13 Matching Annotations
  1. May 2024
    1. AI-powered code generation tools like GitHub Copilot make it easier to write boilerplate code, but they don’t eliminate the need to consult with your organization’s domain experts to work through logic, debugging, and other complex problems.Stack Overflow for Teams is a knowledge-sharing platform that transfers contextual knowledge validated by your domain experts to other employees. It can even foster a code generation community of practice that champions early adopters and scales their learnings. OverflowAI makes this trusted internal knowledge—along with knowledge validated by the global Stack Overflow community—instantly accessible in places like your IDE so it can be used alongside code generation tools. As a result, your teams learn more about your codebase, rework code less often, and speed up your time-to-production.
  2. Feb 2024
    1. Then I gave the question a longer, more descriptive title: I made it an actual question (with a question mark and everything), and replaced the term "lazy evaluation" with a more concrete description. The goal is to make the question more recognizable and more searchable. Hopefully this way, people who need this information have a better chance of finding it with a search engine; people who click through to it from a search page (either on Stack Overflow or from external search) will take less time to verify that it's the question they're trying to answer; and other curators will be able to close duplicates more quickly and more accurately. This edit also improves visibility for some related questions (and I made similar changes elsewhere to promote this one appropriately).
  3. Nov 2022
  4. Jun 2022
  5. Jan 2022
  6. Jun 2021
    1. Hard disagree - they weren't nobodies, Naspers was already a media juggernaut by 2001 (print and TV).

      ultra sad imminent spiritual demise of #StackOverflow incoming. one of the world's most treasured, vital common resources. i hope there are scrapes.

  7. Nov 2019
  8. Oct 2019
  9. Aug 2019
  10. Mar 2016
    1. Overall, there's a strong correlation between job satisfaction and pushing code into production. 65% of developers who never check in code are satisfied at their jobs vs. 77% satisfaction rate among developers who commit code multiple times per day. Developers want to code! (Or maybe happy developers just commit more than everyone else.)
  11. 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