Editing Community Data Science Course (Spring 2023)

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:'''Instructors:''' [https://mako.cc/academic/ Benjamin Mako Hill] / [mailto:makohill@uw.edu makohill@uw.edu] and [https://kayleachampion.com/ Kaylea Champion] / she / [mailto:kaylea@uw.edu kaylea@uw.edu] (TA: you can call me Kaylea)
:'''Instructors:''' [https://mako.cc/academic/ Benjamin Mako Hill] / [mailto:makohill@uw.edu makohill@uw.edu] and [https://kayleachampion.com/ Kaylea Champion] / she / [mailto:kaylea@uw.edu kaylea@uw.edu] (TA: you can call me Kaylea)
:'''Course Website''': We will use Canvas for [https://canvas.uw.edu/courses/1633288/assignments assignments] and [https://canvas.uw.edu/courses/1633288/announcements announcements]. Everything else will be linked on this page.
:'''Course Website''': We will use Canvas for [https://canvas.uw.edu/courses/1633288/assignments assignments] and [https://canvas.uw.edu/courses/1633288/announcements announcements]. Everything else will be linked on this page.
:'''Course Playlist''': [https://open.spotify.com/playlist/4iM6wz4GYRX7O2S7Z2oyXj?si=638c49b13277429e&pt=3f46c0ca5049a1ced44ae09173e28d7b Feel free to add what's moving you lately] (Link will only work if you're logged in to Spotify :/)
:'''Course Playlist''': [https://open.spotify.com/playlist/4iM6wz4GYRX7O2S7Z2oyXj?si=638c49b13277429e&pt=3f46c0ca5049a1ced44ae09173e28d7b Feel free to add what's moving you lately]
:Course Catalog Description (from '''Communication Leadership):'''
:Course Catalog Description (from '''Communication Leadership):'''


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=== Microsoft Teams ===
=== Microsoft Teams ===


We'll be using Microsoft Teams for class chat. There are details in the canvas announcements!
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.
 
You can set up time to meet with Kaylea on [https://harmonizely.com/kaylea her online calendar]!


== 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. At the very least, you will have identify the documentation and the API endpoints that are required. If there are libraries that you think may help with access, note them.
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.
 
Unless you've talked to us, we expect every person to include at least one visualization in their final project. For the proposal, please include "dummy" versions of these that shows us what the x and y axes are. It's OK (and maybe best!) if these are simple and hand drawn!


=== 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 (8 minutes max)
# 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:'''  
:'''Presentation Date:''' At some point during the beginning of the last week of the quarter (the week of May 29). Details will be {{forthcoming}}.
* Presentations need to be shared in the Canvas discussion by '''Monday May 29 at 11:59pm'''
:'''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.
* Feedback on others presentations need to be posted by '''Thursday June 1 at 11:59pm'''
 
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.
;'''Turning in:'''  
* Upload your video as a new thread in this [https://canvas.uw.edu/courses/1633288/discussion_topics/8134432 Canvas discussion]


;'''Watching presentations and feedback:'''
The current plan is:
* We're expecting ''every'' person in the class to watch ''every'' presentation. It should take about 2 hours 30 minutes.
* Leave substantive feedback (see 5-question list below as a guide to feedback) by replying to the threads of the people in [https://teams.microsoft.com/l/message/19:a289c7b44b704149a725047dcafc814d@thread.tacv2/1684191632538?tenantId=f6b6dd5b-f02f-441a-99a0-162ac5060bd2&groupId=189ea783-b3e2-4b4e-83ce-74ebc15db6a5&parentMessageId=1684191632538&teamName=Community%20Data%20Science%20(Spring%202023)&channelName=Final%20Projects&createdTime=1684191632538&allowXTenantAccess=false your final presentation group] [requires Teams access]. We're expecting that you should spend about 15 minutes writing up meaningful feedback for these people. This should take about 90 minutes.
* Leave short feedback (spending 1 minute or so is fine) for everybody who is ''not'' in your presentation group. Saying you love their work is great, but the truest expression of love in data science is intellectual engagement with someone's hard work. Ask a question, make a connection to other ideas and work, or point out a place to dig deeper.


;Length: All presentations will need to be '''a maximum of 8 minutes long'''. Do not exceed 8 minutes and 0 seconds and 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!
;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.


;Recording your talk: There are a range of options for recording your talk. If all else fails, you can join a Zoom room by yourself, share your screen, and record the sessions. It's been working for the class all quarter long so it'll probably work for you too!
;Modality: We will not meet during the final week due to the Memorial Day holiday. As a result, we plan to conduct these virtually.
 
