Course details
Matplotlib is a multi-platform data visualization tool built upon the Numpy and Scipy framework. One of matplotlib's most important features is its ability to play well with many operating systems and graphics backends.
In this course, we hit the ground running and quickly learn how to make beautiful, illuminating figures with Matplotlib and a handful of other Python tools. We understand data dimensionality and set up an environment by beginning with basic plots. We enter into the… + Read More
Course details
Matplotlib is a multi-platform data visualization tool built upon the Numpy and Scipy framework. One of matplotlib's most important features is its ability to play well with many operating systems and graphics backends.
In this course, we hit the ground running and quickly learn how to make beautiful, illuminating figures with Matplotlib and a handful of other Python tools. We understand data dimensionality and set up an environment by beginning with basic plots. We enter into the exciting world of data visualization and plotting. You'll work with line and scatter plots and construct bar plots and histograms. You'll also explore images, contours, and histograms in depth. Plot scaffolding is a very interesting topic wherein you'll be taken through axes and figures to help you design excellent plots. You'll learn how to control axes and ticks, and change fonts and colors. You'll work on backends and transformations. Then lastly you'll explore the most important companions for Matplotlib, Pandas and Jupyter, used widely for data manipulation, analysis, and visualization.
By the end of this course you'll be able to construct effective and beautiful data plots using the Matplotlib library for the Python programming language.
About the Author
Benjamin Keller is a postdoctoral researcher in the MUSTANG group at Universität Heidelberg's Astronomisches Rechen-Institut. He obtained his PhD at McMaster University and got his BSc in Physics with a minor in Computer Science from the University of Calgary in 2011. His current research involves numerical modeling of the interstellar medium over cosmological timescales.
As an undergraduate at the U of C, he worked with Dr. Jeroen Stil on stacking radio polarization to examine faint extragalactic sources. He also worked in the POSSUM Working Group 2 to determine the requirements for stacking applications for the Australian SKA Pathfinder (ASKAP) radio telescope.
At McMaster, he worked with Dr. James Wadsley in the Physics & Astronomy department. His current research was focused around understanding how the energy released from supernovae explosions regulated the flow of gas through galaxies, and how that gas is converted into stars.
Updated on 02 January, 2018 - Read Less
