Lean Analytics and Robust Exploration Sidekick
lares is an R package designed to automate, improve, and accelerate everyday analytics and machine learning tasks. It offers a wide variety of functions grouped in families for:
- Machine Learning: Streamlined model training and evaluation, including friendly AutoML pipelines.
- Data Cleaning & Processing: Functions to quickly prepare your data for modeling or analyzes.
- Exploratory Data Analysis (EDA): Instantly visualize and summarize your data.
- Reporting: Easily generate comprehensive reports to share insights for MMM and ML models.
- Visualization: Out-of-the-box plotting for classification and regression models, timelines, and more.
- API Integrations & Scrapers: Simplify data collection from various sources.
- Time Series & Portfolio Analysis: Specialized utilities for financial and temporal data.
- Credentials & Secrets Management: Securely handle sensitive information in your analytics pipelines.
- NLP & Text Analytics: Tools to analyze and process text data.
Tip: See all available functions and documentation here or type
?lares::
in RStudio to explore interactively.
Installation
# CRAN VERSION
install.packages("lares")
# DEV VERSION (latest updates)
# If you don't have remotes installed yet, run: install.packages('remotes')
remotes::install_github("laresbernardo/lares")
# For a full installation with recommended dependencies:
remotes::install_github("laresbernardo/lares", dependencies = TRUE)
Windows users: You may need to install RTools to build the dev version.
Read about lares
in action!
-
AutoML Quickstart: Introduction to AutoML using
lares
- Model Results Visualization: Classification | Regression
- Marketing Mix Model Selection: Select the right MMM candidate
- Cross-Correlations: Find Insights with Ranked Cross-Correlations
- Secure Credentials: Manage Secrets in R
- Portfolio Analysis: Performance & Reporting
- Fun games: Wordle, Scrabble, Sudoku, Mazes, etc.
- More Examples: Read other posts
Popular Functions
-
h2o_automl()
,plot_model_results()
– Automated machine learning pipeline with optimal model selection and visualizations. -
freqs()
,distr()
,corr_var()
,corr_cross()
– Instantly summarize, visualize, and uncover relationships in your data. -
ohse()
– Efficient and smart one-hot encoding for categorical variables. -
cache_*
– Speed up workflows by caching expensive computations. -
robyn_*
– Additional functions to support Robyn inputs and outputs. -
fb_*
– Interact with Meta’s Marketing API -
gpt_*
– Structured prompts builder and interact with OpenAI’s API -
read_encrypted()
,write_encrypted()
– Interact with encrypted files to keep secrets safe - …and many more!

AutoML Map (lares)
Getting Started & Help
- Browse all functions in the online reference.
- Use
?lares::function_name
in RStudio for detailed help on any function. - Found a bug or have a feature request? Open an issue.
- For questions or suggestions, reach out to laresbernardo.