geotheory

library(tidyverse)

set.seed(7)
N = 1000
x = rnorm(N)
p = plogis(0.2*x - 0.8)
y = rbinom(N, 1, p)

tibble(x, y) %>%  
  mutate(z = cut_number(x, 5)) %>% 

geotheory

/*
 * I add this to html files generated with pandoc.
 */

html {
  font-size: 100%;
  overflow-y: scroll;
  -webkit-text-size-adjust: 100%;
  -ms-text-size-adjust: 100%;
}

geotheory

library(purrr)
library(rrapply)

# Split a data frame into a nested list using a different column for each level.
# This uses rrapply::rrapply() to avoid having to do any nested loops (map, lapply,
# for loop, whatever).

# Nested lists can be useful for avoiding searching through your data: the data
# has already been indexed in the list. This can be pretty handy for saving time 
# if you need to do lots of filtering stuff. 

geotheory

library(bit64)

twepoch <- as.integer64('1288834974657')
base <- as.integer64(2)
datacenter_id_bits <- 5
worker_id_bits <- 5
sequence_id_bits <- 12
max_datacenter_id <- 1 * base^datacenter_id_bits
max_worker_id <- 1 * base^worker_id_bits
max_sequence_id <- 1 * base^sequence_id_bits

geotheory

# Export as Text Table
aws --region XXXXXXXXX cognito-idp list-users --user-pool-id XXXXXXXXXXXXX --output table > ~/users.txt

# Export as JSON
aws --region XXXXXXXXX cognito-idp list-users --user-pool-id XXXXXXXXXXXXX --output json > ~/users.json

# Export User Pool with more than 60 users (pagination)
aws --region XXXXXXXXX cognito-idp list-users --user-pool-id XXXXXXXXXXXXX --pagination-token INCREDIBLYLONGSTRINGHERE --output json > ~/users-2.json

geotheory

var page = require('webpage').create(),
    system = require('system'),
    address;

if (system.args.length === 1) {
    console.log('Usage: phantomjs url_requests.js http://some.url.com');
    phantom.exit(1);
} else {
    address = system.args[1];
    var logUrl = function (req) {

geotheory

{"x": "dogs and cats"}

geotheory

library(sf)
library(RPostgreSQL)
dat <- data.frame(ID = 1:2,
                  long = c(-74.003234, -73.983317), 
                  lat = c(40.731863, 40.722684))
dat_sf <- st_as_sf(dat, coords = c("long", "lat"), 
                   crs = 4326, 
                   agr = "identity")
con <- dbConnect(PostgreSQL(), dbname = "mydb", host = "localhost")
st_write_db(con, dat_sf, "mydata")

geotheory

Some ggplot tutorials available online:

• H. Wickham: Official ggplot2 documentation
• H. Wickham: ggplot2 book
• W. Chang: R graphics cookbook and Cookbook for R
• Z. Ross: Beautiful plotting in R: A ggplot2 cheatsheet
• D. Koffman: Introduction to ggplot2
• R. Saccilotto: Tutorial: ggplot2
• R. Hartman: How to format plots for publication using ggplot2
• G. Williams: Visualising data with ggplot2

geotheory

--- flashall.sh
+++ (clipboard)
@@ -220,15 +220,14 @@
  flash-command --alt u-boot-env0 -D "${VARIANT_FILE}"
 
  echo "Flashing U-Boot Environment Backup"
- flash-command --alt u-boot-env1 -D "${VARIANT_FILE}" -R
+ flash-command --alt u-boot-env1 -D "${VARIANT_FILE}"
         echo "Rebooting to apply partition changes"
- dfu-wait no-prompt