benmarwick

library(tidyverse)


pop_han_in_tw <- tribble(
  ~year,	~population,
  1684,	120000,
  1764,	666210,
  1782,	912920,
  1811,	1944737,

benmarwick

# reviewer pkg comes from https://ropenscilabs.github.io/reviewer/index.html
# remotes::install_github("ropenscilabs/reviewer")

browseURL(reviewer::diff_rmd("path/to/my-document.Rmd", 
                             # this gets the sha of the previous commit
                             git2r::commits(n=2)[[2]]$sha)$raw)
# result will open in a web browser

benmarwick

# starting with code from 
# https://gist.github.com/tomhopper/faa24797bb44addeba79?fbclid=IwAR3FFiHpUhTESqi_ylASZP5-zYD0lOrQyyHM2MSEvnVRCIykmjNREGTv4Uk

library(ggplot2)
library(grid)
library(dplyr)

#' Create some data to plot
n <- 100
df <- data.frame(DateTime =  seq(10, 20, length.out = 100),

benmarwick

library(tidyverse)
library(gh)

.token = ""  # get one from https://github.com/settings/tokens

# get all pkgs on GitHub mirror of CRAN
n <-  5000 # 16125 # https://github.com/cran
cran_repos <- gh("/users/:username/repos",
                 username = "cran",

benmarwick

#------------------------------------------------------
# Exploring the PCA published by Prentiss (1998) to understand the 
# usefulness of the Sullivan and Rozen debitage typology


# read in & tidy the data -----------------------------------------------
library(tidyverse)
# got these data from table 7 (p. 644) of https://www.jstor.org/stable/2694112
# OCR'd using https://tabula.technology/
prentiss <- readr::read_csv("tabula-Prentiss 1988.csv")

benmarwick

library("shiny")
library("EBImage") # >= 4.19.3
library(imager)

ui <- fluidPage(# Application title
  titlePanel("Image outline, chords, and landmarks"),
  

benmarwick

# https://arxiv.org/pdf/1809.09328.pdf & https://twitter.com/CT_Bergstrom/status/1035327464644333568
# they use Mathematica, boo! So let's make them with R

# starting with https://stackoverflow.com/q/33396168/1036500

library(ggplot2)


p <- ggplot() + 
  geom_point(data = anscombe,

benmarwick

# Summarising multiple metric attributes of artefacts

p1 <- read_excel("data/riumailuoi.xlsx", sheet = 'phase1')

summary_stats_table <- function(x) {
  x %>% 
    select(Mass, 
           Length,  
           Width,     
           Thickness,     

benmarwick

# list of lists
url <- "https://en.wikipedia.org/wiki/Lists_of_World_Heritage_Sites"

# Table of sites per country can be found at each of these pages
# probably the simplest entry point

# Africa
africa <- "https://en.wikipedia.org/wiki/List_of_World_Heritage_Sites_in_Africa"

# Americas

benmarwick

---
title: 'C14 analysis: Coastal vs Inland'
output: html_document
---

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

Import and clean the data: