English | Size: 1.5 GB
Genre: eLearning
6+ Hours of Video Instruction
Unlock the power of data with Python’s cutting-edge visualization tools—transform complex insights into compelling, interactive visuals that drive better business decisions.
Python Data Visualization teaches you the basic principles of data visualization and how to implement them using various Python data visualization platforms. Information visualization, as David McCandless aptly puts it, is a form of “knowledge compression.” Our highly evolved visual processing system allows us to efficiently handle vast amounts of information. Visualization’s power lies in its ability to encode data intuitively, making complex data accessible. As data grows in volume and complexity, the importance of effective visualization increases. This video explores how the human visual cortex processes colors and shapes and how we can utilize these mechanisms for effective visualization using Python’s powerful visualization libraries.
Starting with pandas and matplotlib—two core Python libraries—you learn the basics of Python data pre-processing and visualization before moving on to more advanced packages. Seaborn, built on top of matplotlib, simplifies common tasks and enhances productivity. Interactive visualizations using bokeh and plotly are also explored. You will use jupyter notebooks to craft our visualizations.
About the InstructorBruno Gonçalves is currently in the role of Head of Data Science working at the intersection of AI, blockchain technologies, and finance. Previously, he was a data science fellow at NYU’s Center for Data Science while on leave from a tenured faculty position at Aix-Marseille Université. Following the completion of his PhD in the Physics of Complex Systems in 2008, he has pursued the use of data science and machine learning in the large-scale study of human behavior. In 2015 he was awarded the Complex Systems Society’s 2015 Junior Scientific Award for “outstanding contributions in Complex Systems Science” and in 2018 was named a Science Fellow of the Institute for Scientific Interchange in Turin, Italy.
Learn How To:Utilize an understanding of the fundamentals of human perception in designing data visualizations
Identify the best visualization for a specific dataset
Make effective use of matplotlib and seaborn
Use seaborn and matplotlib together for best results
Use bokeh and plotly to produce interactive plots
Generate animations with matplotlib and plotly
The typical participant will be a data scientist who wants to be able to take advantage of state-of-the-art Python visualization packages. That person will have an understanding of Python and basic familiarity with jupyter notebooks and be interested in developing their visualization skills using state of the art Python visualization packages.
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