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Udemy - Data Visualization with Python and Matplotlib

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Description

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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.
Who 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.

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.

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