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USDavid Arenburg
primarykey
Id
3001626
data
Age
CreationDate
2013-11-17T13:11:54.087
DownVotes
1953
LastAccessDate
2018-09-01T22:59:56.327
Reputation
76373
UpVotes
5940
Views
16195
AccountId
3597339
DisplayName
David Arenburg
EmailHash
text
Location
Jerusalem, Israel
AboutMe
<a href="https://stackexchange.com/users/3597339"> <img src="https://stackexchange.com/users/flair/3597339.png" width="208" height="58" alt="profile for David Arenburg on Stack Exchange, a network of free, community-driven Q&A sites" title="profile for David Arenburg on Stack Exchange, a network of free, community-driven Q&A sites"> </a> Some rules of thumb for new R users (According to myself): <ol> <li>If you are working with <code>data.frame</code>s, forget there is a function called <code>apply</code>- whatever you do - don't use it. Especially with a margin of 1 (the only good usecase for this function is to operate over <code>matrix</code> columns- margin of 2). <ul> <li>Some good alternatives: <code>?do.call</code>, <code>?pmax/pmin</code>, <code>?max.col</code>, <code>?rowSums/rowMeans/etc</code>, the awesome <code>matrixStats</code> packages (for matrices), <code>?rowsum</code> and many more</li> </ul></li> <li>For loops are not bad- don't listen to anyone who says otherwise. They are bad only in certain cases: <ul> <li>If you use them to iterate over rows. </li> <li>If you are performing unvectorized/inefficient operation within each iteration </li> <li>If you are writing a loop for something that is already vectorized</li> </ul></li> <li>R is a vectorized language- meaning many operation were already written in C loops- so don't reinvent the wheel and write stuff in R loops if it was already written. With one exception- many of these functions work only with matrices. Hence, if you have a <code>data.frame</code> you should think twice if you want it to be converted it to a <code>matrix</code>(you may experience some unexpected consequences as a result), or can you avoid it.</li> <li>Learn base R before you learn any fancy packages such as <code>dplyr</code>. It is a nice package and all, but it was designed for very specific things. Many many operations could be done much more efficiently using base R.</li> <li>Get familiar with R classes. Learn what is <code>factor</code> and how to use it. Know the difference between a <code>matrix</code> (a vector with a <code>dim</code> attribute) and a <code>data.frame</code> (a <code>list</code> of vectors). Learn how and when to work with <code>list</code>s or <code>array</code>s. Know the difference between <code>numeric</code> and <code>integer</code>. Read about floating points.</li> <li>Learn how and when yo use <code>lapply/sapply/vapply</code> - these could come useful many times</li> <li>You must learn some <code>?regex</code>. Must.</li> <li>Read <code>?S4groupGeneric</code> in order to discover which functions have <code>data.frame</code> methods (a very useful to know).</li> <li>Learn about <code>?methods</code></li> <li>Read <code>?strptime</code> very carefully (note the <code>Sys.setlocale("LC_TIME", "C")</code> part - could be a life saver).</li> <li>Read the damn docs. R has awesome documentation- please use it. You won't find anything even nearly as good in any other language (I know of). </li> </ol> Like Barry Rowlingson once said: "This is all documented in TFM. Those who WTFM don't want to have to WTFM again on the mailing list. RTFM."
WebsiteUrl
http://www.linkedin.com/pub/david-arenburg/1a/432/9b4
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2. POctree function in party package - how to get the list of the splitting variable in a simple way
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