29 Apr Importing & Tidying Data in R
10:00 am - 5:00 pm
statistics course | level: intermediate
registrations and venue via KU Leuven
This one-day course (6h) gives you an introduction to the tools available to importing and to clean&tidy your data in R. Indeed, it is important to become familiar with the data cleaning process and all of the tools available to improve your datasets. This course provides a basic introduction to importing and cleaning data in R using ‘tidyverse’, which is a collection of several R packages designed for data science.
In the final part, you will put into practice what you've learned during the course to be able to import and to clean your own messy dataset.
If you don’t have your own messy database, an example of messy dataset will be provided for you to practice.
• how to read CSV and text files in R;
• how to import flat file data with readr and data.table packages;
• how to read XLS files in R using readxl and gdata packages;
• Different types of data formats:
• How to import data from relational database & statistical software (SAS, STATA, SPSS).
Cleaning Data – general process:
• Exploring raw data;
• Data cleaning process;
• Visualize your data;
• Preparing data for analysis;
• Practical session -> cleaning your own (or provided) messy database.
More specifically, we will dig into several ‘tidy tools’:
• Tibbles with tibble package;
• Dates and Times with lubridate package;
• Strings with stringr package;
• Relational data with dplry package.
This is NOT an introduction course to R!
You need to have a basic knowledge of data handling and coding in R. No explanation of basic R programming will be given. If you have no idea what the following commands mean, the course is too advanced for you:
mydata <- read.table (“c:/temp/rawdata.txt”,header=T, dec=”,”)
Van den Heuvelinstituut (VHI)
PC class F1 – 01.24
The colloquium is organized in a PC Class. However, participants can bring their own laptop with a recent version of R & RStudio installed.
PhD's or postdocs of a Flemish university: free of charge
Other academics: 60 €
Non-profit/Public sector: 100 €
Private sector: 200 €