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. The teaching team will provide you with substantial feedback on your presentation. 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.
 
Here is a list of questions to think about both when providing in your feedback and when structuring your talk:
 
# In your own words, what research question did you hear the presenter answer? What are they trying to communicate? How well did they answer their question or achieve their goals? Did you find the answer compelling? Why or why not?
# Be critical. What problems, challenges, or limitations do you see with the way that the presenter is trying to measure things? What are the risks or threats to the validity of the work?
# How would you improve the work? What additional sort of data do you think could be helpful? What sort of additional analysis or visualization would be helpful? What additional interpretation would be helpful?
# If you saw this as a YouTube video or retweeted on Twitter, what sort of questions would you leave in the comments?
# If you were doing this project and presenting it to a supervisor, how would they respond? What changes would you want to make to address this audience a result? What if you were presenting it a colleague, collaborator or friend?


==== 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]; Upload all your code into the [https://github.com/kayleachampion/spr23_CDSW/tree/main/final_project_code final_project_code directory in the class Github repository].
:'''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 alone 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.
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 typically be graded as either complete (full credit) or incomplete (no credit) or on the UW 4.0 grade scale. As detailed and linked elsewhere on the syllabus, I have provided [[User:Benjamin Mako Hill/Assessment|detailed rubrics on how I approach assessment]] for writing, for participation, and in general.


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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* Be ready to start on Week 1 coding challenges. If all goes well, you'll start on them!
* Be ready to start on Week 1 coding challenges. If all goes well, you'll start on them!


'''Programming challenges answers:'''
'''Problem set answers:'''


* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f85d134d-fc3a-4cc3-b3b5-afda01621fe7 Video from class walking through the results]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f85d134d-fc3a-4cc3-b3b5-afda01621fe7 Video from class walking through the results]
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week1/week1-programming_challenge_examples.ipynb Jupyter notebook with Kaylea's assembled list of examples from you along with notes]
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week1/week1-programming_challenge_examples.ipynb Jupyter notebook with Kaylea's assembled list of examples from you along with notes]
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/week1-homework/hill-week_01_coding_challenges-20230403.ipynb Jupyter notebook with Mako's answers to the programming challenges]
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/week1-homework/hill-week_01_coding_challenges-20230403.ipynb Jupyter notebook with Mako's answers to the problem set]


=== Week 2: April 3 ===
=== Week 2: April 3 ===
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'''Class session:'''
'''Class session:'''


* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f85d134d-fc3a-4cc3-b3b5-afda01621fe7 Video of announcements and week 1 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f85d134d-fc3a-4cc3-b3b5-afda01621fe7 Video of announcements and week 1 problem sets] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=47a9e5d4-2998-4943-a047-afda01621fe4 Video of week 2 lecture] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=47a9e5d4-2998-4943-a047-afda01621fe4 Video of week 2 lecture] [Requires Canvas Access]
* [[/Week 2 lecture notes]]
* [[/Week 2 lecture notes]]
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week2/week2-class_lecture.ipynb Week 2 lecture Jupyter notebook]


'''Resources:'''
'''Resources:'''
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** [https://www.py4e.com/html3/03-conditional Chapter 3, Conditionals]
** [https://www.py4e.com/html3/03-conditional Chapter 3, Conditionals]
* [[Python data types cheat sheet]]
* [[Python data types cheat sheet]]
* [[Python loops cheat sheet]]


'''Assignment Due:'''
'''Assignment Due:'''
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=== Week 3: April 10 ===
=== Week 3: April 10 ===


Today we'll be doing introducing some additional programming concepts in Python including aggregating and counting with dictionaries and some first steps toward writing data to files.
Today we'll be doing introducing some additional programming concepts in Python including aggregating and counting with dictionaries.
 
'''Class session:'''
 
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f855f94e-a0e7-4483-ad73-afe1011f745d Video of announcements and week 2 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=da51ee4c-59b7-4925-9f64-afe1011f7452 Video of week 2 lecture] [Requires Canvas Access]
* [[/Week 3 lecture notes]]
* [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week3/week3-class_lecture.ipynb Week 3 lecture Jupyter notebook]


'''Resources:'''
'''Resources:'''
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** [https://www.py4e.com/html3/06-strings Chapter 6, Strings]  
** [https://www.py4e.com/html3/06-strings Chapter 6, Strings]  
** [https://www.py4e.com/html3/08-lists Chapter 8, Lists]: You can skip the part on "Parsing lines"
** [https://www.py4e.com/html3/08-lists Chapter 8, Lists]: You can skip the part on "Parsing lines"
* [[Python loops cheat sheet]]


