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Informationen zum Autor Lee Vaughan is a programmer, pop culture enthusiast, educator, and author of Impractical Python Projects and Real-World Python (No Starch Press). As a former executive-level scientist at ExxonMobil, he spent decades constructing and reviewing complex computer models, developed and tested software, and trained geoscientists and engineers. Klappentext An introduction to the Python programming language and its most popular tools for scientists, engineers, students, and anyone who wants to use Python for research, simulations, and collaboration. Doing Science with Python introduces readers to the most popular coding tools for scientific research, such as Anaconda, Spyder, Jupyter Notebooks, and JupyterLab, as well as dozens of important Python libraries for working with data, including NumPy, matplotlib, and pandas. No prior programming experience is required! You'll be guided through setting up a professional coding environment, then get a crash course on programming with Python, and explore the many tools and libraries ideal for working with data, designing visualizations, simulating natural events, and more. In the book's applied projects, you'll use these tools to write programs that perform tasks like counting tree rings, creating an interactive science slideshow, and simulating the foraging patterns of animals. Zusammenfassung An introduction to the Python programming language and its most popular tools for scientists, engineers, students, and anyone who wants to use Python for research, simulations, and collaboration. Python Tools for Scientists will introduce you to Python tools you can use in your scientific research, including Anaconda, Spyder, Jupyter Notebooks, JupyterLab, and numerous Python libraries. You’ll learn to use Python for tasks such as creating visualizations, representing geospatial information, simulating natural events, and manipulating numerical data. Once you’ve built an optimal programming environment with Anaconda, you’ll learn how to organize your projects and use interpreters, text editors, notebooks, and development environments to work with your code. Following the book’s fast-paced Python primer, you’ll tour a range of scientific tools and libraries like scikit-learn and seaborn that you can use to manipulate and visualize your data, or analyze it with machine learning algorithms. You’ll also learn how to: Create isolated projects in virtual environments, build interactive notebooks, test code in the Qt console, and use Spyder’s interactive development features Use Python’s built-in data types, write custom functions and classes, and document your code Represent data with the essential NumPy, Matplotlib, and pandas libraries Use Python plotting libraries like Plotly, HoloViews, and Datashader to handle large datasets and create 3D visualizations Regardless of your scientific field, Python Tools for Scientists will show you how to choose the best tools to meet your research and computational analysis needs. Inhaltsverzeichnis Introduction Part 1: Setting up for Science 1 Installing Anaconda and Launching Navigator 2 Keeping Organized with Conda Environments 3 Simple Scripting in Jupyter Qt Console 4 Serious Scripting with Spyder 5: Jupyter Notebook: An Interactive Journal for Computational Research 6 JupyterLab: Your Center for Science Part 2: Python Primer 7 Integers and Floats and Strings 8 Variables 9 The Container Data Types 10 Flow Control 11 Functions and Modules 12 Working with Files and Folders 13 Object Oriented Programming 14 Documenting Your Work Part 3: The Scientific and Visualization Libraries 15 The Scientific Libraries 16 The InfoVis and SciVis Visualization Libraries 17 The GeoVis Libraries Part 4: The Essential Libraries 18 Numpy:...
