Description
data visulization assignment to visulize dataset and explain the doctor said you can use anything but if you was more creative that will give higher marks
Unformatted Attachment Preview
Course Title: Data Visualization
Semester:
Spring 2024
Course
Code:
CSAI 453
Assignment
Due Date &
Time:
Sunday
March 17,
2024 by
11:57pm
Mark
ID
Name
Assignment – 10% Individual
Instructions:
•
Submit the completed assignment through Blackboard with well documented Python code.
Any similarity with other student’s work will lead to a zero for both students.
Individual Assignment Description
[10 Marks]
In this assignment, you will design a visualization for a small data set and provide rigorous
rationale for your design choices. You should in theory be ready to explain the contribution of
every pixel in the display. You are free to use any graphics or visualization tool you prefer.
Data: Stanford Undergraduate Majors
Stanford University publishes a variety of datasets through the Stanford Institutional
Research & Decision Support website. They have published a data table containing
information about the number of Stanford undergraduates obtaining a Bachelor’s degree
in 75 different fields of study from 2003 to 2022. This data is filtered and wrangled to the
top 10 fields of study by cumulative degrees conferred over the time period to produce a
dataset with the following attributes:
Year: Academic year between 2003 and 2022. (Academic years run July-June so
Year=2003 covers July 2002 to June 2003.)
FieldOfStudy: Field in which degree was obtained.
Count: Number of students earning a Bachelor’s degree.
The extracted dataset is available in csv format: TopFieldsStanfordBachelors.csv
Assignment:
•
Your task is to download this data and design a static (i.e., single image) visualization
that you believe effectively communicates one aspect of the data and provide a short
write-up (no more than 4 paragraphs) describing your design choices. Start by
choosing a unique question you’d like your visualization to answer. Design your
visualization to answer that question, and use the question as the title of your graphic.
While you must use the data set given, you are free to derive new data, filter, transform
and augment the data as you see fit. Such transformations may include (but are not limited
to) log transformation, computing percentages or averages, grouping elements into new
categories, and/or removing data that are not relevant to your driving question.
•
•
•
•
You are also free to incorporate external data like comparing the provided figures with
those of AURAK. Your chart should be interpretable without recourse to your short
write-up. Do not forget to include title, axis labels or legends as needed! Hint: Good design
often requires omitting data when it is irrelevant to the question your visualization is
designed to answer.
As different visualizations can emphasize different aspects of a data set, your write-up
should document what aspects of the data you are attempting to most effectively
communicate. In short, what story are you trying to tell? Just as important, also note which
aspects of the data might be obscured due to your visualization design.
In your write-up, you should provide a rigorous rationale for your design decisions.
Document the visual encodings you used and why they are appropriate for the data. These
decisions include the choice of visualization marks type, channels such as, size, color,
scale, and other visual elements, as well as the use of sorting or other data
transformations. How do these decisions facilitate effective communication of the answer
to your question? `
Please include a short list of the tools you used to create the visualization.
Grading:
•
•
The assignment score is out of a maximum of 10 points. The scores are determined by
judging both the soundness of your design and the quality of the write-up. Consideration
of audience, message and intended task are also taken into account. Here are some
aspects that may lead to point deductions.
Use of misleading, unnecessary or unmotivated graphic elements.
1. Missing chart title, axis labels, or data transformation descriptions.
2. Missing or incomplete design rationale in write-up.
3. Inappropriate data or data transformations for answering your question (e.g.,
question cannot be addressed by the data shown).
4. Ineffective encodings for conveying the data relevant to your question (e.g.,
distracting colors, improper data transformation).
Entries that go above and beyond the assignment requirements are rewarded: those who
produce effective graphics. Examples may include outstanding visual design, meaningful
incorporation of external data to reveal important trends, demonstrating exceptional
creativity, or effective annotations or other narrative devices.
Submission Details:
•
•
•
•
This is an individual assignment. You may not work in groups. Your completed
assignment is Due: Sunday March 17, 2024 by 11:57pm, avoid a late submission!
Make sure to size your visualization so that it fills a full 8.5 x 11 page of a PDF document
and that any text within it (e.g., labels, axis markings, etc.) is easily readable when the
visualization is expanded to fill the screen. The short description should appear on a
following page and should be in 11pt font, followed by the documented Python code
To submit your assignment, prepare a PDF containing your image and short description
followed by your code saved under your name and ID as follows:
ADV-FirstnameLastnameID.PDF
Administrative overhead penalty of up to 20% will be imposed if additional processing work
is required to handle your assignment, such as: did not follow answer template,
unreadable file, wrongly named file, using different format, … etc.
Assignment Credit: adapted from CS 448B Visualization Stanford CS course on data visualization techniques (Fall 2023)
Purchase answer to see full
attachment
