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Applying Math with Python

You're reading from   Applying Math with Python Practical recipes for solving computational math problems using Python programming and its libraries

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838989750
Length 358 pages
Edition 1st Edition
Languages
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Authors (2):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Table of Contents (12) Chapters Close

Preface 1. Basic Packages, Functions, and Concepts 2. Mathematical Plotting with Matplotlib FREE CHAPTER 3. Calculus and Differential Equations 4. Working with Randomness and Probability 5. Working with Trees and Networks 6. Working with Data and Statistics 7. Regression and Forecasting 8. Geometric Problems 9. Finding Optimal Solutions 10. Miscellaneous Topics 11. Other Books You May Enjoy

Loading and storing data from NetCDF files

Many scientific applications require that we start large quantities of multi-dimensional data in a robust format. NetCDF is one example of a format used for data that's developed by the weather and climate industry. Unfortunately, the complexity of the data means that we can't simply use the utilities from the Pandas package, for example, to load this data for analysis. We need the netcdf4 package to be able to read and import the data into Python, but we also need to use xarray. Unlike the Pandas library, xarray can handle higher-dimensional data while still providing a Pandas-like interface.

In this recipe, we will learn how to load data from and store data in NetCDF files.

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