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Applying Math with Python

You're reading from   Applying Math with Python Over 70 practical recipes for solving real-world computational math problems

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804618370
Length 376 pages
Edition 2nd Edition
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Author (1):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Toc

Table of Contents (13) Chapters Close

Preface 1. Chapter 1: An Introduction to Basic Packages, Functions, and Concepts 2. Chapter 2: Mathematical Plotting with Matplotlib FREE CHAPTER 3. Chapter 3: Calculus and Differential Equations 4. Chapter 4: Working with Randomness and Probability 5. Chapter 5: Working with Trees and Networks 6. Chapter 6: Working with Data and Statistics 7. Chapter 7: Using Regression and Forecasting 8. Chapter 8: Geometric Problems 9. Chapter 9: Finding Optimal Solutions 10. Chapter 10: Improving Your Productivity 11. Index 12. Other Books You May Enjoy

Technical requirements

This chapter requires many different packages due to the nature of the recipes it contains. The list of packages we need is as follows:

  • Pint
  • uncertainties
  • netCDF4
  • xarray
  • Pandas
  • Scikit-learn
  • GeoPandas
  • Geoplot
  • Jupyter
  • Papermill
  • Cerberus
  • Cython
  • Dask

All of these packages can be installed using your favorite package manager, such as pip:

python3.10 -m pip install pint uncertainties netCDF4 xarray pandas scikit-learn geopandas geoplot jupyter papermill cerberus cython

To install the Dask package, we need to install the various extras associated with the package. We can do this using the following pip command in the terminal:

python3.10 -m pip install dask[complete]

In addition to these Python packages, we will also need to install some supporting software. For the Working with geographical data recipe, the GeoPandas and Geoplot libraries have numerous lower-level dependencies that might need...

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