Non-standard-evaluation and standard evaluation in dplyr

THIS POST IS NO LONGER ENTIRELY RELEVANT. DPLYR 0.7 HAS A SLIGHTLY DIFFERENT (AND SLIGHTLY MORE INTUITIVE) WAY OF WORKING WITH NON-STANDARD EVALUATION. EDIT: IT IS COMPLETELY DIFFERENT NOW. AND I RECOMMEND https://dplyr.tidyverse.org/. I love the dplyr package with all of its functions, however if you use normal dplyr in functions in your package r-cmd-check will give you a warning: R CMD check NOTE: No visible binding for global variable NAME OF YOUR VARIABLE 1. [Read More]

From spss to R, part 4

This is the second part of working with ggplot. We will combine the packages dplyr and ggplot to improve our workflow. When you make a visualisation you often experiment with different versions of your plot. Our workflow will be dynamic, in stead of saving every version of the plot you created, we will recreate the plot untill it looks the way you want it. In the previous lesson we worked with some build in datasets. [Read More]

Tidying your data

Introduction To make analyses work we often need to change the way files look. Sometimes information is recorded in a way that was very efficient for input but not workable for your analyses. In other words, the data is messy and we need to make it tidy. Tidy data means 1: Each variable forms a column. Each observation forms a row. Each type of observational unit forms a table. Today we will work with the DUO dataset about the number of students per program in the past 5 years 2 which was used in lesson 2 of from-spps-to-r. [Read More]

From spss to R, part 2

Introduction In this lesson we will open a .sav file in Rstudio and manipulate the data.frame. We will select parts of the file and create some simple overviews. First time with R? No problem, see lesson 1 (https://blog.rmhogervorst.nl/2016/02/20/from-spss-to-r-part1.html#introduction “From spss to R, part 1”) Download a .sav (SPSS) file I downloaded the following dataset from DUO (Dienst uitvoering onderwijs): Aantal wo ingeschrevenen (binnen domein ho). This dataset has a cc0 declaration, which means it is in the public domain and we can do anything we want with this file. [Read More]