VaishnaviBehl
commented
5 months ago Thanks so much for your thoughtful comments and suggestions, I'll definitely keep it in mind for my next project! I just realised that 2021 in the graph titles was a typo (its meant to be 2010), but I'm glad you liked it overall.
Congratulations on a great piece of work! The analysis's purpose and perspective are clear, and the detailed explanation of data acquisition enhances credibility. Addressing potential 'Issues' and 'Further Research' adds reliability and prevents reader misinterpretation. However, some improvements can be made. First, the report’s presentation can be cleaner, by optimizing the R code setup to exclude unnecessary messages in the beginning. Second, some graphs reference a comparison from 2021 to 2023, while the source of 2021 data is not clear. Lastly, regarding the analysis, valuable information about artists' sales and activity period is obtained but not included in the report. I believe this could have enhanced overall conclusions. Apart from these, the work is commendable given the available data.
Shifting to the code, its well-structured nature with separate chunks, clear comments, and efficient functions is praised. However, the main advice here is related to its replicability. First, conditioning the extensive commented code until line 350 with 'eval=FALSE' is suggested. This will not web scrape the information every time you knit the document and makes it easier for another person to run the analysis. Second, ensuring code compatibility across systems by using a general path when reading Spotify keys improves accessibility. As a last comment, minor efficiency suggestions include optimizing code lines involving unnecessary data frame renaming and defining a function to get the artists' names. In summary, the project demonstrates solid execution, and including these improvements could make it more refined, enhancing its overall presentation and replicability for future analyses.