lares

Analytics & Machine Learning R Sidekick

lares

Lean Analytics and Robust Exploration Sidekick

R-CMD-check CRAN_Status_Badge docs CodeFactor


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!


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.