Pitchfork Music Reviews: Artist & Genre by Kaggle | Media and Entertainment

About this Dataset

Pitchfork Music Reviews: Artist & Genre

Analyzing Popular Music Trends

About this dataset

Dive Into the Music Scene with Pitchfork Ratings

Are you eager to explore the most popular music today? With this dataset at your fingertips, it's time to dive deep into the trends of modern music and get to know which artists and genres have made major waves in the industry.

Created by web scraping techniques, this dataset provides detailed information about top rated albums and songs as judged by Pitchfork.com – the premier online source of music reviews and news. By delving into its comprehensive data – including artists, titles, genres, URLs to reviews and images – you’ll be able to uncover compelling statistics that reveal which musical acts are making a real impact today. So join us as we embark on this exploratory journey together! The insights we uncover will surely provide fascinating lessons on modern music trends for all who participate

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How to use the dataset

This dataset is an excellent resource to explore the latest music trends by artist and genre. The dataset contains information on the best new music rated by Pitchfork.com, the premier online source of music reviews and news, including artist, title, genre, URL to online review and images. With this dataset you can easily analyze various characteristics of top rated music such as trends in artists or genres in a given period of time.

Here’s how to use this dataset:
Review all data fields and understand what information each field includes - You should be familiar with the column titles (artist, title, genre etc.) so that you understand what kind of data you are working with when exploring the sets for analysis purposes.  
Choose where to focus your analysis - Select an aspect or category within the sets that will spark your curiosity for further exploration such as studying trends in certain genres or analyzing particular artists over a certain period of time or across multiple albums or songs etc..

Identify how you want to compare/analyze - There are many ways to slice/dice datasets differentiate between groups/variables i.e., sort results by artist name(A-Z) vs type (album/single) , cross tabulate results on different variables etc.. Decide which variables would be most appropriate for comparison depending what type analysis conclusions are trying look for in terms of insights into trending topics within any given search parameter set keyed off parameters outlined initially when confirmed point 2 was established what was chosen as focus one's comparison goals around
4 4 Get familiar with manipulating subsetting functions available CSV files provided complimentary Sorting Merging Concatenation options desired formulating use analytical methods.(i.e,. grouping counts stats tables totals summarizing chart graphs formatting & making visualizations). Apply these functions based upon analytical desires types modifications validate output according expectations determining if delve deeper altered views selected targeted audience gaining insight range patterns among records being segmented divided slices identify norms similarities inferences about whole group

Research Ideas

Analyzing which genres of music are the most popular by analyzing the ratings given to each type of music in the dataset.

Analyzing how frequently various artists release new songs or albums and comparing that to their overall rating scores on Pitchfork.

Creating a map of both artist and genre popularity based off geographic region by plotting album/song review locations against review properties such as score or average rating score

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: pitchfork_best_songs_dataset.csv

Column name	Description
artist	Name of the artist. (String)
title	Title of the album or single. (String)
genre	Genre of the album or single. (String)
url	URL of the review or news article. (String)
type	Type of release (album or single). (String)
image	URL of the album or single image. (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 .

Tables

Pitchfork Best Songs Dataset

@kaggle.thedevastator_pitchfork_music_reviews_artist_genre.pitchfork_best_songs_dataset

7.75 KB
21 rows
6 columns


CREATE TABLE pitchfork_best_songs_dataset (
  "artist" VARCHAR,
  "title" VARCHAR,
  "genre" VARCHAR,
  "url" VARCHAR,
  "type" VARCHAR,
  "image" VARCHAR
);