Introduction to Python in Earth Science Data Analysis

Introduction to Python in Earth Science Data Analysis
Author: Maurizio Petrelli
Publsiher: Springer Nature
Total Pages: 229
Release: 2021-09-16
Genre: Science
ISBN: 9783030780555

Download Introduction to Python in Earth Science Data Analysis Book in PDF, Epub and Kindle

This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.

Earth Observation Using Python

Earth Observation Using Python
Author: Rebekah B. Esmaili
Publsiher: John Wiley & Sons
Total Pages: 308
Release: 2021-08-24
Genre: Science
ISBN: 9781119606888

Download Earth Observation Using Python Book in PDF, Epub and Kindle

Learn basic Python programming to create functional and effective visualizations from earth observation satellite data sets Thousands of satellite datasets are freely available online, but scientists need the right tools to efficiently analyze data and share results. Python has easy-to-learn syntax and thousands of libraries to perform common Earth science programming tasks. Earth Observation Using Python: A Practical Programming Guide presents an example-driven collection of basic methods, applications, and visualizations to process satellite data sets for Earth science research. Gain Python fluency using real data and case studies Read and write common scientific data formats, like netCDF, HDF, and GRIB2 Create 3-dimensional maps of dust, fire, vegetation indices and more Learn to adjust satellite imagery resolution, apply quality control, and handle big files Develop useful workflows and learn to share code using version control Acquire skills using online interactive code available for all examples in the book The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more about this book from this Q&A with the Author

Python for Data Analysis

Python for Data Analysis
Author: Wes McKinney
Publsiher: "O'Reilly Media, Inc."
Total Pages: 676
Release: 2017-09-25
Genre: Computers
ISBN: 9781491957615

Download Python for Data Analysis Book in PDF, Epub and Kindle

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

An Introduction to Python Programming for Scientists and Engineers

An Introduction to Python Programming for Scientists and Engineers
Author: Johnny Wei-Bing Lin,Hannah Aizenman,Erin Manette Cartas Espinel,Kim Gunnerson,Joanne Liu
Publsiher: Cambridge University Press
Total Pages: 767
Release: 2022-07-07
Genre: Computers
ISBN: 9781108701129

Download An Introduction to Python Programming for Scientists and Engineers Book in PDF, Epub and Kindle

Textbook that uses examples and Jupyter notebooks from across the sciences and engineering to teach Python programming.

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences
Author: Johnny Wei-Bing Lin
Publsiher: Lulu.com
Total Pages: 209
Release: 2012-08-18
Genre: Computers
ISBN: 9781300076162

Download A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences Book in PDF, Epub and Kindle

This book is a mini-course for researchers in the atmospheric and oceanic sciences. "We assume readers will already know the basics of programming... in some other language." - Back cover.

Introduction to Python Programming for Business and Social Science Applications

Introduction to Python Programming for Business and Social Science Applications
Author: Frederick Kaefer,Paul Kaefer
Publsiher: SAGE Publications
Total Pages: 542
Release: 2020-08-06
Genre: Business & Economics
ISBN: 9781544377483

Download Introduction to Python Programming for Business and Social Science Applications Book in PDF, Epub and Kindle

Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.

Python Programming for Data Analysis

Python Programming for Data Analysis
Author: José Unpingco
Publsiher: Springer Nature
Total Pages: 263
Release: 2021-05-04
Genre: Technology & Engineering
ISBN: 9783030689520

Download Python Programming for Data Analysis Book in PDF, Epub and Kindle

This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns. After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly. The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. To get the most out of this book, open a Python interpreter and type along with the many code samples.

Python for Everybody

Python for Everybody
Author: Charles R. Severance
Publsiher: Unknown
Total Pages: 242
Release: 2016-04-09
Genre: Electronic Book
ISBN: 1530051126

Download Python for Everybody Book in PDF, Epub and Kindle

Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics: Exploring Information".There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.