Merge pull request #5 from UofT-DSI/restructure-repo

Reorganizing the repo structure

.github/issue_template.yaml

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+name: Bug Report
+description: Report a bug
+title: "[Bug]: "
+labels: ["bug"]
+assignees:
+  - danielrazavi
+  - rohanalexander
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Please fill out the sections below to help everyone identify and fix the bug
+  - type: textarea
+    id: description
+    attributes:
+      label: Describe your issue
+      placeholder: When I click here this happens
+    validations:
+      required: true
+  - type: textarea
+    id: steps
+    attributes:
+      label: Steps to reproduce
+      placeholder: |
+        1. Go to page X
+        2. Click here
+        3. Click there
+    validations:
+      required: true
+  - type: textarea
+    id: expected
+    attributes:
+      label: What was the expected result?
+      placeholder: I expected this to happen
+  - type: textarea
+    id: screenshots
+    attributes:
+      label: Put here any screenshots or videos (optional)
+  - type: textarea
+    id: assignee
+    attributes:
+      label: Put here the code owner you'd like to review this issue.
+  - type: markdown
+    attributes:
+      value: |
+        Thanks for reporting this issue! We will get back to you as soon as possible.

.github/pull_request_template.md

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+## What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
+
+## What did you learn from the changes you have made?
+
+## Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
+
+## Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
+
+## How were these changes tested?
+
+## A reference to a related issue in your repository (if applicable)
+
+## Checklist
+- [ ] I can confirm that my changes are working as intended

.gitignore

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 .DS_Store
+.vscode/

02_assignments/assignment_1.md

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+# Data Visualization
+
+## Assignment 1: Participation (Ongoing)
+
+### Requirements:
+
+- During every class, follow along with sample code from the slides. All code that you should be running in Python is formatted as follows:
+
+  > If code in a slide looks like this, you should be running it to generate results.
+
+- When there are individual or group activities in submodules, make notes of answers and key points from discussions
+- Following each lesson with code, submit a document (either .py or a Jupyter notebook) containing the functioning code from that day's lesson, along with any written notes or comments.
+
+### Why am I doing this assignment?:
+
+- This ongoing assignment ensures active participation in the course, and assesses learning outcomes 1, 2, and 3:
+    - 1 - Create and customize data visualizations start to finish in Python
+    - 2 - Use general design principles for creating accessible and equitable data visualizations in Python and other software
+    - 3 - Understand data visualization as purposeful/telling a story (and the ethical/professional implications thereof)
+
+### Rubric:
+
+| Component          | Scoring                 | Requirement                                              |
+|--------------------|-------------------------|----------------------------------------------------------|
+| Completion         | Pass/Fail for each class| - All required work from a given class is included in the file |
+| Markdown file format | Pass/Fail for each class| - File is readable and contains functional code, when needed |
+
+## Submission Information
+
+🚨 **Please review our [Assignment Submission Guide](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md)** 🚨 for detailed instructions on how to format, branch, and submit your work. Following these guidelines is crucial for your submissions to be evaluated correctly.
+
+### Note:
+
+* You should make a commit after each session with that lesson's code and notes. Your PR should have the same number of commits as there are sessions. It is important to make the commits to your branch in a timely manner right after each class.
+
+### Submission Parameters:
+* Submission Due Date: `last day of class`
+* The branch name for your repo should be: `assignment-1`
+* What to submit for this assignment:
+    * The `participation` folder/directory should be populated with the above mentioned .py/.ipynb files along with any written notes or comments (preferably in .md or .txt format).
+* What the pull request link should look like for this assignment: `https://github.com/<your_github_username>/visualization/pull/<pr_id>`
+    * Open a private window in your browser. Copy and paste the link to your pull request into the address bar. Make sure you can see your pull request properly. This helps the technical facilitator and learning support staff review your submission easily.
+
+Checklist:
+- [ ] Create a branch called `assignment-1`.
+- [ ] Ensure that the repository is public.
+- [ ] Review [the PR description guidelines](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md#guidelines-for-pull-request-descriptions) and adhere to them.
+- [ ] Verify that the link is accessible in a private browser window.
+
+If you encounter any difficulties or have questions, please don't hesitate to reach out to our team via our Slack at `#cohort-3-help`. Our Technical Facilitators and Learning Support staff are here to help you navigate any challenges.

