Anaisdg / Popular_Music_Insights

Analysis and visualization of musical tastes by artists, songs, genres, lyrics, demographics, race, and gender

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Popular Music Insights

Concert

Analysis and visualization of musical tastes by artists, songs, genres, lyrics, demographics, race, and gender

View the Deployed app on Heroku.

Outline

I. A geographical examination of the musical preferences across 15 cities -- filtered by artist genre, race, and gender -- based on Spotify streaming frequency.

  • Example of the interactive map that examines the musical preferences for particular cities Map

II. Emotional influences and lyrical content mapped by analysis of 70 years of top-charting Billboard songs by genre.

  • Example of the emotional attributes of hit songs over the last 70 years: bubble_plot

Technologies Employed

File Descriptions

wordcloud_data

Data retrieval and analysis of lyrics from lyrics.wikia.com scraped HTML; generation of word cloud images from WordCloud (using matplotlib/Python).

emotion_analysis

Data retrieval and analysis of lyrics data supporting the Plotly bubble charts in vis_integration/static/bubble_charts

  • country

    • billboard_country.csv Top country hits and lyrics
    • country_bub_form.csv Output from country_bubble.ipynb
    • country_bubble.ipynb Converts country_combined.csv into format for bubble plot.
    • country_combined.csv Output from country_exploration.ipynb
    • country_exploration.ipynb Takes country_lyr_results and combines together into one source in country_exploration.ipynb and stored as output in country_combined.csv
    • country_to_watson.ipynb Watson Personality Insights API call and analysis. Converts billboard_country.csv into country_lyr_results.
    • country_lyr_results Output from Watson API
  • pop

    • billboard_pop.csv top pop hits and lyrics
    • pop_bub_form.csvOutput from pop_bubble.ipynb
    • pop_bubble.ipynb Converts pop_combined.csv into format for bubble plot.
    • pop_combined.csv Output from pop_exploration.ipynb
    • pop_exploration.ipynb Takes pop_lyr_results and combines together into one source in pop_exploration.ipynb and stored as output in pop_combined.csv
    • country_to_watson.ipynb Watson Personality Insights API call and analysis. Converts billboard_pop.csv into pop_lyr_results.
    • pop_lyr_results Output from Watson API
  • rnb

    • billboard_rnb.csv Top R&B hits and lyrics
    • rnb_bub_form.csv Output from rnb_bubble.ipynb
    • rnb_bubble.ipynb Converts rnb_combined.csv into format for bubble plot.
    • rnb_combined.csv Output from rnb_exploration.ipynb
    • rnb_exploration.ipynb Takes rnb_lyr_results and combines together into one source in rnb_exploration.ipynb and stored as output in rnb_combined.csv
    • country_to_watson.ipynb Watson Personality Insights API call and analysis. Converts billboard_rnb.csv into rnb_lyr_results.
    • rnb_lyr_results Output from Watson API

Integration Directories

vis_integration

  • Integration of all visualizations, with app.py to run Flask app.

spotify_data

  • Data retrieval, analysis, and storage of artist, genre, song, gender, race, and city demographic data - in support of the interactive Leaflet.js map.

Additional Information

Inspiration for map visualization

proposal_img

  • Inspirational images for the project

readmeimg

  • Images used for this Readme

Development Directories

frontend

  • Landing page working directory

visualizations

  • Visualization pages working directory

About

Analysis and visualization of musical tastes by artists, songs, genres, lyrics, demographics, race, and gender


Languages

Language:Jupyter Notebook 93.7%Language:JavaScript 2.4%Language:HTML 2.2%Language:Python 1.2%Language:CSS 0.5%