soodoku

devin-petersohn

Neurogami

Original code is from https://gist.github.com/aaronshaf/1346968

The instructions were to open a dev console and paste in the script.

A nicer way is to make it a bookmarklet.

1. Create a new bookmark in our browser.  You should be able to edit the name and URL
2. Give it a decent name (e.g. "amz cloud plaintext")
3. Paste the following as the URL (make it all one line):

soodoku

# 
# Get All Unique Domain Names from comScore
# 
# INPUT: comScore browsing data file
#
# OUTPUT: a text file containing a list of unique domains
#
# PAREMETERS:
#   + INTERNET_USAGE_FILE: path to the comScore browsing data
#   + FINAL_OUTPUT_FILE: path to intended output file

abresler

devtools::install_github("abresler/gdeltr2")
devtools::install_github("hafen/trelliscopejs")

library(gdeltr2)
library(dplyr)

asb_ocr <- "Brooklyn Nets"
gkg_codes <-
  get_codes_gkg_themes()
imageweb_codes <- get_gdelt_codebook_ft_api(code_book = "imageweb")

aparrish

johnmyleswhite

> median(FALSE)
[1] FALSE

> median(c(TRUE, FALSE))
[1] 0.5

> median(c(TRUE, FALSE, TRUE))
[1] TRUE

> f <- factor(c('a', 'b', 'c'), levels = c('a', 'b', 'c'), ordered = TRUE)

soodoku

# Read the data
sf <- read.csv("sf_tenants.csv")

# Recode 
sf$market_rates <- gsub("%", "", sapply(strsplit(sf$market_rate, " / "), "[", 2)) # market_rate
sf$rent_control_rates <- gsub("%", "", sapply(strsplit(sf$rent_control, " / "), "[", 2)) # market_rate

# Ratio of rent_control vs. rent_control 
sf$ratio <- as.numeric(sf$rent_control_rates)/as.numeric(sf$market_rates)

soodoku

# Load libs 
library(ggplot2)


# Simulate correlated data
R = matrix(cbind(1,.80, .80,1), nrow=2)
U = t(chol(R))

soodoku