Data Visualization with Python and Matplotlib

Python,Data Visualization,Matplotlib
4.6 (65 ratings) Instead of using a simple lifetime average, Udemy calculates a
course's star rating by considering a number of different factors
such as the number of ratings, the age of ratings, and the
likelihood of fraudulent ratings.
1,724 students enrolled
$19
$100
81% off
Take This Course
  • Lectures 59
  • Length 6 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
Wishlisted Wishlist

How taking a course works

Discover

Find online courses made by experts from around the world.

Learn

Take your courses with you and learn anywhere, anytime.

Master

Learn and practice real-world skills and achieve your goals.

About This Course

Published 7/2015 English

Course Description

More and more people are realising the vast benefits and uses of analysing big data. However, the majority of people lack the skills and the time needed to understand this data in its original form. That's where data visualisation comes in; creating easy to read, simple to understand graphs, charts and other visual representations of data. Python 3 and Matplotlib are the most easily accessible and efficient to use programs to do just this.

Learn Big Data Python

Visualise multiple forms of 2D and 3D graphs; line graphs, scatter plots, bar charts, etc.

Load and organise data from various sources for visualisation

Create and customise live graphs

Add finesse and style to make your graphs visually appealling

Python Data Visualisation made Easy

With over 58 lectures and 6 hours of content, this course covers almost every major chart that Matplotlib is capable of providing. Intended for students who already have a basic understanding of Python, you'll take a step-by-step approach to create line graphs, scatter plots, stack plots, pie charts, bar charts, 3D lines, 3D wire frames, 3D bar charts, 3D scatter plots, geographic maps, live updating graphs, and virtually anything else you can think of!

Starting with basic functions like labels, titles, window buttons and legends, you'll then move onto each of the most popular types of graph, covering how to import data from both a CSV and NumPy. You'll then move on to more advanced features like customised spines, styles, annotations, averages and indicators, geographical plotting with Basemap and advanced wireframes.

This course has been specially designed for students who want to learn a variety of ways to visually display python data. On completion of this course, you will not only have gained a deep understanding of the options available for visualising data, but you'll have the know-how to create well presented, visually appealing graphs too.

Tools Used

Python 3: Python is a general purpose programming language which a focus on readability and concise code, making it a great language for new coders to learn. Learning Python gives a solid foundation for learning more advanced coding languages, and allows for a wide variety of applications.

Matplotlib: Matplotlib is a plotting library that works with the Python programming language and its numerical mathematics extension 'NumPy'. It allows the user to embed plots into applications using various general purpose toolkits (essentially, it's what turns the data into the graph).

IDLE: IDLE is an Integrated Development Environment for Python; i.e where you turn the data into the graph. Although you can use any other IDE to do so, we recommend the use of IDLE for this particular course.

What are the requirements?

  • Students should be comfortable with the basics of the Python 3 programming language
  • Python 3 should be already installed, and students should already know how open IDLE or their own favorite editor to write programs in.

What am I going to get from this course?

  • Visualize multiple forms of both 2D and 3D graphs, like line graphs, scatter plots, bar charts, and more
  • Load data from files or from internet sources for data visualization.
  • Create live graphs
  • Customize graphs, modifying colors, lines, fonts, and more
  • Visualize Geographical data on maps

What is the target audience?

  • Students should not take this course without a basic understanding of Python.
  • Students seeking to learn a variety of ways to visually display data
  • Students who seek to gain a deep understanding of options for visualizing data.
  • Students should not take this course if they are only looking for a brief summary of how to quickly display data.

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Course Introduction
03:01

Download the source code here.

Getting Matplotlib And Setting Up
Preview
05:44
Section 2: Different types of basic Matplotlib charts
Section Intro
Preview
01:18
Basic matplotlib graph
08:14
Labels, titles and window buttons
08:39
Legends
04:56
Bar Charts
05:12
Histograms
06:50
Scatter Plots
06:48
Stack Plots
08:40
Pie Chart
07:12
Loading data from a CSV
05:05
Loading data with NumPy
04:50
Section Outro
00:50
Section 3: Basic Customization Options
Section Intro
01:17
Getting Stock Prices For Our Data Set
09:59
Parsing stock prices from the internet*
09:17
Plotting basic stock data*
06:10
Modifying labels and adding a grid*
06:12
Converting from unix time and adjusting subplots*
08:00
Customizing ticks*
05:55
Fills and Alpha*
06:47
Add, remove, and customize spines*
08:05
Candlestick OHLC charts*
09:45
Styles with Matplotlib*
07:32
Creating our own Style*
09:27
Live Graphs*
08:49
Adding and placing text*
06:12
Annotating a specific plot*
08:34
Dynamic annotation of last price*
08:20
Section Outro
01:44
Section 4: Advanced Customization Options
Section Intro
01:00
Basic subplot additions*
08:28
Subplot2grid *
08:05
Incorporating changes to candlestick graph*
07:24
Creating moving averages with our data*
10:01
Adding a High minus Low indicator to graph*
05:30
Customizing the dates that show*
10:18
Label and Tick customizations*
07:52
Share X axis*
07:20
Multi Y axis*
10:04
Customizing Legends*
09:41
Section Outro
01:21
Section 5: Geographical Plotting with Basemap
Section Intro
01:19
Downloading and installing Basemap
06:22
Basic basemap example
09:26
Customizing the projection
09:01
More customization, like colors, fills, and forms of boundaries
06:50
Plotting Coordinates*
09:45
Connecting Coordinates*
07:17
Section Outro
00:58
Section 6: 3D graphing
Section Intro
01:25
Basic 3D graph example using wire_frame
05:51
3D scatter plots
05:18
3D Bar Charts
07:14
More advanced Wireframe example
05:02
Section outro
00:54
Section 7: Course Conclusion
Conclusion
03:05
Request a Course
Article

Students Who Viewed This Course Also Viewed

  • Loading
  • Loading
  • Loading

Instructor Biography

Stone River eLearning, 200,000+ Happy Udemy Students

At Stone River eLearning, technology is all we teach. If you're interested in programming, development or design - we have it covered. 

Check out our huge catalog of courses and join the over 370,000 students currently taking Stone River eLearning courses. We currently offer 100+ different technology training courses on our Stone River eLearning website and are adding new courses on hot and trending topics every month. A subscription option is available for those with a real passion for learning.

Ready to start learning?
Take This Course