sbalci

library(tidyverse)

# Make yard size, the presence/absence of a home garden, and attitudes toward the 
# environment all correlated with each other. Home garden will be binary, so I split 
# it based on some threshold later. Attitudes toward the environment will be on a 
# scale of 1-10, so I rescale and ceiling it later

mu <- c(yard_size = 20000, home_garden = 30, attitude_env = 70)
stddev <- c(yard_size = 10000, home_garden = 15, attitude_env = 40)

sbalci

# What's the most natural way to express this code in base R?
library(dplyr, warn.conflicts = FALSE)
mtcars %>%
  group_by(cyl) %>%
  summarise(mean = mean(disp), n = n())
#> # A tibble: 3 x 3
#>     cyl  mean     n
#>   <dbl> <dbl> <int>
#> 1     4  105.    11
#> 2     6  183.     7

sbalci

## load rtweet
library(rtweet)

## store bounding box coordinates for state of nevada
nv <- c(-120.00647, 35.00186, -114.03965, 42.00221)

## initialize output vector and Midwestern 'ope' counter
s <- list()
ope <- 0L

sbalci

# theme options based on hour of day -------------------------------------------
# based on https://github.com/rstudio/rstudio/issues/1579
setHook("rstudio.sessionInit", function(chooseTheme) {
  if (chooseTheme) {
    if (format(as.POSIXct(Sys.time(), format = "%H:%M:%S"), "%H") %in% c(0:6, 20:23)) {
      if (rstudioapi::getThemeInfo()$editor != "Solarized Dark") rstudioapi::applyTheme("Solarized Dark")
    } else {
      if (rstudioapi::getThemeInfo()$editor != "Solarized Light") rstudioapi::applyTheme("Solarized Light")
    }
  }

sbalci

# Shamlessly stolen from:
# https://www.r-bloggers.com/how-to-remove-all-user-installed-packages-in-r/

# create a list of all installed packages
 ip <- as.data.frame(installed.packages())
 head(ip)
# if you use MRO, make sure that no packages in this library will be removed
 ip <- subset(ip, !grepl("MRO", ip$LibPath))
# we don't want to remove base or recommended packages either\
 ip <- ip[!(ip[,"Priority"] %in% c("base", "recommended")),]

sbalci

library("shiny")
library("foreign")

sbalci

simple_roc <- function(labels, scores){
  labels <- labels[order(scores, decreasing=TRUE)]
  data.frame(TPR=cumsum(labels)/sum(labels), FPR=cumsum(!labels)/sum(!labels), labels)
}

sbalci

How to use Gephi to visualize from Wikidata

I'm a long-time fan of the graph visualization tool Gephi and since Wikimania 2019 I got involved with Wikidata. I was aware of the Gephi plugin "Semantic Web Importer", but when I check it out, I only find old tutorials connecting to DBpedia, not Wikidata:

• "Visualising Related Entries in Wikipedia Using Gephi" by Tony Hirst, 2012-07-03
• "Let’s Play Gephi: Dbpedia, RDF, Sparql and your favorite Actors" by Matthieu Totet, 2015-10-06
• ["Gephi tutorials: Semantic Web Importer" by Matthieu

sbalci

When you use knit_expand it appears that the inclusion of the Rmd is done on the first pass, and then the complete document evaluated. This means that a Rmd block referenced in loop with knit_expand will only evaluate changing variables at their last value.

This can be worked around by passing the literal value of the variable at the time of the knit_expand with {{var}} syntax.

This is documented in the knitr_expand docs, but less clear (to an R noob like me) for embedded documents rather than strings.

sbalci

# List the jpg files in the folder

old_files <- list.files("C:/ImageTest", pattern = "*.JPG", full.names = TRUE)
old_files

# Create vector of new files

new_files <- paste0("C:/NewFiles/file_",1:length(old_files),".JPG")
new_files