Write Effective Code
What is “effective” code? The notion of effectiveness evolves as a data science project moves through the develop, deploy, and scale stages.
In Development, effectiveness is measured by the data scientist’s ability to use code to solve a problem. Code that is burdensome to maintain or not optimized to perform under demand is not effective.
The articles below offer guidance through these stages.
Featured
Learning to code in R and/or Python
When just beginning, these resources can help
Training
Posit Academy
The most effective way to learn data skills with your team
The most effective way to learn data skills with your team
Getting comfortable with your tools
No matching items
Learn new frameworks
Whether R or Python, there are new tools to add to your toolbelt
Analyses and Reports
Add interactivity or parameterization to your reports for greater flexibility
Web Applications and Dashboards
Without knowing html, javascript, or CSS, you can create powerful interactive applications and dashboards
APIs
Use APIs as a means to expose your analytics to other systems or create pipelines
No matching items
Code Smart
Be efficient with your code and your time.
Parameterization
Create a report template and customize your outputs with parameters
Break out work into reusable pieces
Utilize Automation
No matching items