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Treehouse

Introduction to Data Visualization with Matplotlib Course (How To)

via Treehouse

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Overview

Get started creating charts with the Python library, matplotlib, an industry-standard data visualization library. Matplotlib provides a way to easily generate a wide variety of plots and charts in a few lines of Python code. It is an open-source project that can be integrated into Python scripts, jupyter notebooks, web application servers, and multiple GUI toolkits. Whether you are exploring sample data available on the internet, or your own business data, learning matplotlib is a great place to start your data visualization journey.

What you'll learn

  • Introduction to the Python matplotlib library
  • Uses and reasons behind the selection of a particular chart type
  • This course will introduce the user to the concepts of data visualization, which will help them to better understand business drivers and data trends
  • Explores graph customization to further enhance data reporting and communicating meaning

Syllabus

Getting Started with Data Visualization

In this stage, you’ll learn about some of the different common types of charts used to visual data and how matplotlib is used to create them. We’ll take a look at why and when to select a specific type of chart and using a static data set, create different views of our data.

Chevron 6 steps

  • Welcome to Matplotlib

    2:05

  • Getting Started with Charting

    4:22

  • The Legend of Charting

    5:25

  • Charting Overview

    5 questions

  • Chart Types & Reasons to Use

    6:00

  • Charting Type Why & When

    5 questions

Chart Toppers

In this stage, we’ll continue our dataviz journey by looking at data from the well-known Fisher Iris data set. We’ll see how choosing different charts, and settings for those charts allows for different reporting on the data and can provide different meanings. Then, we’ll see how we can use the power of matplotlib to save our charts in a wide variety of formats to share our visualizations.

Chevron 6 steps

  • Our Data Set - Flower Power

    4:07

  • Scatter Plot

    7:17

  • Histogram

    6:01

  • Box Plot

    5:35

  • Saving Your Work

    3:12

  • Matplotlib Syntax

    5 questions

Data Eruption

With a few tools in our toolbelt for data visualization, let’s take our skills to a client and show them how data visualization can be helpful for business making decisions.

Chevron 4 steps

  • Problem Discussion

    1:48

  • Decision Process

    9:22

  • Problem Summary and Presentation

    1:07

  • Review: Matplotlib

    7 questions

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