University of Michigan
Applied Plotting, Charting & Data Representation in Python
University of Michigan

Applied Plotting, Charting & Data Representation in Python

Christopher Brooks

Instructor: Christopher Brooks

Sponsored by University of Michigan

201,000 already enrolled

Gain insight into a topic and learn the fundamentals.
4.5

(6,246 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 24 hours
Learn at your own pace
93%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.5

(6,246 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 24 hours
Learn at your own pace
93%
Most learners liked this course

What you'll learn

  • Describe what makes a good or bad visualization

  • Understand best practices for creating basic charts

  • Identify the functions that are best for particular problems

  • Create a visualization using matplotlb

Details to know

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Taught in English

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This course is part of the Applied Data Science with Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course

In this module, you will get an introduction to principles of information visualization. We will be introduced to tools for thinking about design and graphical heuristics for thinking about creating effective visualizations. All of the course information on grading, prerequisites, and expectations are on the course syllabus, which is included in this module.

What's included

8 videos6 readings1 peer review1 app item1 discussion prompt

In this module, you will delve into basic charting. For this week’s assignment, you will work with real world CSV weather data. You will manipulate the data to display the minimum and maximum temperature for a range of dates and demonstrate that you know how to create a line graph using matplotlib. Additionally, you will demonstrate the procedure of composite charts, by overlaying a scatter plot of record breaking data for a given year.

What's included

7 videos2 readings1 peer review2 ungraded labs

In this module you will explore charting fundamentals. For this week’s assignment you will work to implement a new visualization technique based on academic research. This assignment is flexible and you can address it using a variety of difficulties - from an easy static image to an interactive chart where users can set ranges of values to be used.

What's included

6 videos3 readings2 peer reviews3 ungraded labs

In this module, then everything starts to come together. Your final assignment is entitled “Becoming a Data Scientist.” This assignment requires that you identify at least two publicly accessible datasets from the same region that are consistent across a meaningful dimension. You will state a research question that can be answered using these data sets and then create a visual using matplotlib that addresses your stated research question. You will then be asked to justify how your visual addresses your research question.

What's included

4 videos3 readings1 peer review2 ungraded labs

Instructor

Instructor ratings
4.5 (485 ratings)
Christopher Brooks
15 Courses891,034 learners

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