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Duration 14 hours
Course Outline
Developing Robust and Reusable R Code for Government
- Assessing elements that ensure R code is scalable, readable, and maintainable in public sector contexts
- Constructing reusable functions with precise inputs, outputs, and default parameters to support consistent operations
- Minimizing redundancy through optimized function design and structured script organization for operational efficiency
Practical Data Transformation Workflows for Government
- Establishing transparent analysis pipelines using tidyverse tools to enhance data integrity
- Executing grouped summaries, joins, and data reshaping to support comprehensive data governance
- Configuring data preparation steps to ensure repeatability and auditability of analysis
Functional Programming for Recurring Tasks
- Leveraging iteration tools as a secure alternative to repetitive loops in government systems
- Implementing map-style workflows with purrr to streamline bulk processing
- Mitigating risks associated with errors and missing values in automated task executions
Debugging and Optimizing Performance
- Identifying and resolving common coding deficiencies in scripts and functions to maintain system reliability
- Utilizing effective debugging methodologies within R and RStudio for accurate diagnostics
- Conducting performance benchmarks and applying targeted optimizations to enhance processing speed
Reproducible Reporting and Stakeholder Communication
- Generating reproducible reports using R Markdown to ensure transparency and accountability
- Enhancing visual accuracy with ggplot2 for effective communication of data insights
- Formatting analysis results for dissemination to leadership, partners, and other public sector stakeholders
Applied Workshop and Future Implementation
- Integrating functions, data workflows, debugging protocols, and reporting standards in a comprehensive exercise
- Evaluating core techniques and established patterns for routine R applications in government environments
- Determining strategic next steps for continuous improvement in R programming capabilities
Requirements
- Proficient understanding of core R syntax, data types, vectors, and data frames
- Practical experience writing scripts in R and utilizing RStudio
- Intermediate R programming proficiency, encompassing basic data manipulation and visualization
Audience
- Data analysts seeking to produce more efficient, reusable, and maintainable R code for government applications
- Data scientists requiring robust workflows for analysis, reporting, and inter-agency collaboration
- Researchers and technical professionals utilizing R for operational data management in public sector settings
Testimonials (1)
The flexible and friendly style. Learning exactly what was useful and relevant for me.
