Author and Project: – Author: XAVIER CAPDEPON – Xavier was a student of the Data Science Bootcamp#2 (B002) – Data Science, Data Mining and Machine Learning –

When psychology researchers switch from SPSS to R a common first question is "Can I load SPSS data in R?". The answer is yes, and it's now easier than ever thanks to the Haven package which both reads and writes SPSS files. Previously, you might have used the foreign library and the read.spss command - I don't...

by Andrie de Vries A few days ago I received an unexpected parcel in my letterbox. To my delight, it turned out to be a translation into Simplified Chinese of R for Dummies, co-authored by myself and Joris Meys. Let me clarify: Joris and I wrote the book, but were not involved in the translation at all. The Wiley...

In the (http://rforpublichealth.blogspot.com/2015/03/basics-of-lists.html), I went over the basics of lists, including constructing, manipulating, and converting lists to other classes. Knowing the basics, in this post, we'll use the **apply()** functions to see just how powerful working with lists can be. I've done two posts on apply for dataframes and matrics, (http://rforpublichealth.blogspot.com/2012/09/the-infamous-apply-function.html) and (http://rforpublichealth.blogspot.com/2013/10/loops-revisited-how-to-rethink-macros.html), so give those a...

by Ari Lamstein, consultant specializing in software engineering and data analysis and author of the free email course Learn to Map Census Data in R. One of my favorite things about R is that it allows me to follow up on interesting news stories. Consider this interview on EconTalk about the history of fracking in America. Russ Roberts interviewed...

Don’t get me wrong, it’s certainly a great tool for presenting your code or even reporting, but everytime I use it for explorative, interactive data science, I keep switching to other tools quite quickly and wonder why I am still even trying to use it. I just mostly end up with messy, broken, “ungitable” and unreadable analyses and I...

Last time we have discussed the two formats of longitudinal data and visualised the individual growth trajectories using an imaginary randomised controlled trial data-set. But could we estimate the overall trajectory of the outcomes along time and see if it’s increasing, decreasing, or stable? Yes, of course, we could estimate that in multilevel growth models

I wasn’t happy with my visualisation of individual incomes from the New Zealand income survey. Because it used a logarithmic scale to improve readability, in effect all zero and negative values are excluded from the data. Whenever I throw out data, my tail goes bushy… there has to be a better way. Those zero and...

I enjoy doing new tunes; it gives me a little bit to perk up, to pay a little bit more attention (Earl Scruggs, American musician) I recently finished reading The Signal and the Noise, a book by Nate Silver, creator of the also famous FiveThirtyEight blog. The book is a very good reading for all … Continue reading...

Bar charts are a pretty common way to represent data visually, but constructing them isn’t always the most intuitive thing in the world. One way that we can construct these graphs is using R’s default packages. Barplots using base R Let’s start by viewing our dataframe: here we will be finding the mean miles per

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