Editing Community Data Science Course (Spring 2023)
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=== Microsoft Teams === | === Microsoft Teams === | ||
We'll be using Microsoft Teams for class chat. | We'll be using Microsoft Teams for class chat. More details are {{forthcoming}} soon! | ||
=== Open Labs === | === Open Labs === | ||
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=== Office Hours === | === Office Hours === | ||
Mako will not be holding additional office hours but is generally available. You can set up a 30 minute minute meeting by adding something to [https://mako.cc/calendar/ his online calendar] which has a meeting signup link attached to it. | Mako will not be holding additional office hours but is generally available. You can set up a 30 minute minute meeting by adding something to [https://mako.cc/calendar/ his online calendar] which has a meeting signup link attached to it. | ||
== Assignments == | == Assignments == | ||
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Your proposal should frame your final analysis, but it's also a chance to "sanity check" your plan. I will give you feedback on these proposals and suggest changes or modifications that are more likely to make them successful or compelling. I will also work with you to make sure that you have the resources and support necessary to carry out your project successfully. | Your proposal should frame your final analysis, but it's also a chance to "sanity check" your plan. I will give you feedback on these proposals and suggest changes or modifications that are more likely to make them successful or compelling. I will also work with you to make sure that you have the resources and support necessary to carry out your project successfully. | ||
Be as specific as possible about the data available on the sources you've chosen. I expect that you will have written at least some of the final code that you will use in this course. | Be as specific as possible about the data available on the sources you've chosen. I expect that you will have written at least some of the final code that you will use in this course. Identify the documentation and the API endpoints where required. If there are libraries that you think may help with access, note them. | ||
=== Final Project === | === Final Project === | ||
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For your final project, I expect you to build on the first two assignments to describe what they have done and what you have found. I'll expect every student to give both: | For your final project, I expect you to build on the first two assignments to describe what they have done and what you have found. I'll expect every student to give both: | ||
# A short presentation ( | # A short presentation (7 minutes) | ||
# A final report that is not more than 4500 words (~18 pages) | # A final report that is not more than 4500 words (~18 pages) | ||
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==== Final Presentation ==== | ==== Final Presentation ==== | ||
:'''Presentation Date:''' At some point during the beginning of the last week of the quarter (the week of May 29). Details will be {{forthcoming}}. | |||
:'''Turning in:''' Details are {{tentative}} but we will very likely ask you upload a video to Canvas and will provide information and links on how to do this. | |||
Your presentation should provide the teaching team and your classmates with a very clear idea of what to expect in your final paper. However, don't treat it as a comprehensive overview of your paper: I would rather you tell a subset of the story well than the whole story in a rushed fashion. For instance, you can give a completely successful presentation by describing the motivation and walking through one plot in your paper. I'm going to give you all at least a paragraph of feedback after your talk. This will be an opportunity for me to see a preview of your paper and give you a sense for what I think you can improve. It's to your advantage to both give a compelling talk and to give me a sense for your project. | |||
The current plan is: | |||
;Length: All presentations will need to be '''a maximum of | ;Length: All presentations will need to be '''a maximum of 7 minutes long'''. Do not exceed 7 minutes and 0 seconds; don't edit your video to speed it up if you go too long. Concisely communicating an idea in the time allotted is an important skill in its own right. | ||
;Slides: You are encouraged to use slides for your talk. Please keep in mind that your slides are meant to be additive, not a teleprompter. | ;Slides: You are encouraged to use slides for your talk. Please keep in mind that your slides are meant to be additive, not a teleprompter. | ||
; | ;Modality: We will not meet during the final week due to the Memorial Day holiday. As a result, we plan to conduct these virtually. | ||
==== Final Paper (and Code!) ==== | ==== Final Paper (and Code!) ==== | ||
:'''Due Date:''' Thursday June 8 at 11:59 p.m. | :'''Due Date:''' Thursday June 8 at 11:59 p.m. | ||
