Week 1 Meeting - Githubissues

rbouwer commented 7 months ago

Teamwork Contract

@rbouwer

README.md (the project title and a summary of its purpose in ~3-4 sentences) -> @korayt
LICENSE.md (include the license for both software and non-software content) -> @hema2022ubc
CODE_OF_CONDUCT.md (include a citation if you used a template from elsewhere) -> @hema2022ubc
CONTRIBUTING.md (include a citation if you used a template from elsewhere) -> @hema2022ubc
src/app.py or src/app.R (this file can be empty for now, but indicates which language you are planning to use) -> @rbouwer
data/raw/ (should inlucde your chosen raw data file(s); indicate in the proposal if you plan to load from an external source instead) -> @hema2022ubc
notebooks/ (optional: if you start doing EDA, include your notebooks in this folder) -> TBD if we have time
environment.yml (can contain just the basics for now, e.g. the libraries for the dashboard, data wrangling, and vizualization; include version numbers) -> @YimengXia
reports/m1_proposal.md (see below) -> @korayt @hema2022ubc @YimengXia @rbouwer
img/sketch.png (see below) -> @rbouwer

@korayt

Who is your target audience, and what role are you embodying?
- Audience: Music Producers / Labels
- Role we are embodying: Consulting Agency
What is the problem the target audience is facing and why is it important to solve?
How can your dashboard assist in solving this problem for the intended target audience?

@hema2022ubc

Include how many rows and columns there are in the dataset (that you plan to use).
There should be a clear link to how the dataset and the variables you describe will help you solve your target audience's problem.
Indicate at least one new variable that you are planning to derive/engineer for your visualizations.
- live -> transform to binary (live/not live) -> this would help inform producers/labels on whether it is beneficial to invest in live albums
- speechness -> transform into categorical variable (with three categories) -> this again would help producers/labels decide what type of songs are most popular
If there are no new variables to derive, indicate what additional information you would have liked to have in the dataset to better be able to answer your research questions (even if it is impossible for you to engineer it).
If you are planning to visualize a lot of columns, provide a high level description of the variable types rather than listing every single column.
Might wish to perform a brief exploratory data analysis for you to grasp what could be interesting variables to look at in your data not grading the EDA aspect, but include your EDA notebooks in the public GitHub repo, so that you have everything in one place

@YimengXia

For this it can be helpful to create a brief persona description of a member in your intended target audience
Then, think about what they might want to do with your app and write small user story. User stories are typically written in a narrative style and include:
- The specific context/background of the user
- The overall goal of the user
- Tasks needed to reach that goal
- A hypothetical walkthrough of how the user would accomplish those tasks with your app
- The outcome/action that the user would take based on the information they find in the app

@rbouwer

sketch
high-level description of the main components in the app interface and how the user will interact with it. You are not required to use terminology specific to Dash/Shiny (i.e. widgets, components, etc...).
- mostly continuous data -> look at binning (explicit and genre are categorical, also could separate features that. are characteristics of the song quality itself)
- sorted by (median) popularity

rbouwer commented 7 months ago

@korayt to make repo structure

rbouwer commented 7 months ago

Note for next meeting - LIVE?

rbouwer commented 7 months ago

Notes from Meeting 2