nathania

Install native ARM R: https://cloud.r-project.org/

Install RStudio (probably preview) which is not native as of today: https://www.rstudio.com/products/rstudio/download/preview/

This blog post is helpful for getting Tensorflow working, but it is older, before the ARM version of R and the RStudio version that supports it was available.

This other blog post has specific steps outlined, but some of it has also been superseded.

nathania

# install.packages(c("here", "fs", "stringr", "purrr", "git2r"))

# to add invisibly in your R profile, open with usethis::edit_r_profile()
# then define it in an environment, e.g.
# .env <- new.env()
# .env$move_slides_to_web <- {function definition}

move_slides_to_web <- function(folder = NULL, index = NULL) {
  
  if (is.null(folder)) {

nathania

# https://community.rstudio.com/t/how-to-apply-a-plotting-function-to-a-list-of-dataframes-and-a-character-vector/26033

library(tidyverse)
library(scales)
library(naniar)


# original viz ------------------------------------------------------------

cols <- c('Good' = '#1a9641', 

nathania

ruler <- function(width = getOption("width")) {
  x <- seq_len(width)
  y <- dplyr::case_when(
    x %% 10 == 0 ~ as.character((x %/% 10) %% 10),
    x %% 5 == 0  ~ "+",
    TRUE         ~ "-"
  )
  cat(y, "\n", sep = "")
  cat(x %% 10, "\n", sep = "")
}

nathania

# `expand(df, nesting(patient, PCP), event_type)`
#   generates all unique combinations in `(patient, PCP) x event_type`.
#   That is; there will be `n_distinct(df$event_type)` rows per `patient, PCP`
#   tuple in the data
#  
#  df <- tibble(x = 1:4, y = letters[1:4]) 
# testthat::expect_equivalent(expand(df, nesting(x, y)), distinct(df, x, y)) 
# testthat::expect_equivalent(expand(df, crossing(x, y)), expand(df, x, y))

# generate all combinations of elements in a set S

nathania

plot(1:10)

nathania

# Adapted from https://stackoverflow.com/a/7267364/1036500 by Andrie de Vries

library(ggplot2)

td <- expand.grid(
  hjust=c(0, 0.5, 1),
  vjust=c(0, 0.5, 1),
  angle=c(0, 45, 90),
  text="text"
)

nathania

#!/usr/bin/env python
# numpy and biopython are required -- pip install numpy biopython

from Bio import Entrez
from Bio import Medline

MAX_COUNT = 10
TERM = 'Tuberculosis'

print('Getting {0} publications containing {1}...'.format(MAX_COUNT, TERM))

nathania

<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.4.0/css/font-awesome.min.css">
<div class="rating">
  <span><i class="fa fa-male"></i></span>
  <span><i class="fa fa-male"></i></span>
  <span><i class="fa fa-male"></i></span>
  <span><i class="fa fa-male"></i></span>
  <span><i class="fa fa-male"></i></span>
</div>

nathania

#!/usr/bin/env ruby -wKU

# Adapted from Brett Terpstra’s original “Markdown to Evernote” service (http://brettterpstra.com/a-better-os-x-system-service-for-evernote-notes-with-multimarkdown/)
# Martin Kopischke 2011 – License: Creative Commons Attribution Share-Alike (CC BY-SA) 3.0 Unported (http://creativecommons.org/licenses/by-sa/3.0/)
# Changes:	– create only one Evernote note per (Multi)Markdown input passed (instead of one per line)
#			– do not choke on shell escape characters (use Tempfile instead of shell pipe for osascript)
#			– default to MultiMarkdown 3 executable (instead of MMD 2 Perl script)
#			– make smart typography processing optional (set SMARTY to 'false' to bypass processing;
#			  note smart typography cannot be disabled in MMD 3.0 and 3.0.1
#			– handle both smart typography processing scripts (ie. SmartyPants.pl)