:'''Turning in:''' Turn in a PDF of your paper to [https://canvas.uw.edu/courses/1633288/assignments/8231894 the Canvas dropbox]; | :'''Turning in:''' Turn in a PDF of your paper to [https://canvas.uw.edu/courses/1633288/assignments/8231894 the Canvas dropbox]; Details on how to turn in your code will be {{forthcoming}}. | ||
Your final project should include detailed information on: | Your final project should include detailed information on: | ||
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Keep in mind that most stories on Five Thirty Eight are under 1000 words and I'm giving up to 4,500 words to show me what you've learned. As a result, you should do ''more'' than FiveThirtyEight does in a single story. You can ask and answer more questions, you can provide more background, context, and justification, you can provide more details on your methods and data sources, you can show us more graphs, you can discuss the implications of your findings more. Use the space I've given you to show off what you've done and what you've learned! | Keep in mind that most stories on Five Thirty Eight are under 1000 words and I'm giving up to 4,500 words to show me what you've learned. As a result, you should do ''more'' than FiveThirtyEight does in a single story. You can ask and answer more questions, you can provide more background, context, and justification, you can provide more details on your methods and data sources, you can show us more graphs, you can discuss the implications of your findings more. Use the space I've given you to show off what you've done and what you've learned! | ||
Finally, you should also share with me the full Python source code you used to collect the data as well as the data set itself. Your code | Finally, you should also share with me the full Python source code you used to collect the data as well as the data set itself. Your code along will not form a large portion of your final grade. Rather, I will focus on the degree to which you have been successful at answering the ''substantive'' questions you have identified. | ||
Visualization is critical to storytelling, so 25% of your grade for this project will be determined by the visualizations and tables in your report. Good visualizations should "stand alone" and motivate the core results in your paper all by themselves. A good question to keep in mind is "could I tell this story with the visualizations and a tweet?" | Visualization is critical to storytelling, so 25% of your grade for this project will be determined by the visualizations and tables in your report. Good visualizations should "stand alone" and motivate the core results in your paper all by themselves. A good question to keep in mind is "could I tell this story with the visualizations and a tweet?" | ||
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== Grades == | == Grades == | ||
Assignments will accrue to your final grade in the following way: | Assignments will accrue to your final grade in the following way: | ||
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* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=001c2a6d-71ea-478d-9ce6-afe801795f2c Video of week 4 lecture part 2] [Requires Canvas Access] (rerecorded material from the last 30m of class) | * [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=001c2a6d-71ea-478d-9ce6-afe801795f2c Video of week 4 lecture part 2] [Requires Canvas Access] (rerecorded material from the last 30m of class) | ||
* [[/Week 4 lecture notes]] | * [[/Week 4 lecture notes]] | ||
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week4/week4_lecture_part_1_bored_api.ipynb Week 4 lecture Jupyter notebook part 1] covering the [http://www.boredapi.com/ Bored API] | * [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week4/week4_lecture_part_1_bored_api.ipynb Week 4 lecture Jupyter notebook part 1] (covering the [http://www.boredapi.com/ Bored API]) | ||
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week4/week4_lecture_part_2_nominatim.ipynb Week 4 lecture Jupyter notebook part 2] covering the [https://nominatim.openstreetmap.org/ OpenStreetMap Nominatim API] | * [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week4/week4_lecture_part_2_nominatim.ipynb Week 4 lecture Jupyter notebook part 2] covering the [https://nominatim.openstreetmap.org/ OpenStreetMap Nominatim API] | ||
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=== Week 5: April 24 === | === Week 5: April 24 === | ||
Today we'll be using Python to read and write files from disk and | Today we'll be using Python to read and write files from disk and be learning to do some basic tricks with a very useful Python module called Pandas. | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
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'''Class schedule:''' | '''Class schedule:''' | ||
* Go over the [[/Week 4 coding challenges]] | * Go over the [[/Week 4 coding challenges]] and review some histograms | ||
* [[/Week 5 lecture notes]] introducing some | * [[/Week 5 lecture notes]] introducing new material on pandas, plus building some basic histograms in Python. | ||
* Introduce the [[/Week 5 coding challenges]] | * Introduce the [[/Week 5 coding challenges]] <!-- [[Community Data Science Course (Spring 2019)/Day 5 Coding Challenges|Day 5 Coding Challenges]] --> | ||
