The Rolling Stone's Albums by Kaggle | Other

About this Dataset

The Rolling Stone's Albums

From Pop To Rock, From The 1960s To The 2000s

About this dataset

The Rolling Stone's 500 Greatest Albums of All Time is without a doubt one of the most iconic music media lists of all time. Since its initial 2003 publication, it has been revised and updated with a later survey including albums in the 2000s.
In this dataset, you will find information about each album that made the list: its position on the list, year of release, name album title, artist name as well as genre and subgenre names sourced from Discogs API. The data is compiled through votes from various rock musicians and industry figures for predominantly American and British music spanning across 1960s to 2000s releases.
Though painstakingly collected from reliable sources such as MusicBrainz and Discogs API, some genres/subgenres may still be inaccurate due to their lack coverage by these databases. Therefore we invite any critical eyes to help identify any flaws in order to continuously improve our data accuracy!

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How to use the dataset

How to Use this Dataset

Welcome to Rolling Stone's 500 Greatest Albums of All Time! In this dataset, you will find a list of the 500 greatest albums of all time according to Rolling Stone magazine. The data includes the position on the list, year of release, album name, artist name, genre name and subgenre name. With this dataset you can explore music from the 1960s and 1970s that is considered the best by music experts.

To get started with using this dataset, you'll want to become familiar with each column in order to understand what information it contains about each album. The first column is 'Number' which contains a number corresponding to the position on Rolling Stone's list. This number can be used for sorting purposes or simply for reference if you're curious about where an album ranks on here compared to another. The next column is 'Year' which shows when each album was released and can help identify when certain trends or artists peaked in popularity. Following that is 'Album', containing the titles of all 500 albums included in the list, as well as further identifying information like remixes or special versions if any were included in their ranking system Finally we have 'Artist'. This provides a quick glance at who specific songs are by enabling sorting into solo artists or band names while simultaneously being able reproduce tracks they made back then easier thanks Lastly our last two columns are Genre & Subgenre. Those two columns contain specific types/styles music that informed what we consider classics today & potentially even helped shape culture through there creative production too!.

Now that you know what each piece of data means within these files let's talk about ways you can use them! If your looking for new music this is great place start discovering some older works without relying entirely on popular channels like Spotify playlists so its good way explore offbeat things from classic decade . Alternatively if your curious about certain artist specifically singularly without digging around yourself analyzing scores individual chart performance years could yielding useful insights well . Last but not least genres Additionally pinpointing specific listening out come most fitting needs also easy do separate categorize stuff too ”Genres + Subgenres columns lets tag bunch singals into map out library discography projects more easily with having knowledge gathered one convenient location at hand !

Hopefully understanding how access exploit value within rolling stone has provided additional insight how better utilize their data fields shortly Have Fun Enjoy Music Found In Here Create Something New Awesome Cassette Tape Mix Tape One Day !

Research Ideas

Creating a visual of the most successful genres and subgenres over time.

Developing an interactive quiz that allows users to guess the correct answer from Rolling Stone's list of albums based on certain cues (e.g., artist name, genre, year).

Building a website or application that lets users rank their favorite albums according to various criteria such as genre, artist, year and then comparing their ranking to those on Rolling Stone's list for reference or comparison

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: albumlist.csv

Column name	Description
Number	Position on the list (numbered 1-500). (Integer)
Year	Year the album was released. (Integer)
Album	Name of the album. (String)
Artist	Name of the artist. (String)
Genre	Name of the genre. (String)
Subgenre	Name of the subgenre (if applicable). (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Gibs.

Tables

Albumlist

@kaggle.thedevastator_discover_the_500_greatest_albums_of_all_time.albumlist

28.42 KB
500 rows
7 columns


CREATE TABLE albumlist (
  "index" BIGINT,
  "number" BIGINT,
  "year" BIGINT,
  "album" VARCHAR,
  "artist" VARCHAR,
  "genre" VARCHAR,
  "subgenre" VARCHAR
);