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Author: Bruna Wundervald License: MIT

CRAN status CRAN downloads Rdoc Travis-CI Build Status

chorrrds: A package for music chorrrds extraction.

chorrrds is a package for R that scrapes the Cifraclub website to download and organize music chords. It can be considered a package for MIR (Music Information Retrieval), a broad area of computational music which extracts and processes music data, from the unstructured ones, as sound waves, to structured, like sheet music or chords.

If you enjoy this work, consider buying me a coffee in Ko-Fi, or Paypal:

so I can keep developing and maintaining this package :)

Installation

You can install chorrrds from your favorite CRAN mirror, simply running:

install.packages("chorrrds")

You can also install the latest version of chorrrds from the R-Music GitHub organization with:

# install.packages("devtools")
devtools::install_github("r-music/chorrrds")

Functionalities

The package currently has as its main functions:

  • A function to extract the name of the songs of an artist: get_songs();
  • A function that extracts the chords of the song: get_chords().

There are also some accessory objects and functions, that provides useful too use in combination with the music chords:

  • The deg_maj and deg_min dataframes, that contains all of the minor and major main scales and its respective degrees;
  • The dist dataframe, that contains the distance from C in the circle of fifths, by semitones and by steps in the circle, for each tonic chord;
  • The genre dataframe, that contains the musical genre information for many Brazilian artists;
  • The all dataframe, that contains the chords data for many Brazilian artists;
  • The search_data() function, that looks for an artist in the available data;
  • The clean_data() function, that cleans the chords in case something weird (such as lyrics) were wrongly scraped.
  • The feature_extraction() function, that extracts useful features to represent the characteristics of the chords.

All of the functions and documentation can be found with:

library(chorrrds)
packageVersion("chorrrds")
ls("package:chorrrds")
help(package = "chorrrds")

To be implemented

  • Standardization of the chords formats.
  • Link the package to the syntax provided by the tabr package.
  • Functions to perform the feature extraction of the chords.
  • The official pkgdown for chorrrds.

Examples and Resources

A tutorial about how to extract & analyze the data with the chorrrds package is available at:

https://r-music.rbind.io/posts/2018-08-19-chords-analysis-with-the-chorrrds-package/

R-Music

R for music data extraction and analysis

See the R-Music organization on GitHub for more R packages related to music data extraction and analysis. The R-Music blog provides package introductions and examples.

tabr connection

The usability of this package can be highly increased when in combination with other MIR tools, such as the tabr package, which offers a music notation syntax converter for the packages. Please find more information at: https://leonawicz.github.io/tabr/reference/to_tabr.html

Besides its many other functions, the tabr package has a chord chart rendering, that might be especially interesting for users of the chorrrds package: https://leonawicz.github.io/tabr/articles/tabr-chordchart.html

Citation

To cite this package in publications, please use:

Bruna Wundervald (2019). chorrrds: Music
Chords Extraction. R package version
0.1.8.
https://CRAN.R-project.org/package=chorrrds

A BibTeX entry for LaTeX users is

@Manual{,
title = {chorrrds: Music Chords Extraction},
author = {Bruna Wundervald},
year = {2019},
note = {R package version 0.1.8},
url = {https://CRAN.R-project.org/package=chorrrds},
}

This citation format can be obtained at any moment in R with:

citation('chorrrds')

Contributing

Contributions to this project are always highly incentivized. To do so, please be aware that git is our main tool for version control. The minimal steps for a contribution are:

  1. Fork this repository into your GitHub account and clone it the way you prefer.
  2. Do the changes, making sure everything is well documented, examples are provided and checking if the package still correctly builds.
  3. Push your changes to git and create a new pull request in GitHub, explaining why and what are the changes made.
  4. Done! Wait for review & acceptance of the pull request :)

To contributors who are new to writing R packages, we recommend the 'R Packages' book, by Hadley Wickham. To those who are new to git/GitHub, we recommend this tutorial. Many contributing resources to open source projects can be found at this repository.