Data Analytics Workouts

This post is a very simple display of how to use microbenchmark in R . Other sites might have longer and more detailed posts , but this post is primarily to 'spread the word' about this useful function, and show how to plot it. An alternative version of this post exists in Microsoft's Azure Notebooks, as Performance Testing Results with Microbenchmark Load Libraries Memoise as part of the code to test, microbenchmark to show usage, and ggplot2 to plot the result. library(memoise) library(microbenchmark) library(ggplot2) Create Functions Generate several functions with varied performance times, a base function plus functions that leverage vectorization and memoisation. # base function monte_carlo = function(N) { hits = 0 for (i in seq_len(N)) { u1 = runif(1) u2 = runif(1) if (u1 ^ 2 > u2) hits = hits + 1 } return(hits / N) } # memoise test function monte_carlo_memo <- memoise(mon...

Full of potential coding improvements, Efficient R Programming: A Practical Guide to Smarter Programming , the book makes two suggestions that are notable. Vectorization, explained here and here , and memoisation , caching prior results albeit with additional memory use, were relevant and significant. What follows is a demonstration of the speed improvements that might be achieved using these concepts. ################################ # performance # vectorization and memoization ################################ # clear memory between changes rm(list = ls()) #load memoise #install.packages('memoise') library(memoise) # create test function monte_carlo = function(N) { hits = 0 for (i in seq_len(N)) { u1 = runif(1) u2 = runif(1) if (u1 ^ 2 > u2) hits = hits + 1 } return(hits / N) } # memoise test function monte_carlo_memo <- memoise(monte_carlo) # vectorize function monte_carlo...

To prepare for further exploration in data analytics, and give myself some time to absorb R, I decided to work in Python for a while. For this, I worked through Computational Statistics in Python module Introduction to Python . These are some of the code produced to solve the exercises: # Tutorial Answers """http://people.duke.edu/~ccc14/sta-663/IntroductionToPythonSolutions.html""" """1. Solve the FizzBuzz problem “Write a program that prints the numbers from 1 to 100. But for multiples of three print “Fizz” instead of the number and for the multiples of five print “Buzz”. For numbers which are multiples of both three and five print “FizzBuzz”.""" def fizz_buzz(begin, end): """Write a program that prints the numbers from 1 to 100. But for multiples of three print “Fizz” instead of the number and for the multiples of five print “Buzz”. For numbers which are multi...