Read + filter · Week 06

Reading and Transforming Data with R

Bring a CSV into R, inspect its rows and columns, and use filter() to keep the observations needed for a question.

Sep 28–Oct 2Lecture 5 through filter() + Classwork 5
ImportantWeek 6 sequence
  1. Use Lecture 5 to read a CSV from a project folder or web address and inspect the resulting data frame.
  2. Use Classwork 5 to find and copy an absolute pathname for a downloaded file.
  3. Use the pipe and filter() to keep rows that meet logical conditions.

We finished Lecture 5 through filter() this week. We will continue with arrange(), distinct(), select(), and rename(), and complete Classworks 6 and 7, in Week 7.

Focus

  • CSV files and absolute versus relative paths
  • Rows, columns, observations, and variables
  • The pipe and filtering rows by condition

Prepare

  • Open Lecture 5 and Classwork 5
  • Open your section’s project in Posit Cloud
  • Download the lecture’s CSV from Brightspace

Practice

  • Read a CSV with read_csv() and inspect its data frame
  • Find and copy a downloaded file’s pathname
  • Keep rows with filter() and combine conditions

Learning targets

  • Explain what a CSV stores and how an absolute or relative pathname locates a file.
  • Use read_csv() to import a CSV from a project folder or web address.
  • Inspect a data frame’s dimensions, variable names, and values.
  • Connect steps with the pipe and use filter() to keep rows that meet a condition.
  • Combine filtering conditions with AND (& or a comma), OR (|), and NOT (!).
  • Recognize missing values and check them with is.na().

From a file to a useful data frame

Concept Plain-language meaning
CSV A plain-text table with values separated by commas.
Pathname The location of a file, written as an absolute or relative path.
Data frame A table in R with observations in rows and variables in columns.
Pipe (\|>) Pass the data from one step into the next function.
filter() Keep rows where a logical condition is TRUE.
Tip

In Posit Cloud, put custdata_rev.csv in a data folder inside your project. Then data/custdata_rev.csv is a relative pathname from the project folder.

Core pattern

custdata <- readr::read_csv("data/custdata_rev.csv")
dplyr::glimpse(custdata)

Lecture slides

TipLecture slide shortcuts

Click inside the slide preview, then use:

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  • your mouse wheel or trackpad to keep scrolling the weekly page;
  • M to open the menu;
  • F to enter fullscreen;
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Lecture 5 · Reading and Transforming Data with R · through filter()View slides in new tab

This week’s materials

Lecture 5 · Reading and Transforming Data with R — through filter()Classwork 5 · Finding and Copying an Absolute Pathname
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