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Assignment 1: Foundations Mastery (protests)
Due Jan 25 by 10pm Points 100 Submitting a text entry box
Submit Assignment
The past few years in the United States, there has been a surge in protests in support of Black Lives
Matter, gender equity, and other social issues. In this assignment, you'll work with data from
CountLove —the same data often cited by the New York Times—to learn more about these
demonstrations. You'll practice using your data programming skills to assess where, why, when, and
how protests are happening.
Objectives
By completing this assignment you will practice and master the following skills:
Using version control to manage your code
Declaring document rendring using Markdown syntax
Using programming fundamentals (e.g., variables and functions) in R
Working with foundational R data structures (vectors, lists, and data frames)
Setup
Follow the below link to create your private code repo for this assignment. You will need to accept
this assignment to create your code repo. Do not fork this repository!
https://classroom.github.com/a/xXBwBhBg (https://classroom.github.com/a/xXBwBhBg)
Note that you do not have to accept an invitation to the organization (you won't get one); once you've
accepted the assignment you're done and can access it.
You will need to accept this assignment to create your code repo. This repo will have the name
info201b-wi21/a1-protests-yourusername , and you can view it online at https://github.com/info201bwi21/a1-protests-yourusername
(replacing yourusername with your GitHub user name).
Do not fork this repository!
After you've accepted the assignment, clone the repo to your local machine so you can edit the files.
Make sure you don't clone it inside another repo!
The starter repo includes a README.md file you will fill in, as well an analysis.R file where you will
perform your analysis (your R code). You will need to modify both files—the details can be found in
the files themselves.
iSchool Canvas Support
2021/2/25 Assignment 1: Foundations Mastery (protests)
https://canvas.uw.edu/courses/1434910/assignments/5937458 2/4
Remember that it's always a good idea to add and commit (and even push ) your changes
whenever you finish a section of an assignment or project!
The Markdown File
Data analysis isn't just code and numbers, it's the interpretation of those numbers and the context of
that interpretation. In the README.md file for this assignment you'll provide that context and
interpretation.
Follow the instructions written in the README.md file to fill out each section. Note that you should delete
the "instruction" text, replacing that with your own work. The instruction text is also included below for
your reference.
1. Background Research Before diving into this (or any) dataset, it's important to have domain
familiarity (i.e., to know something about the topic). As preparation, you should locate and read
three (3) articles about public protests in the U.S.. These can be news articles or more holistic
analysis pieces (e.g., as might be in an online magazine or publication).
In this section of the README.md file, create an unordered list of the three articles you found. For
each article in the list, provide a link to the article (in Markdown formatting, with display text other
than the URL) as well as a 1-2 sentence summary or takeaway/thesis from each one.
2. Representative Image. A picture is, as they say, worth many words. Images are great at
increasing engagement with your analysis as well as conveying the point of your analysis. Find
and download at least one (1) image to accompany your analysis, saving the file in the provided
img/ folder in your repo.
In this section of the README.md file, display the image from your img/ folder (remember to use a
relative path!). Below that image, include 2-3 sentences captioning the image. Your caption should
both identify the image as well as explain why you included that image in particular. As practice,
use either bold or italic text when captioning your image.
3. Analysis Reflections As you follow the instructions in the analysis.R file, you will be prompted
to write six (6) reflections interpreting the results of your code. Those reflections should do in this
section.
Each reflection should be about 1-2 sentences long. You can organize the reflections into an
ordered list or otherwise label which is which.
4. Conclusion Once you are finished with your analysis (you've completed the analysis.R file), fill
in this section by answering the following questions (in about 1-2 sentences each):
1. What results from the analysis surprised you? Why?
2. What parts of the analysis did you find most challenging?
3. What kind of analysis do you wish you were able to do with the dataset (but perhaps don't
have the technical skills to do so)?
The analysis.R File.
iSchool Canvas Support
2021/2/25 Assignment 1: Foundations Mastery (protests)
https://canvas.uw.edu/courses/1434910/assignments/5937458 3/4
a1 Protests Rubric
In this file you will write R code to analysis protest data taken from CountLove.org
(https://countlove.org/) .
Below each prompt in the file, write the code necessary/indicated to calculate the answer. Each result
should be stored in a variable with a name indicated in backtics (to help us with grading). It's also a
good idea to "print" the result so you can see the answers—don't just look at RStudio's environmental
variables!
Note that you are not allowed to use R packages such as dplyr in this assignment. The
goal is to make sure you can use foundational R syntax, which is a necessary skill for future
work.
At each prompt marked "Reflection", be sure to write your answer in the README.md file.
After you complete each section of your analysis, you must add , commit , and push your
changes. This will give you practice working with git and make sure you don't lose any work in
case of technical failures! It's perfectly fine to have more commits as well. We'll be looking for
multiple commits (with informative commit messages) in your repository.
Submit Your Solution
In order to submit assignments in this class:
1. Confirm that you've successfully completed the assignment (e.g., that you've filled in all of the
parts of the README.md file and the analysis.R file)
2. add and commit the final version of your work, and push your code to your GitHub repository.
3. Submit the URL of your GitHub Repository as your assignment submission on Canvas (this page,
at the top).
iSchool Canvas Support
2021/2/25 Assignment 1: Foundations Mastery (protests)
https://canvas.uw.edu/courses/1434910/assignments/5937458 4/4
Total Points: 100
Criteria Ratings Pts
3 pts
20 pts
6 pts
15 pts
22 pts
24 pts
10 pts
Git and GitHub Usage
You created and cloned a git repo, made multiple commits to that repo, and pushed your
changes to GitHub. Commit messages are (mostly) informative and well-written.
README.md
You have filled in the README.md file, providing all required information.
6pt - Background Research (links and descriptions)
3pt - Representative Image (w/ caption)
9pt - Reflections (1.5pt for each question)
2pt - Conclusion
Analysis Part 1
You have provided correct and effective code for each prompt.
This section contains 4 prompts, each worth about 1.5pt.
Analysis Part 2
You have provided correct and effective code for each prompt.
This section contains 8 code prompts, each worth about 2pt (there is a buffer of 1pt; so
15/16 is still 100% of this section)
Analysis Part 3
You have provided correct and effective code for each prompt.
This section contains 11 code prompts, each worth about 2pt.
Analysis Part 4
You have provided correct and effective code for each prompt.
This section contains 12 code prompts, each worth about 2pt.
Analysis Part 5
You have provided correct and effective code for each prompt.
This section contains 5 code prompts, each worth about 2pt.
iSchool Canvas Support

data structures辅导、讲解R编程、讲解R程序 解析Haskell程序|解析C/C++编程

data structures辅导、讲解R编程、讲解R程序解析Haskell程序|解析C/C++编程