Spring 2027

Data Visualization for Economists

Introduces economic data visualization and analysis, focusing on using Tableau to design dashboards, graphs, and charts that clarify economic relationships and present research findings.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 7

Past student reviews · Gregory Pac

The workload included a few homework assignments, a final project, and a take-home exam. Multiple students reported self-teaching Tableau; one noted the instructor designed this to prepare them for projects.

What you’ll be able to do

  • Visually represent, interpret, and communicate economic data

  • Understand data visualization theory

  • Incorporate data visualization into economic research

  • Present economic research findings clearly and efficiently

  • Use Tableau software to interact with economic data

Source: UW Guide

Grade history

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average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

(ECON 101 or 111) and ECON 310

ECON 315

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

GRZEGORZ PAC is recorded teaching in Spring 2022, Spring 2023, Fall 2023, Fall 2024, Spring 2025, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.

Meeting source records
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Student experience

the class

Past student reviews · Gregory Pac

Students described the course as interesting and practical, noting that Professor Pac taught real-world data visualization skills using Tableau. Reviewers found the teaching style fun, personable, and engaging.

Recent recorded grades — Fall 2024: 3.49 GPA, 72.7% A/AB (n=44 letter grades); Spring 2025: 3.17 GPA, 58.7% A/AB (n=46 letter grades); Fall 2025: 3.49 GPA, 71.4% A/AB (n=42 letter grades).

difficulty & workload

Past student reviews · Gregory Pac

The workload included a few homework assignments, a final project, and a take-home exam. Multiple students reported self-teaching Tableau; one noted the instructor designed this to prepare them for projects.

Past student reviews · Gregory Pac

Experiences varied significantly; some students found lectures boring and unhelpful, requiring independent study, while others appreciated the professor's flexibility and personable demeanor after the initial adjustment period.

Topics

  • Fundamentals of data visualization theory and economic data analysis.
  • Using Tableau to design and develop dashboards, graphs, and charts for economic data.
  • Interpreting and communicating economic relationships through visual representations.

Skills

  • Visualize, interpret, and communicate economic data using Tableau to create dashboards, graphs, and charts.
  • Incorporate data visualization into economic research to present findings clearly and efficiently.

Grades

Latest available · Fall 2025— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
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D
F

Grades over time

Through Fall 2025

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Fall 2025 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1316 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

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Selected offering source records

No offering records for the selected term.

Raw records 
[]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "c648cf9fcace6a20af06f26f341b6de192da9c33866e41d7a120fb0678b6d9f4",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}