svmiller

library(tidyverse)
library(stevemisc)

GSS <- readRDS("~/Dropbox/data/gss/GSS_spss-2018/gss7218.rds")

GSS %>%
  mutate(regioncondensed = NA,
         regioncondensed = ifelse(region == 8 | region == 9, "West", regioncondensed),
         regioncondensed = ifelse(region == 3 | region == 4, "Midwest", regioncondensed),
         regioncondensed = ifelse(region == 5 | region == 6 | region == 7, "South", regioncondensed),

statwonk

# install.packages("countreg", repos="http://R-Forge.R-project.org")
# https://www.fromthebottomoftheheap.net/2016/06/07/rootograms/
# https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference/countreg-Tools-for-count-data-regression
library(countreg)

rzinbinom(3e3, size = 4, mu = 20, pi = 0.05) -> x
table(x)
hist(x, col = "orange")

rootogram(glm(x ~ 1, family = "poisson")) # zeros under fit

ljanda

library(tidyverse)
library(scales)
data(diamonds)

diamonds %>% 
  filter(str_detect(cut, "Fair|Ideal")) %>% 
  ggplot(aes(price, carat)) +
  geom_point(color = "skyblue", alpha = 0.5) +
  facet_wrap(~cut, strip.position = "bottom") + 
  scale_x_continuous(labels = comma) +

andrewheiss

library(tidyverse)
library(broom)
library(huxtable)
library(estimatr)
library(fabricatr)

set.seed(1234)
dat <- fabricate(
  N = 40,

vankesteren

# script that outputs a graph
library(tidyverse)
library(firatheme)
wine <- read_delim("https://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data", 
  delim = ",",
  col_names = c(
    "Cultivar", "Alcohol", "Malic acid", "Ash", "Alcalinity of ash", "Magnesium",
    "Total phenols", "Flavanoids", "Nonflavanoid phenols", "Proanthocyanins",
    "Color intensity", "Hue", "OD280/OD315", "Proline"
  )

gaborcsardi

Run usethis::use_pkgdown_travis()

❯ usethis::use_pkgdown_travis()
✔ Setting active project to '/Users/gaborcsardi/works/ps'
✔ Adding 'docs/' to '.gitignore'
● Set up deploy keys by running `travis::use_travis_deploy()`
● Insert the following code in '.travis.yml'
  before_cache: Rscript -e 'remotes::install_cran("pkgdown")'

acoppock

rm(list = ls())
library(tidyverse)
library(ggrepel)
covid <-
  read_csv(file = "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv")

covid <-
  covid %>% filter(`Country/Region` != "Cruise Ship")

covid_long <-

clauswilke

---
title: "COVID-19 Case Fatality Rate (CFR) by age"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

library(tidyverse)
```

mikedecr

# ----------------------------------------------------
#   Installing packages for new R version.
#   Michael DeCrescenzo
#   
#   Hi, I'm a political science PhD student looking for 
#     a data science/quantitative research/statistics job.
#   Learn more at <mikedecr.github.io> and <github.com/mikedecr>
# 
#   This script deals with the following problem:
#   I upgraded to new major version of R, & I want to reinstall packages.

datalorax

library(RSelenium)
library(rvest)
library(tidyverse)
theme_set(theme_minimal(15) +
            theme(plot.title.position = "plot",
                  plot.caption = element_text(color = "gray40", size = 8)))

url <- "https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html"

rd <- rsDriver(browser = "chrome", chromever = "81.0.4044.69")