dplyr
Efficient data manipulation package for R
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is dplyr?
dplyr is a powerful and intuitive package in R that simplifies common data manipulation tasks, making it easier to clean, transform, and analyze datasets.
Key differentiator
“dplyr stands out as the go-to package in R for efficient and consistent data manipulation, offering a streamlined API that simplifies common tasks.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
dplyr operations can be slower compared to base R functions or data.table for extremely large datasets due to its abstraction layer.
Integration with other languages and environments outside of R requires additional configuration, which can be complex for developers unfamiliar with R.
While the basic documentation is comprehensive, it often falls short in providing detailed guidance on more sophisticated data manipulation tasks.
dplyr does not natively support distributed computing frameworks like Apache Spark, limiting its scalability for big data applications without additional tools or packages.
Fit analysis
Who is it for?
✓ Best for
Developers working with R who need to manipulate data efficiently
Data analysts looking for a consistent and powerful API for data manipulation tasks
✕ Not a fit for
Projects requiring real-time data processing or streaming capabilities
Users primarily focused on machine learning model training rather than data preparation
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with dplyr
Step-by-step setup guide with code examples and common gotchas.