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. ---- Answers to R FOUNDATIONS LESSON 3 are here:    • R coding basics | Foundations of data anal...   ---- 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