lares

Analytics & Machine Learning R Sidekick

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
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Academic publication links
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Committers with academic emails
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (18.1%) to scientific vocabulary

Keywords

analytics api automation automl data-science descriptive-statistics h2o machine-learning marketing mmm predictive-modeling puzzle r r-package rlanguage robyn rstats visualization

Last synced: 6 months ago · JSON representation

Repository

Analytics & Machine Learning R Sidekick

Basic Info

Host: GitHub
Owner: laresbernardo
Language: R
Default Branch: main
Homepage: https://laresbernardo.github.io/lares/
Size: 344 MB

Statistics

Stars: 237
Watchers: 10
Forks: 50
Open Issues: 1
Releases: 24

Topics

analytics api automation automl data-science descriptive-statistics h2o machine-learning marketing mmm predictive-modeling puzzle r r-package rlanguage robyn rstats visualization

Created over 7 years ago · Last pushed 7 months ago

Metadata Files

Readme Changelog

README.md

lares

Lean Analytics and Robust Exploration Sidekick

$CRAN\_Status\_Badge$

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

```r

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.

Owner

Login: laresbernardo
Kind: user
Location: Bogota
Company: Meta Platforms, Inc

Repositories: 3
Profile: https://github.com/laresbernardo

Professional and passionate Venezuelan Data Scientist. ML, BI, R, data visualization, product ownership, automation, and optimization lover

GitHub Events

Total

Create event: 3
Issues event: 1
Release event: 2
Watch event: 5
Delete event: 1
Issue comment event: 3
Push event: 118
Pull request review comment event: 1
Pull request review event: 1
Pull request event: 2

Last Year

Create event: 3
Issues event: 1
Release event: 2
Watch event: 5
Delete event: 1
Issue comment event: 3
Push event: 118
Pull request review comment event: 1
Pull request review event: 1
Pull request event: 2

Committers

Last synced: 9 months ago

All Time

Total Commits: 1,845
Total Committers: 7
Avg Commits per committer: 263.571
Development Distribution Score (DDS): 0.213

Past Year

Commits: 72
Committers: 2
Avg Commits per committer: 36.0
Development Distribution Score (DDS): 0.194

Top Committers

Name	Email	Commits
Bernardo	l**o@g**m	1,452
bernardolares	b**s@c**m	374
bl896211_gsk	b**s@g**m	15
Will Beasley	w**y@h**m	1
Philip Bulsink	b**p@g**m	1
Patrik	P****s	1
Neal Fultz	n**z@g**m	1

Committer Domains (Top 20 + Academic)

gsk.com: 1 comparamejor.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 51
Total pull requests: 9
Average time to close issues: 3 months
Average time to close pull requests: 1 day
Total issue authors: 44
Total pull request authors: 6
Average comments per issue: 3.98
Average comments per pull request: 2.11
Merged pull requests: 7
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 1
Pull requests: 3
Average time to close issues: N/A
Average time to close pull requests: 2 days
Issue authors: 1
Pull request authors: 2
Average comments per issue: 0.0
Average comments per pull request: 1.0
Merged pull requests: 1
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

ElKron (3)
michellekee (2)
louisjanin (2)
anelda (2)
pangka (2)
AntoineSoetewey (2)
CWen001 (1)
joaomaroco (1)
RickPack (1)
Patrikios (1)
romainfrancois (1)
ms1948 (1)
SugarRayLua (1)
superzilence (1)
teecrow (1)

Pull Request Authors

laresbernardo (6)
wibeasley (1)
pbulsink (1)
nfultz (1)
teunbrand (1)
Patrikios (1)

Top Labels

Issue Labels

bug (11) enhancement (11) help wanted (2)

Pull Request Labels

enhancement (3)

Packages

Total packages: 2
Total downloads:
- cran 6,782 last-month
Total docker downloads: 2,505

Total dependent packages: 2
(may contain duplicates)
Total dependent repositories: 6
(may contain duplicates)
Total versions: 53
Total maintainers: 1

proxy.golang.org: github.com/laresbernardo/lares

Documentation: https://pkg.go.dev/github.com/laresbernardo/lares#section-documentation
Latest release: v5.3.0+incompatible
published 8 months ago

Versions: 24
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.5%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 6 months ago

cran.r-project.org: lares

Lean Analytics and Robust Exploration Sidekick

Homepage: https://github.com/laresbernardo/lares
Documentation: http://cran.r-project.org/web/packages/lares/lares.pdf
License: AGPL-3
Latest release: 5.3.2
published 6 months ago

Versions: 29
Dependent Packages: 2
Dependent Repositories: 6
Downloads: 6,782 Last month
Docker Downloads: 2,505

Rankings

Forks count: 1.4%

Stargazers count: 1.9%

Downloads: 7.2%

Average: 10.1%

Dependent repos count: 11.9%

Dependent packages count: 13.6%

Docker downloads count: 24.4%

Maintainers (1)

laresbernardo@gmail.com

Last synced: 6 months ago

Dependencies

DESCRIPTION cran

R >= 3.5 depends
dplyr * imports
ggplot2 * imports
h2o * imports
httr * imports
jsonlite * imports
lubridate * imports
openxlsx * imports
pROC * imports
patchwork * imports
rlang * imports
rpart * imports
rpart.plot * imports
rvest * imports
stringr * imports
tidyr * imports
yaml * imports
DALEX * suggests
beepr * suggests
googleAuthR * suggests
googlesheets4 * suggests
knitr * suggests
quantmod * suggests
rdrop2 * suggests
rmarkdown * suggests

.github/workflows/R-CMD-check.yaml actions

actions/checkout v2 composite
actions/upload-artifact main composite
r-lib/actions/check-r-package v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/pkgdown.yaml actions

actions/cache v2 composite
actions/checkout v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite

lares

Science Score: 26.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

lares

Lean Analytics and Robust Exploration Sidekick

Installation

CRAN VERSION

DEV VERSION (latest updates)

If you don't have remotes installed yet, run: install.packages('remotes')

For a full installation with recommended dependencies:

Read about lares in action!

Popular Functions

Getting Started & Help

Owner

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

proxy.golang.org: github.com/laresbernardo/lares

Rankings

cran.r-project.org: lares

Rankings

Maintainers (1)

Dependencies

Read about `lares` in action!