02_assignments/assignment_2.md

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+# Data Visualization
+
+## Assignment 2: Good and Bad Data Visualization
+
+### Requirements:
+
+- Data visualizations are important tools for communication and convincing; we need to be able to evaluate the ways that data are presented in visual form to be critical consumers of information 
+- To test your evaluation skills, locate two public data visualizations online, one good and one bad  
+    - You can find data visualizations at https://public.tableau.com/app/discover or https://datavizproject.com/, or anywhere else you like! 
+- For each visualization (good and bad):  
+    - Explain (with reference to material covered up to date, along with readings and other scholarly sources, as needed) why you classified that visualization the way you did.
+      ```
+      Your answer...
+
+
+
+
+
+
+
+      ```
+    - How could this data visualization have been improved?  
+      ```
+      Your answer...
+
+
+
+
+
+
+      
+      ```
+- Word count should not exceed (as a maximum) 500 words for each visualization (i.e. 
+300 words for your good example and 500 for your bad example)
+
+### Why am I doing this assignment?:
+
+- This assignment ensures active participation in the course, and assesses learning outcomes 2 and 3:
+  - 2 - Use general design principles for creating accessible and equitable data visualizations in Python and other software.
+  - 3 - Understand data visualization as purposeful/telling a story (and the ethical/professional implications thereof).
+
+### Rubric:
+
+| Component               | Scoring   | Requirement                                                 |
+|-------------------------|-----------|-------------------------------------------------------------|
+| Data viz classification and justification | Pass/Fail | - Data viz are clearly classified as good or bad<br />- At least three reasons for each classification are provided<br />- Reasoning is supported by course content or scholarly sources |
+| Suggested improvements  | Pass/Fail | - At least two suggestions for improvement<br />- Suggestions are supported by course content or scholarly sources |
+
+## Submission Information
+
+🚨 **Please review our [Assignment Submission Guide](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md)** 🚨 for detailed instructions on how to format, branch, and submit your work. Following these guidelines is crucial for your submissions to be evaluated correctly.
+
+### Submission Parameters:
+* Submission Due Date: `HH:MM AM/PM - DD/MM/YYYY`
+* The branch name for your repo should be: `assignment-2`
+* What to submit for this assignment:
+    * This markdown file (assignment_2.md) should be populated and should be the only change in your pull request.
+* What the pull request link should look like for this assignment: `https://github.com/<your_github_username>/visualization/pull/<pr_id>`
+    * Open a private window in your browser. Copy and paste the link to your pull request into the address bar. Make sure you can see your pull request properly. This helps the technical facilitator and learning support staff review your submission easily.
+
+Checklist:
+- [ ] Create a branch called `assignment-2`.
+- [ ] Ensure that the repository is public.
+- [ ] Review [the PR description guidelines](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md#guidelines-for-pull-request-descriptions) and adhere to them.
+- [ ] Verify that the link is accessible in a private browser window.
+
+If you encounter any difficulties or have questions, please don't hesitate to reach out to our team via our Slack at `#cohort-3-help`. Our Technical Facilitators and Learning Support staff are here to help you navigate any challenges.

02_assignments/assignment_3.md

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+# Data Visualization
+
+## Assignment 3: Data Visualization Ethics
+
+### Requirements:
+- Let’s return to the data visualizations we evaluated for Assignment 2.  
+- For each visualization: 
+    - Explain (with reference to material covered up to date, along with readings and other scholarly sources, as needed) whether or not you think this data visualization is accessible, reproducible, and equitable. 
+        ```
+        Your answer...
+
+
+
+        ```
+    - How could this data visualization have been improved (in terms of accessibility, reproducibility, equity)?  
+        ```
+        Your answer...
+
+
+
+        ```
+
+- Word count should not exceed (as a maximum) 300 words for each visualization. 
+
+### Why am I doing this assignment?:
+- This ongoing assignment ensures active participation in the course, and assesses learning outcomes 2 and 3:  
+    - 2 - Use general design principles for creating accessible and equitable data visualizations in Python and other software 
+    - 3 - Understand data visualization as purposeful/telling a story (and the ethical/professional implications thereof)
+
+### Rubric:
+| Component               | Scoring   | Requirement                                                 |
+|-------------------------|-----------|-------------------------------------------------------------|
+| Data viz classification and justification | Pass/Fail | - Data viz are clearly classified as good or bad<br />- At least three reasons for each classification are provided<br />- Reasoning is supported by course content or scholarly sources |
+| Suggested improvements  | Pass/Fail | - At least two suggestions for improvement<br />- Suggestions are supported by course content or scholarly sources |
+
+## Submission Information
+
+🚨 **Please review our [Assignment Submission Guide](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md)** 🚨 for detailed instructions on how to format, branch, and submit your work. Following these guidelines is crucial for your submissions to be evaluated correctly.
+
+### Submission Parameters:
+* Submission Due Date: `HH:MM AM/PM - DD/MM/YYYY`
+* The branch name for your repo should be: `assignment-3`
+* What to submit for this assignment:
+    * This markdown file (assignment_3.md) should be populated and should be the only change in your pull request.
+* What the pull request link should look like for this assignment: `https://github.com/<your_github_username>/visualization/pull/<pr_id>`
+    * Open a private window in your browser. Copy and paste the link to your pull request into the address bar. Make sure you can see your pull request properly. This helps the technical facilitator and learning support staff review your submission easily.
+
+Checklist:
+- [ ] Create a branch called `assignment-3`.
+- [ ] Ensure that the repository is public.
+- [ ] Review [the PR description guidelines](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md#guidelines-for-pull-request-descriptions) and adhere to them.
+- [ ] Verify that the link is accessible in a private browser window.
+
+If you encounter any difficulties or have questions, please don't hesitate to reach out to our team via our Slack at `#cohort-3-help`. Our Technical Facilitators and Learning Support staff are here to help you navigate any challenges.

