#Counting loop in r how to
#Counting loop in r code

#Counting loop in r code

You immediately see this is rather tedious: you repeat the same code chunk over and over. You can do this as follows: print(paste('The year is', 2010)) Suppose you want to do several printouts of the following form: The year is where is equal to 2010, 2011, up to 2015. LetвЂ™s get back to the conceptual meaning of a loop. If you want to learn more on the concepts of vectorization in R, this is a good read.

#Counting loop in r how to

Nevertheless, as a beginner in R, it is good to have a basic understanding of loops and how to write them. For example, solutions that make use of loops are less efficient than vectorized solutions that make use of apply functions, such as lapply and sapply. Simply put, this allows for much faster calculations. Learning to count in R, whether it be a categorical variable, for example animal species or new column names, can help improve the return value of your data analysis, and the summary statistic output that this type of function provides can help you create a graph, identify a specific value, calculate the correlation coefficient, or even find. Why? Well, thatвЂ™s because R supports vectorization. When surfing on the web youвЂ™ll often read that one should avoid making use of loops in R. Sounds weird? No worries, it will become more clear once we start working with some examples below.Д«efore you dive into writing loops in R, there is one important thing you should know. They allow you to automate parts of your code that are in need of repetition. It is aimed at beginners, and if youвЂ™re not yet familiar with the basic syntax of the R language we recommend you to first have a look at this introductory R tutorial.Д¬onceptually, a loop is a way to repeat a sequence of instructions under certain conditions. How much did I spend in total? How much did I spend on each drink? aggregate does the job for this kind of figuring.In this tutorial we will have a look at how you can write a basic for loop in R. Just tell count which data frame youвЂ™re using, then which columns you want to tally by, and it does the counting very quickly and efficiently. How many times did each person drink each drink? To say you want to tally things up by more than one column use the c function to combine things into a vector: > count ( bevs, c ( 'name', 'drink' )) name drink freq 1 Bill cocoa 2 2 Bill coffee 2 3 Llib tea 2 4 Llib water 2 How many times does each name occur? > count ( bevs, 'name' ) name freq 1 Bill 4 2 Llib 4 Hmm! But there are examples at the bottom, and like all R documentation, you can just run then and look at what happens, which will probably explain everything. > library ( plyr ) > ? countД®quivalent to вЂas.ame(table(x))вЂ™, but does not include Now, like a lot of R functions, the count help page is a bit intimidating. How many times does each name occur? ThatвЂ™s just basic counting, which is easy with the count function from Hadley WickhamвЂ™s excellent plyr package.

R does that automatically and itвЂ™s very useful.) (Note how I specified two names and four drinks, but they repeated themselves to fill up the eight lines to equal the size of the cost sequence I specified.

For example, letвЂ™s say my antimatter equivalent Llib and I have been drinking some repetitive yet oddly priced beverages: > bevs bevs $ cost bevs name drink cost 1 Bill coffee 1 2 Llib tea 2 3 Bill cocoa 3 4 Llib water 4 5 Bill coffee 5 6 Llib tea 6 7 Bill cocoa 7 8 Llib water 8 I often want to count things in data frames.

A short post about counting and aggregating in R, because I learned a couple of things while improving the work I did earlier in the year about analyzing reference desk statistics.