Programming with Data!
About This Guide
- Brenton’s Notes
Attribution
- Major Attributions
- Additional Attributions
License
Colophon
Module 00
Getting Started
- 0.1 Big Ideas
- 0.2 Course Modality
Syllabus
I Module 01
1 Welcome to Data Science
- 1.1 Module Materials
2 What is Data Science?
- 2.1 See for yourselves!
3 Meet our toolbox!
- 3.1 R and RStudio
4 Bechdel Activity
5 Thoughtful Workflow
6 R basics and workflows
7 R Scripts
- 7.1 Assign an Object
- 7.2 Types of Objects and Operations
8 Markdown
- 8.1 Markdown syntax
- 8.2 RMarkdown
9 GitHub and Version Control
10 Lab 1: Getting started with RStudio, Git, and Markdown
II Module 02
11 Plotting with ggplot2
- 11.1 Learning Objectives
- 11.2 Resources
12 Plotting in R
- 12.1 Just Plot It
13 The Grammar of Graphics
- 13.1 Example: Scatterplot grammar
- 13.2 Activity: Bar chart grammar
14 Working with ggplot2
15 Activity: Build some plots!
16 Example geoms and Plots
17 Lab 2: Global plastic waste
III Module 03
18 Wrangle yo’ data with dplyr
- 18.1 Today’s Topics
- 18.2 Resources
19 Selecting and sorting data frames
20 The pipe advantage
21 Filtering and mutating data frames
22 Grouping and summarizing data
23 Advanced dplyr functions
24 Lab 3: Explore gapminder with ggplot2 and dplyr
25 Lab 4: Personality and green reputation
- 25.1 Getting started
IV Module 04
26 Tidy Data and Pivoting
- 26.1 Orientation
27 Tidy data
- 27.1 Untidy Examples
28 Pivoting data
- 28.1 Univariate pivoting
29 Lab 5A: Univariate pivoting
- 29.1 Exercise 1: Univariate Pivoting
30 Multivariate pivoting
31 Lab 5B: Multivariate pivoting
V Module 05
32 Tibble Joins: A Tale of Two Tibbles
- 32.1 Resources
33 Join Functions
34 Lab 06: Join those tables!
VI Module 06
35 File input/output (I/O)
- 35.1 Resources
36 Filesystems and paths
37 The working directory and RStudio Projects
38 RStudio projects
39 here::here()
40 Reading data from disk
41 Import a file from the web/cloud
- 41.1 Import a CSV file from the internet
- 41.2 Import an Excel file (.xls or .xlsx) from the internet
42 Read in a sample SPSS file.
43 Saving files
- 43.1 Saving data frames
- 43.2 Saving plots
44 Organizing Your Project Folders
45 Bonus Activity: rio
46 Entering Data Manually
- 46.1 Making data.frames or tibbles
- 46.2 datapasta
47 Lab 07: Make a portfolio piece
VII Module 07
48 Text Data
49 Case Study: Martin Luther King Jr.’s Speech
- 49.1 Wrangle our text
- 49.2 Visualizing the words
50 Mining
- 50.1 Sentiment Analysis
- 50.2 Metrics of Text
51 Case Study 2: Reviews on Product
- 51.1 Contributions
- 51.2 References
VIII Module 08
52 All the plot things
53 Basic elements of ggplot
54 Changing the stat
55 Customizing plots!
56 Scales
57 Position scales
- 57.1 Arguments
58 Color scales
- 58.1 Arguments
59 Shape scales
60 Linetype scales
61 Alpha and size scales
62 Guides
63 Legend guides
- 63.1 Legend arguments
64 Axis guides
65 Hide guides
IX Module 09
66 Interactive Dashboards with flexdashboard
67 Data Stories vs Dashboards
68 Villains vs Heroes
- 68.1 Column
- 68.2 Column
69 Gender/Sexual Minority Characters
- 69.1 Row
- 69.2 Row
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Marvel Dashboard

Part 53 Basic elements of ggplot

Data
Aesthetics (mapping)
Geoms
Facets
Stats