02_assignments/assignment_4.md

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+# Data Visualization
+
+## Assignment 4: Final Project
+
+### Requirements:
+- We will finish this class by giving you the chance to use what you have learned in a practical context, by creating data visualizations from raw data. 
+- Choose a dataset of interest from the [City of Toronto’s Open Data Portal](https://www.toronto.ca/city-government/data-research-maps/open-data/) or [Ontario’s Open Data Catalogue](https://data.ontario.ca/). 
+- Using Python and one other data visualization software (Excel or free alternative, Tableau Public, any other tool you prefer), create two distinct visualizations from your dataset of choice.  
+- For each visualization, describe and justify: 
+    > What software did you use to create your data visualization?
+
+    > Who is your intended audience? 
+    
+    > What information or message are you trying to convey with your visualization? 
+    
+    > What design principles (substantive, perceptual, aesthetic) did you consider when making your visualization? How did you apply these principles? With what elements of your plots? 
+    
+    > How did you ensure that your data visualizations are reproducible? If the tool you used to make your data visualization is not reproducible, how will this impact your data visualization? 
+    
+    > How did you ensure that your data visualization is accessible?  
+    
+    > Who are the individuals and communities who might be impacted by your visualization?  
+    
+    > How did you choose which features of your chosen dataset to include or exclude from your visualization? 
+    
+    > What ‘underwater labour’ contributed to your final data visualization product?
+
+- This assignment is intentionally open-ended - you are free to create static or dynamic data visualizations, maps, or whatever form of data visualization you think best communicates your information to your audience of choice! 
+- Total word count should not exceed **(as a maximum) 1000 words** 
+
+### Why am I doing this assignment?:  
+- This ongoing assignment ensures active participation in the course, and assesses 
+learning outcomes 1, 2, and 3:   
+    1. Create and customize data visualizations start to finish in Python 
+    2. Use general design principles for creating accessible and equitable data visualizations in Python and other software 
+    3. Understand data visualization as purposeful/telling a story (and the ethical/professional implications thereof)   
+- This would be a great project to include in your GitHub Portfolio – put in the effort to make it something worthy of showing prospective employers!
+
+### Rubric:
+
+| Component         | Scoring  | Requirement                                                                 |
+|-------------------|----------|-----------------------------------------------------------------------------|
+| Data Visualizations | Pass/Fail | - Data visualizations are distinct from each other<br>- Data visualizations are clearly identified<br>- Different sources/rationales (text with two images of data, if visualizations are labeled)<br>- High-quality visuals (high resolution and clear data)<br>- Data visualizations follow best practices of accessibility |
+| Written Explanations | Pass/Fail | - All questions from assignment description are answered for each visualization<br>- Explanations are supported by course content or scholarly sources, where needed |
+| Code              | Pass/Fail | - All code is included as an appendix with your final submissions<br>- Code is clearly commented and reproducible |
+
+## Submission Information
+
+🚨 **Please review our [Assignment Submission Guide](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md)** 🚨 for detailed instructions on how to format, branch, and submit your work. Following these guidelines is crucial for your submissions to be evaluated correctly.
+
+### Submission Parameters:
+* Submission Due Date: `HH:MM AM/PM - DD/MM/YYYY`
+* The branch name for your repo should be: `assignment-4`
+* What to submit for this assignment:
+    * A folder/directory containing:
+        * This file (assignment_4.md)
+        * Two data visualizations 
+        * Two markdown files for each both visualizations with their written descriptions.
+        * Link to your dataset of choice.
+        * Complete and commented code as an appendix (for your visualization made with Python, and for the other, if relevant) 
+* What the pull request link should look like for this assignment: `https://github.com/<your_github_username>/visualization/pull/<pr_id>`
+    * Open a private window in your browser. Copy and paste the link to your pull request into the address bar. Make sure you can see your pull request properly. This helps the technical facilitator and learning support staff review your submission easily.
+
+Checklist:
+- [ ] Create a branch called `assignment-4`.
+- [ ] Ensure that the repository is public.
+- [ ] Review [the PR description guidelines](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md#guidelines-for-pull-request-descriptions) and adhere to them.
+- [ ] Verify that the link is accessible in a private browser window.
+
+If you encounter any difficulties or have questions, please don't hesitate to reach out to our team via our Slack at `#cohort-3-help`. Our Technical Facilitators and Learning Support staff are here to help you navigate any challenges.

02_assignments/participation/.keep

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+hello 👋