Data Visualization with Python

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In this Guided Project, you will:

Create DataTable

MatPlotLib to Plot Data

Use Seaborn to Visualize Data

Clock55 minutes
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

Visualizing data is used by virtually every discipline these days. It is used for analyzing web traffic to determine peak server load, growth and death rate of populations for biological analysis, analyzing weather patterns over time, stock market trends, and so on. Simply put, Data Visualization brings meaning to numbers that help people understand it. Seeing the data change can draw attention to trends and spikes that may otherwise go unnoticed. Python is an open-source (free) programming language has libraries that can be used to read and make useful graphics to present the data. In this course, you will create an application that reads data from CSV files. You will learn how to visualize the data using various techniques using existing Python libraries. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Data SciencePython ProgrammingPandasSeabornMatplotlib

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Create a Pandas DataFrame Table

  2. MatPlotLib Plot

  3. Scatterplot Graph

  4. Heatmap plot

  5. Jointplot Distribution

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.