DVHZ3-SOCS0100-Assessment2

Second summative assignment for the SOCS0100 module, including an interactive dashboard with three visualizations

What the project include

1. an interactive_report.qmd and an interactive_report file, which include the three interactive visualisations
2. an app file called interactive visualisations, which features the same visualisation but in app format
3. 140123original_IFPI_data.csv : data statically scrapped from IFPI report
4. 140123tophits.csv: data collected using spotify API consists of 50 top hits songs from 6 countries on 14 Jan 2023
5. references.bib : reference list for academic papers cited
6. Assignment coversheet_SRI.docx: the coversheet for the assignment
7. an html report similar to the one in qmd
8. data_scraping.R a separate R script for data scraping (included in the report & the app)
9. data_wrangling.R a separate R script for data wrangling (included in the report & the app)

what this project does

This project includes code snippets that performs automatic data collection from Spotify API and International Federation of the Phonographic Industry (IFPI) data. It then produces three interactive visualisation:

1. scatter plot of different audio features and popularity

2. radar graph of the avearage audio features of tophits in six countries

3. dot plot of the size and level of digitization of countries with the largest music markets form 2011-2017

How to start the project

Opening report

1. open the interactive_report.qmd with R-studio
2. remove the # before if (!require("groundhog")) {install.packages("groundhog")} and groundhog.library(pkgs, "2024-01-04") in the setup code chunk located at the top of the document to install packages necessary for running the document
3. render the .qmd document in r-studio

For other files in this project, follow a similar procedure as the set-up code is always located at the top of the code and follows the same format using groundhog for reproducibility

Opening app

1. find the app in interactive visualisations, open it with r-studio
2. remove # before the set up chunk
3. Run app

Reproducibility

• the packages used will be loaded via groundhog as they are available on 04-Jan-2023

• the scraped data are stored in their original form on 14-Jan-2023 in this file

• the radar chart and the scatter plot are downloadable for future reference

• Both the app and the interactive report runs on version 2023.09.0+463 (2023.09.0+463) of R-studio.

Contribution

The tophits data were automatically collected using the Spotify API and the spotifyr package

The IFPI annual data were statically scrapped from this wikipedia page

I consulted the following tutorials for API and static data collection

1. Exploring the Spotify API with R Using the spotify API in R

2. in-class material for static web scraping.

For the plots, I consulted the following tutorials

1. scatter plot of market size

2. radar chart of the popular audio features in different country

3. plotly scatter plot for audio features of top songs

For the download feature, I used the code provided by this solution.

I followed the official shiny gallery for the Navbar layout in the app.

I critically engaged with ChatGPT for code refinement and correction throughout the process.