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Reproducible Data Analytic
Workflows with Snakemake and `R`

Preface
I Preliminaries
1 Motivating & Rationale
2 Project Organization
II Basic Snakemake Workflows
3 Initial Steps with Snakemake
4 Working With Multiple Rules
5 Target Rules
III Minimizing Repetition, Maximizing Generalizability
6 Wildcards
- 6.1 The starting point of our Snakefile
- 6.2 Using wildcards to tidy up our code
7 Wildcards in Target Rules
8 Automating List Construction for Wildcard Expansion
IV Bringing Many Outputs Together
9 Make Tables
10 One rule to rule them all
11 Adding Papers and Slides to a Snakemake Workflow
V Decorating Snakemake Workflows
12 Logging Output and Errors
- 12.1 Logging Output
- 12.2 Logging Output and Errors in One File
  - Exercise: Logging all R Scripts
13 Adding Parameters
- 13.1 Motivating Example: Constructing a Regression Table from OLS Results
- 13.2 Creating a Rule with params
  - Exercise: Building Table 2
14 Config Files
- 14.1 The config.yaml filepath
- 14.2 Using paths from the config file
  - Exercise: Using Config Files
15 Self Documenting Help
16 Subworkflows: Divide and Conquer
- 16.1 Subworkflow Basics
- 16.2 Subworkflow dependencies
  - Exercise: More Subworkflows
  - Guided Exercise: help rules with subworkflows
VI Putting Workflows in a Box
17 Package Dependencies with renv
18 Containers
Appendix
A Installation Guide
B References
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Reproducible Data Analytic Workflows for Economics

Chapter 18 Containers