Tutorial: Animation Nodes - Solar system

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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

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.

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

hey can not be subjects in RDF triples – they are always the objects used to describe a resource.

Literals are nodes in an RDF graph, used to identify values such as numbers and dates by means of a lexical representation.

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