'''Assignment Due:'''
'''Assignment Due:'''
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'''Class schedule:'''
'''Class schedule:'''


* Some quick announcements
* Go over last week's assignments
* Go over last week's assignments
* [[/Week 3 lecture notes]] introducing new material on dictionaries and aggregations plus average, more loop control, and writing data to files
* [[/Week 3 lecture notes]] <!-- [[Community_Data_Science_Course_%28Spring_2019%29/Day_2_Lecture|Lecture notes]] --> introducing new material on dictionaries and aggregations plus average, median (using the Wordplay data)
* ''A Break''
* A break
* Introduce the [[/Week 3 coding challenges]] based on the [[Baby names]] project.
* Introduce the [[/Week 3 coding challenges]] based on the [http://mako.cc/teaching/2015/cdsw-autumn/babynames.zip Baby names] project. <!-- [[Community Data Science Course (Spring 2019)/Day 3 Coding Challenges|Day 3 Coding Challenges]] -->
* Project time—We'll work through projects
* Project time—We'll work through projects


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=== Week 4: April 17 ===
=== Week 4: April 17 ===


Today we'll be learning about the basic of web APIs and JSON.
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.
 
'''Class session:'''
 
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=49d798d0-61b0-4998-b8db-afe8013c5ca8 Video of announcements and week 3 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8aa88ce5-5de7-4b49-8920-afe8013c5cb9 Video of week 4 lecture part 1] [Requires Canvas Access]
* [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]]
* [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]


'''Assignment Due:'''
'''Assignment Due:'''


* Read chapters 8 and 10 of '''Python for Informatics''':
** Dictionaries
** Files
* Finish and turn in your [[/Week 3 coding challenges]] (Due Sunday before class)
* Finish and turn in your [[/Week 3 coding challenges]] (Due Sunday before class)
'''Resources:'''
* Read chapters 7 and 9 of ''Python for Everyone'':
** [https://www.py4e.com/html3/07-files Chapter 7, Files] — we'll only be doing the section on "Writing files" (NB: you'll notice that the book uses <code>.write()</code> instead of <code>print()</code>)
** [https://www.py4e.com/html3/09-dictionaries Chapter 9, Dictionaries] — feel free to stop when you get to the section on "Advanced text parsing"


'''Class schedule:'''
'''Class schedule:'''


* Go over the [[/Week 3 coding challenges]]
* Go over the [[/Week 3 coding challenges]]
* [[/Week 4 lecture notes]] introducing new material on APIs and JSON
* [[/Week 4 lecture]] introducing new material, plus building some basic histograms in Python.
* Introduce the [[/Week 4 coding challenges]] <!-- [[Community Data Science Course (Spring 2019)/Day 5 Coding Challenges|Day 5 Coding Challenges]] -->
* Introduce the [[/Week 4 coding challenges]], which will also be based on the [http://mako.cc/teaching/2015/cdsw-autumn/babynames.zip Baby names] project.
* Project time—We'll work through projects
* Project time—We'll work through projects
<!-- * [[/Day 4 coding challenges]] [[Community Data Science Course (Spring 2019)/Day 4 Coding Challenges|Day 4 Coding Challenges]] -->


=== Week 5: April 24 ===
=== Week 5: April 24 ===


Today we'll be using Python to read and write files from disk and walk through an API project from start to finish.
Today we'll be learning about the basic of web APIs and JSON.
 
'''Class session:'''
 
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8dff4630-e718-489c-a0c3-afef01525285 Video of announcements and week 4 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8133566f-217d-4e45-b3c9-afef0152528b Video of week 5 lecture]
* [[/Week 5 lecture notes]]
* Notebooks from the lecture including:
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week5/week_5_lecture_part_1-data_collection.ipynb Week 5 lecture notebook part 1] - Data Collection
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week5/week_5_lecture_part_2-data_processing.ipynb Week 5 lecture notebook part 2] - Data Processing
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week5/week-5-lecture_pre-baked_workthrough-20230424.ipynb Week 5 lecture notebook (prebaked)] — A combination of the ideas from both notebooks above with the version of the code that I wrote as notes for myself before the class.  


