Create attractive visualizations using Python’s most popular libraries
About This Video
Set up an optimal Python environment for data visualization
Import, organize, and visualize your data with the popular open source Python libraries such as matplotlib, NumPy, plot.ly and more
A practical tutorial to help you determine different approaches to data visualization, and how to choose the most appropriate one for your needs
Effective visualization can help you get better insights from your data, and help you make better and more informed business decisions.
This video starts by showing you how to set up matplotlib and other Python libraries that are required for most parts of the course, before moving on to discuss various widely used diagrams and charts such as Gantt Charts. As you will go through the course, you will get to know about various 3D diagrams and animations. As maps are irreplaceable to display geo-spatial data, this course will show you how to build them. In the last section, we’ll take you on a thorough walkthrough of incorporating matplotlib into various environments and how to create Gantt charts using Python.
With practical, precise, and reproducible videos, you will get a better understanding of the data visualization concepts, how to apply them, and how you can overcome any challenge while implementing them.
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Python Data Visualization Solutions
3 hours 26 minutes
Dimitry is a data scientist with a background in applied mathematics and theoretical physics. After completing his physics undergraduate studies in ENS Lyon (France), he studied fluid mechanics at École Polytechnique in Paris where he obtained first Class class Master’s degree. He holds a PhD in applied mathematics from the University of Cambridge. He currently works as a data-scientist for a smart-energy start-up in Cambridge, in close collaboration with the university.