Certificate In Data Visualization with Python and Matplotlib Online Course

Advanced graphs with the Matplotlib add-on

Certificate In Data Visualization with Python and Matplotlib Online Course

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Learn Advanced graphs with the Matplotlib add-on

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 data visualization online 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. 

Course Fast Facts:

  1. Learn the fundamentals of Data Visualization with Python and Matplotlib
  2. Comprehensive 7 module Accredited Certificate In Data Visualization with Python and Matplotlib Online Course
  3. Study along with simple instructions & demonstrations
  4. Written and developed by leading Data Visualization with Python and Matplotlib experts
  5. Receive one-on-one online help & support
  6. Unlimited, lifetime access to online course
  7. Certificate of completion
  8. Study at your own pace with no rigid class timetables, 24/7 from any computer or smart device

Course Delivery

CoursesForSuccess.com are accessed online  by any device including PC, tablet or Smart Phone. Upon purchase an automated welcome email will be sent to you (please check your junk email inbox if not received as this is an automated email), in order for you to access your online course, which is Available 24/7 on any computer or smart mobile device. 

Recognition & Accreditation

All students who complete this course, receive a certificate of completion and will be issued a certificate via email.

Course Introduction

  • Introduction
  • Getting Matplotlib And Setting Up

Different types of basic Matplotlib charts

  • Section Introduction
  • Basic matplotlib graph
  • Labels, titles and window buttons
  • Legends
  • Bar Charts
  • Histograms
  • Scatter Plots
  • Stack Plots
  • Pie Chart
  • Loading data from a CSV
  • Loading data with NumPy
  • Section Conclusion

Basic Customization Options

  • Section Introduction
  • Source for our Data*
  • Parsing stock prices from the internet*
  • Plotting basic stock data* 
  • Modifying labels and adding a grid*
  • Converting from unix time and adjusting subplots*
  • Customizing ticks*
  • Fills and Alpha*
  • Add, remove, and customize spines*
  • Candlestick OHLC charts*
  • Styles with Matplotlib*
  • Creating our own Style*
  • Live Graphs*
  • Adding and placing text*
  • Annotating a specific plot*
  • Dynamic annotation of last price* 
  • Section Conclusion

Advanced Customization Options

  • Section Introduction
  • Basic suplot additions* 
  • Subplot2grid *
  • Incorporating changes to candlestick graph* 
  • Creating moving averages with our data*
  • Adding a High minus Low indicator to graph*
  • Customizing the dates that show* 
  • Label and Tick customizations*
  • Share X axis*
  • Multi Y axis* 
  • Customizing Legends*
  • Section Conclusion

Geographical Plotting with Basemap

  • Section Introduction
  • Downloading and installing Basemap
  • Basic basemap example
  • Customizing the projection
  • More customization, like colors, fills, and forms of boundaries
  • Plotting Coordinates*
  • Connecting Coordinates*
  • Section Conclusion

3D graphing

  • Section Introduction
  • Basic 3D graph example using wire_frame
  • Start 3D scatter plots
  • 3D Bar Charts 
  • More advanced Wireframe example
  • Section Conclusion

Course Conclusion

  • Conclusion

Entry requirements

Students must have basic literacy and numeracy skills.

Minimum education

Open entry. Previous schooling and academic achievements are not required for entry into this course.

Computer requirements

Students will need access to a computer and the internet. 

Minimum specifications for the computer are:

Windows:

  • Microsoft Windows XP, or later
  • Modern and up to date Browser (Internet Explorer 8 or later, Firefox, Chrome, Safari)

MAC/iOS

  • OSX/iOS 6 or later
  • Modern and up to date Browser (Firefox, Chrome, Safari)

All systems

  • Internet bandwidth of 1Mb or faster
  • Flash player or a browser with HTML5 video capabilities(Currently Internet Explorer 9, Firefox, Chrome, Safari)

Students will also need access the following applications:

Adobe Acrobat Reader

About this Course

Learn Advanced graphs with the Matplotlib add-on

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 data visualization online 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. 

