elliottmorris

#' Description
#' This file runs a live election-night forecast based on The Economist's pre-election forecasting model
#' available at projects.economist.com/us-2020-forecast/president.
#' It is resampling model based on https://pkremp.github.io/update_prob.html.
#' This script does not input any real election results! You will have to enter your picks/constraints manually (scroll to the bottom of the script).
#' 
#' Licence
#' This software is published by *[The Economist](https://www.economist.com)* under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by *The Economist* are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).
#' The licences include only the data and the software authored by *The Economist*, and do not cover any *Economist* content or third-party data or content made available using the software. More information about licensing, syndication and the copyright of *Economist* content can be fou

MattNickodemus

Setting up RStudio for Oracle pull using odbc on maxOS Catalina

1. install unixodbc using homebrew

You can install homebrew here. Once that is done, run this in the terminal.

brew install unixodbc

2. Download instant client from Oracle

johnburnmurdoch

read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv") %>%
  gather(date, cases, 5:ncol(.)) %>%
  mutate(date = as.Date(date, "%m/%d/%y")) %>%
  group_by(country = `Country/Region`, date) %>%
  summarise(cases = sum(cases)) %>%
  filter(country != "Others" & country != "Mainland China") %>%
  bind_rows(
    tibble(country = "Republic of Korea", date = as.Date("2020-03-11"), cases = 7755)
  ) %>%
  group_by(country) %>%

ovitente

---
# https://help.github.com/en/actions/automating-your-workflow-with-github-actions
# https://help.github.com/en/actions/automating-your-workflow-with-github-actions/events-that-trigger-workflows
# https://help.github.com/en/actions/automating-your-workflow-with-github-actions/workflow-syntax-for-github-actions
# https://help.github.com/en/actions/automating-your-workflow-with-github-actions/contexts-and-expression-syntax-for-github-actions
# https://help.github.com/en/actions/automating-your-workflow-with-github-actions/virtual-environments-for-github-hosted-runners
name : debug
on :
  push :
    branches : [ "master" ]

rpodcast

This app requires the shiny and xml2 packages. Run the gist interactively with the following:

shiny::runGist('6c33ee09a16d55569c562f7aa3951088')

vi

#!/bin/bash

IN=$1
OUT=$2

true ${SD_PARAMS:="-55dB:d=0.3"};
true ${MIN_FRAGMENT_DURATION:="20"};
export MIN_FRAGMENT_DURATION

if [ -z "$OUT" ]; then

thomasp85

transformers <- styler::tidyverse_style()
transformers$token$fix_quotes <- function (pd_flat) {
  str_const <- pd_flat$token == 'STR_CONST'
  str_const_change <- grepl('^"(.*)"$', pd_flat$text[str_const])
  raw_str <- sub('^"(.*)"$', '\\1', (pd_flat$text[str_const][str_const_change]))
  raw_str <- gsub('(\\\\)?\'', '\\\\\'', raw_str)
  raw_str <- gsub('\\\\"', '"', raw_str)
  pd_flat$text[str_const][str_const_change] <- paste0('\'', raw_str, '\'')
  pd_flat
}

yonicd

library(rtweet)
library(slickR) # remotes::install_github('metrumresearchgroup/slickR')

tweets <- rtweet::search_tweets("#rstats", n = 5, include_rts = FALSE)

# https://github.com/mkearney/rtweet/pull/305/files
tweet_embed <- function(screen_name,status_id,...){
  
  stem <- 'https://publish.twitter.com/oembed'
  

walkerke

library(tidycensus)
library(mapdeck)
library(tidyverse)

token <- "your mapbox token"

hv <- get_acs(geography = "tract", 
              variables = "B25077_001", 
              state = "CA", 
              geometry = TRUE) %>%

clauswilke

library(sf)
library(dplyr)
library(ggplot2)
library(gganimate) # needs development version from github

# helper function to place a geometric object at a desired position
# and scale
place_geometry <- function(geometry, position, scale = 1) {
  (geometry - st_centroid(geometry)) * scale + 
    st_sfc(st_point(position))