* Project time—We'll work through projects | * Project time—We'll work through projects | ||
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Today we'll be putting everything together and walking through a project that builds a dataset from the Wikipedia API from start-to-finish, with a focus on cleaning and getting data into tools like Excel or Google Sheets, and introducing a set of tricks along the way. | Today we'll be putting everything together and walking through a project that builds a dataset from the Wikipedia API from start-to-finish, with a focus on cleaning and getting data into tools like Excel or Google Sheets, and introducing a set of tricks along the way. | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* Readings {{tbd}} | |||
* Finish and turn in your [[/Week 5 coding challenges]] (Due Sunday before class) | * Finish and turn in your [[/Week 5 coding challenges]] (Due Sunday before class) | ||
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* Let's discuss remaining schedule | * Let's discuss remaining schedule | ||
* Go over the [[/Week 5 coding challenges]] | * Go over the [[/Week 5 coding challenges]] | ||
* [[/Week 6 lecture | * [[/Week 6 lecture]] introducing new material on APIs and JSON <!-- [[Community Data Science Course (Spring 2019)/Day 5 Notes|Day 5 Notes]] --><!-- [[Community Data Science Course (Sprint 2019)/Day 7 Notes|Day 7 Notes]] --> | ||
* Introduce the [[/Week 6 coding challenges]] | * Introduce the [[/Week 6 coding challenges]] <!-- [[Community Data Science Course (Spring 2019)/Day 7 Coding Challenges|Day 7 Coding Challenges]] --> | ||
* Project time—We'll work through projects | * Project time—We'll work through projects | ||
<!-- | <!-- | ||
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=== Week 7: May 8 === | === Week 7: May 8 === | ||
Today we'll | Today we'll be introducing two additional web APIs in parallel. We'll run a poll of the class to get a sense of what folks want to learn but we're considering Yelp, Reddit, Twitter, and data.seattle.gov. | ||
' | |||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* Readings {{tbd}} | |||
* Finish and turn in your [[/Week 6 coding challenges]] (Due Sunday before class) | * Finish and turn in your [[/Week 6 coding challenges]] (Due Sunday before class) | ||
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* Go over the [[/Week 6 coding challenges]] | * Go over the [[/Week 6 coding challenges]] | ||
* [[/Week 7 lecture | * [[/Week 7 lecture]] introducing new material on new APIs | ||
* Introduce the [[/Week 7 coding challenges]] | * Introduce the [[/Week 7 coding challenges]] | ||
* Project time—We'll work through projects | * Project time—We'll work through projects | ||
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=== Week 8: May 15 === | === Week 8: May 15 === | ||
We'll | Today we'll be introducing two additional web APIs in parallel. We'll run a poll of the class to get a sense of what folks want to learn but we're considering Yelp, Reddit, Twitter, and data.seattle.gov. | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* [[#Final Project Proposal]] | * [[#Final Project Proposal]] | ||
* Readings {{tbd}} | |||
* Finish and turn in your [[/Week 7 coding challenges]] (Due Sunday before class) | * Finish and turn in your [[/Week 7 coding challenges]] (Due Sunday before class) | ||
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* Let's discuss remaining schedule | * Let's discuss remaining schedule | ||
* Go over the [[/Week 7 coding challenges]] | * Go over the [[/Week 7 coding challenges]] | ||
* | * [[/Week 8 lecture]] | ||
* Introduce the [[/Week 8 coding challenges]] | |||
* Project time—We'll work through projects | * Project time—We'll work through projects | ||
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'''Assignment Due:''' | '''Assignment Due:''' | ||
* | * Readings {{tbd}} | ||
* Finish and turn in your [[/Week 8 coding challenges]] (Due Sunday before class) | |||
'''Class schedule:''' | '''Class schedule:''' | ||
* Project time—We'll | * Let's discuss remaining schedule | ||
* | * Go over the [[/Week 8 coding challenges]] | ||
* [[/Week 9 lecture]] | |||
* Project time—We'll work through projects | |||
'''Resources:''' | |||
* Visualization dos and don'ts. We'll discuss the European Environmental Agency's [https://www.eea.europa.eu/data-and-maps/daviz/learn-more/chart-dos-and-donts list of advice for making charts]. **I will refer to this guide as a grade your final projects.** | |||
* Two options for remainder of class. You can work through this introductory guide to visualization in python or you can work on your final project. I'll be here to answer any questions. | |||
* Self-guided visualization tutorial in python. [https://raw.githubusercontent.com/guyrt/teaching/master/2019/Com520B/VisualizationNotebook.ipynb Download here]. Save the file in a new directory in your desktop and open it with Jupyter Notebook. (If you are on Windows, you may run into an issue with missing path variables. [https://stackoverflow.com/questions/52821162/jupyter-notebook-failed-to-load-dll This SO post helped me solve it.]) | |||
=== Week 10: May 29 (NO MEETING) === | === Week 10: May 29 (NO MEETING) === |