Next Steps in the Tidyverse

Description:

The tidyverse is essential for any statistician or data scientist who deals with data on a day-to-day basis. By focusing on small key tasks, the tidyverse suite of packages removes the pain of data manipulation.

This course assumes basic familiarity with R and the tidyverse, e.g. the Mastering the tidyverse. Participants should bringtheir own laptop.

STRUCTURE:

FORCATS: FACTORS FOR THE TIDYVERSE

Factors are used to work with categorical variables, variables that have a fixed and known set of possible values. Used correctly, factors are incredibly useful. However, base R's obsession with converting everything to a factor is annoying.

BROOM: TIDYING STATISTICAL OUTPUT

broom is an attempt to bridge the gap from untidy outputs of predictions and estimations to the tidy data we want to work with. The package contains a variety of functionsthat enable output from common R functions, into a tidy format.

PURRR: A FUNCTIONAL PROGRAMMING TOOLKIT

R is a a functional programming language, e.g. the apply family. However, due to the evolution of the language,the interface has some idiosyncrasies. The purrr packages, provides a complete and consistent set of tools for working with functions and vectors.

STRINGR: STRINGS, THE BAND OF A DATA SCIENTIST'S LIFE

In almost all data cleaning tasks, manipulating strings takes centre stage. But strings aren't glamorous, and while base R can handle all tasks, it isn't always clear how to approacheach task. The stringr package provides a cohesive set of functions designed to make working with strings straightforward.

If you are interested in this course you can also contact us directly for information about how you can study at our offices for a lower price.

For more information please go to our website at Jumpingrivers.com

Cost:

375.00 + VAT

Website and registration:

https://www.eventbrite.co.uk/e/next-steps-in-the-tidyverse-tickets-50274556552

Region:

Yorkshire and Humberside

Keywords:

Data Collection, Data Quality and Data Management , Data Visualisation, Teaching and Supervising Research Methods

Related publications and presentations:

Data Collection
Data Quality and Data Management
Data Visualisation
Teaching and Supervising Research Methods

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