'''Assignment Due:'''
'''Assignment Due:'''


* Readings {{tbd}}
* Finish and turn in your [[/Week 4 coding challenges]] (Due Sunday before class)
* Finish and turn in your [[/Week 4 coding challenges]] (Due Sunday before class)
'''Resources:'''
* Read selections of chapter 13 from ''Python for Everyone'':
** [https://www.py4e.com/html3/13-web Chapter 13, Python and Web Services] — sections on "JavaScript Object Notation - JSON", "Parsing JSON", and "Application Programming Interfaces"


'''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 new concepts and walking through a project from start to finish
* [[/Week 5 lecture]] introducing new material on APIs and JSON <!-- [[Community Data Science Course (Spring 2019)/Day 5 Notes|Day 5 Notes]] -->
* 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


=== Week 6: May 1  ===
=== Week 6: May 1  ===


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.
'''Class session:'''
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=cc521a93-d6ea-4093-aefe-aff6016dde91 Video of announcements and week 5 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=cc2034fa-eeb3-4b07-abbc-aff8007f170f Video of week 6 lecture]
* [[/Week 6 lecture notes]]
* Notebooks from the lecture including:
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/01-collect_rock_bands_json.ipynb Week 6 lecture notebook Wikipedia part 1] which handles data collection
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/02-analyze_rock_band_data.ipynb Week 6 lecture notebook Wikipedia part 2] which handles data analysis
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/yelp_business_search-module.ipynb Week 6 lecture notebook Yelp (module)] which uses the [https://github.com/lanl/yelpapi yelpapi] Python module
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/yelp_business_search-module.ipynb Week 6 lecture notebook Yelp (direct)] which uses API directly and is only here so you can see how this would work without a module so you get a sense for what the module is doing


'''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 notes]]
* [[/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 (finally!) focus on using a module called <code>pandas</code> that provides spreadsheet like functionality within Python.
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.
 
'''Class session:'''
 
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8078bce8-61bf-4b3d-8bf5-affd0130c1a7 Video of announcements and week 6 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=a815f1ce-ded8-4972-9bb0-affd0130c1a6 Video of week 7 lecture on pandas] [Requires Canvas Access]
* [[/Week 7 lecture notes]]
* Notebooks from the lecture including:
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week7/week_7_lecture_as_delivered-2023-05-08.ipynb Week 7 lecture notebook] which is the notebook I created in class
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week7/week_7_lecture_prework-2023-05-08.ipynb Week 7 lecture notebook (prework)] which is most of the same content but it is the version I created before class
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week7/02-analyze_rock_band_data-pandasify.ipynb Wikipedia revisions pandas-ified] which is a modification of the <code>02-analyze_rock_band_data-pandasify.ipynb</code> notebook I created last week but which is modified to output pandas data.


'''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)


Line 429: Line 357:


* Go over the [[/Week 6 coding challenges]]
* Go over the [[/Week 6 coding challenges]]
* [[/Week 7 lecture notes]] introducing new material on new APIs
* [[/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 be transitioning into a focus on the final projects and trying to build time into class to make real progress on the programming and data collection part of your final projects.
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.
 
 
'''Class session:'''
 
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=bb9b5451-6d22-4e70-ac30-b00500463da4 Video of announcements and week 7 programming challenges] [Requires Canvas Access]
* <strike>[https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=322d5481-254f-4df4-929d-b00500463da3 Video of the second part of the class with final presentations overview]</strike> [Appears to be Basically broken; Requires Canvas Access]
 
'''Resources:'''
 
* Readings:
** [https://pandas.pydata.org/docs/user_guide/10min.html 10 minutes to pandas] (from the pandas user guide)


'''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)


Line 457: Line 375:
* Let's discuss remaining schedule
* Let's discuss remaining schedule
* Go over the [[/Week 7 coding challenges]]
* Go over the [[/Week 7 coding challenges]]
* We'll talk in some depth about the [[#Final Presentation]]
* [[/Week 8 lecture]]
* Introduce the [[/Week 8 coding challenges]]
* Project time—We'll work through projects
* Project time—We'll work through projects


Line 466: Line 385:
'''Assignment Due:'''
'''Assignment Due:'''


* Upload your complete data collection code to the [https://github.com/kayleachampion/spr23_CDSW/tree/main/week8-homework week8-homework directory] in the Github repository and be ready to talk about it in class!
* Readings {{tbd}}
* Finish and turn in your [[/Week 8 coding challenges]] (Due Sunday before class)


'''Class schedule:'''
'''Class schedule:'''


* Project time—We'll check in on projects and walk through folks data collection code in two groups
* Let's discuss remaining schedule
* We'll do three topics in parallel: (1) ChatGPT API with Josh; (2) AI/ML for classification with Kaylea, and (3) statistics with Mako.
* 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) ===
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