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Data Visualization with Python and Matplotlib
Data in its original form comes in haphazard numbers, which without a proper guide could mean anything. To ascertain the meaning from these numbers, you need to analyze the data bit by bit, or you can get a software to do that for you and even shave hours or days of extra work.
Python has become a popular language among enthusiasts for a number of tasks, including programming, development and now even data analysis. Data visualization helps data become easier to read and simple to understand by presenting the data in the form of graphs, charts, etc.
Matplotlib is a plotting library that is used in Python, which creates publication quality figures using Python scripts. It can present data in a variety of different formats such as plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc.
If you want to master the art of present data in a simple and easy format, then this course is for you!
This course has been designed to help you breakdown the complicated world of Matplotlib into simple and easy to understand segments, at the end of which you will be able to analyze your own data using colorful and expressive visualizations.
With over 6 hours of content, divided into 58 systematic lectures, the course covers almost every major chart that is included in Matplotlib. In order to get the most out of this course, students are expected to have a basic understanding of Python and its syntax, on which we will build 2D and 3D visualization projects such as 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 any other on that you can think of.
This course focuses on helping you learn three major tools: Python 3, Matplotlib, and IDLE.
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 you will find in this course:
At the end of this course, you will not only have the knowledge to work with Matplotlib and how to create some visually attractive graphics, but also exactly how to simplify your data analysis technique. You will also learn how to shave off hours from your work schedule.
Enroll now and learn how to present your data that is off the charts!