218 Matching Annotations
  1. Jun 2017
  2. Mar 2017
  3. Feb 2017
    1. Video tutorial from Jun 2016 showing how to use Hypothesis to annotate a Wikipedia page.

      It briefly shows groups and the stream, but using the old (pre-Nov 2016) Hypothesis website.

  4. Jan 2017
  5. Jun 2016
  6. Jan 2016
    1. slack-invite-script

      Much thanks to @dherbst for creating this—a very useful tool for Slack, which doesn't currently let users sign themselves up for your teams. I used this for the Digital Humanities Slack (tinyurl.com/dhslack) invite form.

      Unfortunately, I neglected to note how I did the one fiddly part when following these instructions—finding your Slack channel code—and some colleagues are now stuck on getting that part to work. I've tried to annotate these docs with more info and questions to help others use them, too.

    2. in getMyHost() fill in your slack domain

      Replace the URL in line 3 of code.js. Should take the form: yourslackteamname.slack.com

    3. fill in your slack api token

      Replace the fill_in_your_api_token in Line 8 with your token (should look like a longish number/letters)

    4. fill in the channel you want to send updates to

      I remember this part took me a bit to figure out, and now I can't remember what I did to see my Slack team's channel codes. Anyone have more specific instructions for finding your channel codes?

  7. Oct 2015
  8. Aug 2015
    1. R Grouping functions: sapply vs. lapply vs. apply. vs. tapply vs. by vs. aggregate var ados = ados || {}; ados.run = ados.run || []; ados.run.push(function () { ados_add_placement(22,8277,"adzerk794974851",4).setZone(43); }); up vote 463 down vote favorite 606 Whenever I want to do something "map"py in R, I usually try to use a function in the apply family. (Side question: I still haven't learned plyr or reshape -- would plyr or reshape replace all of these entirely?) However, I've never quite understood the differences between them [how {sapply, lapply, etc.} apply the function to the input/grouped input, what the output will look like, or even what the input can be], so I often just go through them all until I get what I want. Can someone explain how to use which one when? [My current (probably incorrect/incomplete) understanding is... sapply(vec, f): input is a vector. output is a vector/matrix, where element i is f(vec[i]) [giving you a matrix if f has a multi-element output] lapply(vec, f): same as sapply, but output is a list? apply(matrix, 1/2, f): input is a matrix. output is a vector, where element i is f(row/col i of the matrix) tapply(vector, grouping, f): output is a matrix/array, where an element in the matrix/array is the value of f at a grouping g of the vector, and g gets pushed to the row/col names by(dataframe, grouping, f): let g be a grouping. apply f to each column of the group/dataframe. pretty print the grouping and the value of f at each column. aggregate(matrix, grouping, f): similar to by, but instead of pretty printing the output, aggregate sticks everything into a dataframe.] r sapply tapply r-faq

      very useful article on apply functions in r

  9. May 2015
  10. berkelee.wordpress.com berkelee.wordpress.com
    1. Hypothes.is says its mission is to bring a new layer to the web, allowing you to annotate and share anything on the Internet. You can also see and respond to other people’s public or shared comments, creating online conversation and a system of peer review for online content. I created a quick video tutorial in Quicktime, shared above.

      Watch a quick video tutorial of hypothes.is here.

  11. Apr 2015
    1. Outside the triple, information is lost and a literal is just data without any meaning.

      That does seem to be a problem.

    2. hey can not be subjects in RDF triples – they are always the objects used to describe a resource.
    3. Literals are nodes in an RDF graph, used to identify values such as numbers and dates by means of a lexical representation.

      Yeah! At last a definition I can understand!

  12. Jan 2015
    1. Edit, Compile, Execute and Share your C, C++, Java, Python, Perl, PHP, Node.js, Javascript, HTML-5 or any project in your social networks using simple links.

      Online kodlama, tutorial tüm diller var