Data wrangling & tidying with Tidyverse – ONLINE

Data wrangling & tidying with Tidyverse – ONLINE

  • 14/12/2020
    9:30 am - 4:30 pm

Course details

statistics course | level: intermediate | register now
for questions related to this event, contact kuleuven@flames-statistics.com
affiliation: KU Leuven


Abstract

This one-day course (6h) gives you an introduction to the tools available to wrangle and to clean&tidy your data in R. 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 wrangling 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.

Course overview:
• Exploring raw data;
• Data wrangling;
• 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;
• Data wrangling with dplyr;
• Dates and Times with lubridate package;
• Strings with stringr package;
• Factors with forcats package;


Prerequisites

This is NOT an introduction course to R!

You MUST have a basic/fair knowledge of data handling and coding in R. No explanation of basic R programming will be given.


Background readings

Grolemund, G., & Wickham, H. (2018). R for data science.

https://r4ds.had.co.nz/


Fee

Free of charge


Venue

ONLINE. You will receive more information via email after registration.


Instructor

Cristina Cametti


Sign up (price ticket depends on affiliation)

You will receive payment details later from the organiser by email.
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