During the app design stage we were not made aware of the computation limit for shiny apps, therefore loading some of the geospatial visualizations will cause the app to crash. We would prefer that the marking of this assignment be based on a locally run version, which works as intended: please feel free to clone the repo and follow the instructions on README.md. Thank you!
Thanks for all your hard work on this final project! You got an A. Here are some comments:
In "Weekly Wage Percentage Change by Industry," the color scheme is too low-contrast to be effective. This is mitigated by the interactive overlays, but some labels in the chart itself would help. In "US Unemployment Rate by Industry throughout the pandemic" (note the inconsistent capitalization, by the way), your subplot labels are duplicated in your legend. Do we even need the colors, if each subplot is labeled? The sentiment analysis charts would be more effective if we saw the proportions of these words in the corpus of tweets.
There are all kinds of things you can do to fix the loading problems, caused by too much data. One is simply to break out the webpage into several smaller webpages.
@QMSS-G5063-2022/teaching_team SHA: 02b9c92
During the app design stage we were not made aware of the computation limit for shiny apps, therefore loading some of the geospatial visualizations will cause the app to crash. We would prefer that the marking of this assignment be based on a locally run version, which works as intended: please feel free to clone the repo and follow the instructions on README.md. Thank you!
Link to deployed shiny app: https://tobykylaw.shinyapps.io/Group_A_COVID-19_insights/ Link to presentation video: https://drive.google.com/file/d/1qYHouPkVQekBr220wVu3xFk_wpJQHg1U/view?usp=sharing