Week 2 Live Session (Fall 2026)

We reviewed the week's core {dplyr} functions (select, mutate, filter, summarize, arrange), including how grouped data behaves after group_by versus the by argument. We also covered importing Excel files, fixing encoding problems in CSVs, working with projects and file paths in Positron, and common errors, then answered participants' questions.

You'll learn:

• How select, mutate, filter, summarize and arrange differ, and when to use each
• Why you must assign a pipeline to an object to change your data, and why to keep a raw copy such as penguins_raw
• How group_by leaves a data set grouped while the by argument in summarize groups only for that one operation, and how ungroup() removes grouping
• How to read Excel files with {readxl} and fix garbled characters in a CSV using guess_encoding() and the locale argument of read_csv
• How relative and absolute paths work when you open a folder as a project, and why to wrap a column range in parentheses when excluding columns with select

Resources mentioned:

• {dplyr}
• {tidyverse}
• {readxl}
• {readr}
• Positron
• RStudio
• {scales}
• {ggplot2}

Key moments:

• 00:41 Most surprising things about R so far
• 05:27 Question on how to check in about a data set
• 06:05 Participant feedback on co-working sessions
• 08:02 Why and when to use select
• 13:02 Question on recoding values with mutate
• 15:37 Question on objects versus the original CSV
• 21:42 Live demo of grouped data sets with group_by and summarize
• 26:50 Question on grouping inside summarize versus group_by
• 34:49 Importing Excel files with {readxl}
• 36:47 Fixing CSV encoding with guess_encoding
• 46:35 Absolute versus relative paths in a project
• 48:47 Windows participant on backslashes in copied paths
• 50:25 Why select needs parentheses for column ranges
• 54:46 Question on setting NA handling by default