau","Saint Louis","Scott","Sherburne","Sibley","Stearns","Steele","Stevens","Swift","Todd","Traverse","Wabasha","Wadena","Waseca","Washington","Watonwan","Wilkin","Winona","Wright","Yellow Medicine","Unknown/missing")
location <- paste0("https://www.health.state.mn.us/diseases/

MattSandy

// Twilio Credentials
const accountSid = "accountSid";
const authToken = "authToken";

//require the Twilio module and create a REST client
const client = require("twilio")(accountSid, authToken);
//END Twilio
const fetch = require("node-fetch");
setInterval(() => {
  check_if_available();

MattSandy

library(tidycensus)
library(tidyverse)
library(viridisLite)
library(gganimate)
library(patchwork)

us_county_population <- get_estimates(geography = "county",
                                      product = "population",
                                      shift_geo = TRUE, geometry = TRUE,
                                      year = 2018) %>%

MattSandy

MattSandy

library(tidyverse)
library(lubridate)
library(ggthemes)
library(forecast)
library(xts)
library(timetk)

future <- 7
confirmed <- read_csv("https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv")
South_Korea <- list()

MattSandy

library(tidyverse)
library(lubridate)
library(ggthemes)
library(forecast)
library(xts)
library(timetk)

future <- 7
confirmed <- read_csv("https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv")

MattSandy

library(tidyverse)
library(rvest)
library(magrittr)

# Functions ---------------------------------------------------------------

dfmd <- function(df) {
  md <- paste(names(df), collapse = " | ")
  md %<>% append(rep("---",length(names(df))) %>% paste(collapse = "|"))
  for(i in 1:nrow(df)) {

MattSandy

library(tidyverse)
library(rvest)
library(data.table)
library(quanteda)
library(magrittr)
library(ggthemes)

url <- "https://www.washingtonpost.com/" %>% 
  paste0("politics/2019/09/13/transcript-third-democratic-debate/")
transcript <- url %>% read_html %>%