Lee Vaughan, Python Tools for Scientists

Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python's Scientific Libraries

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 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 simulating globular star clusters, building ships for a wargame simulator, creating an interactive science slideshow, and classifying animal species.

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.

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.

Eine Einführung in die Programmiersprache Python und ihre beliebtesten Werkzeuge für Wissenschaftler, Ingenieure, Studenten und alle, die Python für Forschung, Simulationen und Zusammenarbeit nutzen möchten. Python Tools for Scientists wird Ihnen die Python-Tools vorstellen, die Sie in Ihrer wissenschaftlichen Forschung verwenden können, darunter Anaconda, Spyder, Jupyter Notebooks, JupyterLab und zahlreiche Python-Bibliotheken. Sie lernen, Python für Aufgaben wie die Erstellung von Visualisierungen, die Darstellung von geospatialen Informationen, die Simulation natürlicher Ereignisse und die Manipulation numerischer Daten zu verwenden. Nachdem Sie eine optimale Programmierumgebung mit Anaconda eingerichtet haben, erfahren Sie, wie Sie Ihre Projekte organisieren und Interpreter, Texteditoren, Notebooks und Entwicklungsumgebungen nutzen, um mit Ihrem Code zu arbeiten. Nach dem schnellen Python-Einsteiger des Buches werden Sie eine Reihe von wissenschaftlichen Werkzeugen und Bibliotheken wie scikit-learn und seaborn kennenlernen, die Sie verwenden können, um Ihre Daten zu manipulieren und zu visualisieren oder sie mit Machine-Learning-Algorithmen zu analysieren. Sie lernen auch, wie Sie isolierte Projekte in virtuellen Umgebungen erstellen, interaktive Notebooks bauen, Code in der Qt-Konsole testen und die interaktiven Entwicklungsfunktionen von Spyder nutzen. Verwenden Sie die integrierten Datentypen von Python, schreiben Sie benutzerdefinierte Funktionen und Klassen und dokumentieren Sie Ihren Code. Stellen Sie Daten mit den grundlegenden Bibliotheken NumPy, Matplotlib und pandas dar. Nutzen Sie Python-Plotbibliotheken wie Plotly, HoloViews und Datashader, um grosse Datensätze zu verarbeiten und 3D-Visualisierungen zu erstellen. Unabhängig von Ihrem wissenschaftlichen Bereich wird Ihnen Python Tools for Scientists zeigen, wie Sie die besten Werkzeuge auswählen, um Ihre Forschungs- und Analysebedürfnisse zu erfüllen.