Course Fast Facts:

  1. Learn the fundamentals of Data Visualization with Python and Matplotlib
  2. Comprehensive 7 module Accredited Certificate In Data Visualization with Python and Matplotlib Online Course
  3. Study along with simple instructions & demonstrations
  4. Written and developed by leading Data Visualization with Python and Matplotlib experts
  5. Receive one-on-one online help & support
  6. Unlimited, lifetime access to online course
  7. Certificate of completion
  8. Study at your own pace with no rigid class timetables, 24/7 from any computer or smart device

Course Delivery

CoursesForSuccess.com are accessed online  by any device including PC, tablet or Smart Phone. Upon purchase an automated welcome email will be sent to you (please check your junk email inbox if not received as this is an automated email), in order for you to access your online course, which is Available 24/7 on any computer or smart mobile device. 

Recognition & Accreditation

All students who complete this course, receive a certificate of completion and will be issued a certificate via email.

Course Introduction

  • Introduction
  • Getting Matplotlib And Setting Up

Different types of basic Matplotlib charts

  • Section Introduction
  • Basic matplotlib graph
  • Labels, titles and window buttons
  • Legends
  • Bar Charts
  • Histograms
  • Scatter Plots
  • Stack Plots
  • Pie Chart
  • Loading data from a CSV
  • Loading data with NumPy
  • Section Conclusion

Basic Customization Options

  • Section Introduction
  • Source for our Data*
  • Parsing stock prices from the internet*
  • Plotting basic stock data* 
  • Modifying labels and adding a grid*
  • Converting from unix time and adjusting subplots*
  • Customizing ticks*
  • Fills and Alpha*
  • Add, remove, and customize spines*
  • Candlestick OHLC charts*
  • Styles with Matplotlib*
  • Creating our own Style*
  • Live Graphs*
  • Adding and placing text*
  • Annotating a specific plot*
  • Dynamic annotation of last price* 
  • Section Conclusion

Advanced Customization Options

  • Section Introduction
  • Basic suplot additions* 
  • Subplot2grid *
  • Incorporating changes to candlestick graph* 
  • Creating moving averages with our data*
  • Adding a High minus Low indicator to graph*
  • Customizing the dates that show* 
  • Label and Tick customizations*
  • Share X axis*
  • Multi Y axis* 
  • Customizing Legends*
  • Section Conclusion

Geographical Plotting with Basemap

  • Section Introduction
  • Downloading and installing Basemap
  • Basic basemap example
  • Customizing the projection
  • More customization, like colors, fills, and forms of boundaries
  • Plotting Coordinates*
  • Connecting Coordinates*
  • Section Conclusion

3D graphing

  • Section Introduction
  • Basic 3D graph example using wire_frame
  • Start 3D scatter plots
  • 3D Bar Charts 
  • More advanced Wireframe example
  • Section Conclusion

Course Conclusion

  • Conclusion

Entry requirements

Students must have basic literacy and numeracy skills.

Minimum education

Open entry. Previous schooling and academic achievements are not required for entry into this course.

Computer requirements

Students will need access to a computer and the internet. 

Minimum specifications for the computer are:

Windows:

  • Microsoft Windows XP, or later
  • Modern and up to date Browser (Internet Explorer 8 or later, Firefox, Chrome, Safari)

MAC/iOS

  • OSX/iOS 6 or later
  • Modern and up to date Browser (Firefox, Chrome, Safari)

All systems

  • Internet bandwidth of 1Mb or faster
  • Flash player or a browser with HTML5 video capabilities(Currently Internet Explorer 9, Firefox, Chrome, Safari)

Students will also need access the following applications:

Adobe Acrobat Reader

We provide a 7 Day Money Back Refund on all Courses

Now Only US$99 Save US$500 (83%)
OFF RRP US$599
Delivery Method Online
Get Info Pack

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Course Summary

Course ID No.: 009SRDVWPM
Delivery Mode: Online
Course Access: Unlimited Lifetime
Tutor Support: Yes
Time required: Study at your own pace
Course Duration: 7 Hours
Assessments: Yes
Qualification: Certificate

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