This week builds onto our data wrangling skills by
- dealing with different data types (factor, times, string)
Data scientists often work with different data types, and sometimes working with different data types can be difficult. Thankfully, the Tidyverse has powerful (and easy to use!) packages that make data wrangling with difficult data types much easier.
- joining data
It’s rare that a data analysis involves only a single table of data. Typically you have many tables of data, and you must combine them to answer the questions that you’re interested in. Collectively, multiple tables of data are called relational data because it is the relations, not just the individual datasets, that are important.
This module covers these basic capabilities by teaching you how to use the dplyr package and other Tidyverse to perform common data transformation and joining tasks.
Assignments
- Complete Homework #3 located in this week’s folder.
- Submit your Rmd and html report via Canvas.
- Check Canvas for homework assignment due date.
Readings
- BEFORE next session’s class, read Chapter 3, all sections, of R for Data Science.
- As you read, check your answers for the guided reading with this solutions manual.
Class
Please download the class material from canvas.
See you in class!