Learn R Programming for Data Analysis | Full Beginner's Course | A to Z
👋 LESSON MATERIALS 🛑
You can access the datasets, code, quizzes and PDF notes for these lessons on our website: https://thegraphcourses.org/courses-p...
This course is for anyone interested in learning R for data analysis.
Over 9 hours of instruction, you will:
• Learn to import, clean, transform, and summarize data.
• Create elegant data visualizations using the ggplot2 package.
• Publish your work as reports and presentations.
• Apply your new data analysis skills to health data questions and beyond.
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Answers to R FOUNDATIONS LESSON 3 are here: • R coding basics | Foundations of data anal...
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Chapters:
0:00 R FOUNDATIONS 1: SETTING UP
2:05 RStudio cloud
3:55 Windows
6:37 Mac
9:43 Wrap-up
10:23 R FOUNDATIONS 2: USING RSTUDIO
13:40 Source/Editor & Data viewer
17:34 Console
18:41 Environment, History, Files, Plots, Packages, Viewer, Help
28:17 RStudio options
32:43 Cheatsheets
34:18 R FOUNDATIONS 3: CODING BASICS
36:58 Comments, sections, R as a calculator
41:39 Formatting
44:52 R Objects
1:07:00 Functions, packages, pacman
1:23:53 Wrap-up
1:25:36 R FOUNDATIONS 4: DATA DIVE
1:29:50 Intro
1:39:12 Data exploration, visdat
1:51:36 Analyze a numeric variable
2:06:38 Analyze a categorical variable
2:13:58 Question answering & why not Excel?
2:20:06 Wrap-up
2:22:19 R FOUNDATIONS 5: RSTUDIO PROJECTS
2:24:35 Rstudio Cloud
2:25:53 Set up new project
2:38:44 Export data & plots
2:50:55 Wrap-up
2:51:43 R FOUNDATIONS 6: R MARKDOWN
2:56:18 YAML metadata & output formats
3:01:36 Visual mode & Markdown syntax
3:09:20 Options menu
3:10:19 Code chunks & code chunk options
3:17:03 Global options
3:19:09 Inline R code
3:21:26 Tables & Plots
3:26:51 Further resources, Quarto
3:29:34 Example analysis
3:37:13 Wrap-up
3:39:26 R FOUNDATIONS SNIPPET: PIPES
3:40:34 Example 1: quakes data
3:49:42 Example 2: varicella data
3:57:24 DATA UNTANGLED 1 | SELECT
4:06:00 Excluding columns with !
4:09:19 Helper functions for select()
4:15:42 Change column names with rename()
4:18:27 Wrap Up
4:19:24 DATA UNTANGLED 2 | FILTER
4:24:55 Relational operators
4:28:58 Combine conditions with & and |
4:33:10 Negate conditions with !
4:37:26 NA values
4:42:16 Wrap Up
4:43:36 DATA UNTANGLED 3 | MUTATE
4:53:16 Create a Boolean variable
4:58:51 Create a numeric variable based on a formula
5:02:04 Change a variable’s type
5:05:18 Wrap up
5:06:28 DATA UNTANGLED 4 | CASE_WHEN
5:15:59 The TRUE default argument
5:18:41 Match NA’s with is.na()
5:21:02 Keep default values of a variable
5:25:30 Multiple conditions
5:35:39 Order of priority of conditions
5:47:28 Binary conditions: dplyr::if_else()
5:50:03 Wrap up
5:51:01 DATA UNTANGLED 5 | GROUP_BY & SUMMARIZE
5:57:30 Grouped summaries
6:06:53 Ungrouping
6:10:31 Counting rows
6:18:08 Include missing combinations in summaries
6:26:30 Wrap-up
6:27:53 DATA UNTANGLED 6 | OTHER GROUPED OPERATIONS
6:29:35 Arrange by group
6:35:01 Filter by group
6:40:29 Mutate by group
6:48:09 Wrap-up
6:48:58 DATA UNTANGLED 7 | PIVOTING DATA
6:55:31 Wide to long
7:01:27 Long to wide
7:06:53 Long data better for analysis?
7:15:26 Wrap up
7:16:23 DATA ON DISPLAY 1 | GGPLOT2 INTRODUCTION
7:21:16 The Grammar of Graphics
7:31:23 Modifying layers
7:34:59 Other aesthetic mappings
7:40:27 Fixed aesthetics
7:46:00 Wrap-up
7:49:27 DATA ON DISPLAY 2 | SCATTERPLOTS AND SMOOTHING
7:54:36 Modify point aesthetics
8:03:08 Set fixed aesthetics
8:11:36 Add a trend line
8:20:21 Wrap-up
8:22:30 DATA ON DISPLAY 3 | LINES, SCALES & LABELS
8:29:06 Fixed aesthetics in geom_line()
8:33:36 Map data to multiple lines
8:39:13 Modify continuous scales
8:53:04 Label plots
9:01:08 Wrap up