Part III: Data Wrangling
29
Spatial data
Statistical Computing using R and Python
Preface
Part I: Tools
1
Computer Basics
2
Setting Up Your Computer
3
RStudio’s Interface
4
Scripts and Notebooks
5
Version Control with Git
6
Reproducibility and Professional Communication
Part II: General Programming
7
Introduction to Programming
8
Variables and Basic Data Types
9
Mathematical and Logical Operators
10
Functions, Packages, and Environments
11
Data Structures
12
Matrix Calculations
13
Control Structures
14
Writing Functions
15
Debugging
16
Programming With Data
17
Other Helpful Programming Resources
Part III: Data Wrangling
18
Data Input
19
Data Visualization Basics
20
Exploratory Data Analysis
21
Data Visualization
22
Creating Good Charts
23
Data Cleaning
24
Working with Strings
25
Reshaping Data
26
Joining Data
27
Dates and Times
28
Functional Programming
29
Spatial data
Part IV: Advanced Topics
30
Simulation and Reproducibility
31
Interactive Graphics
32
Other Topics
Table of contents
29.1
References
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Part III: Data Wrangling
29
Spatial data
29
Spatial data
Published
April 30, 2025
Coming soon!
29.1
References
28
Functional Programming
Part IV: Advanced Topics