Skip to Content
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
book

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

by Robert Johansson
September 2024
Intermediate to advanced content levelIntermediate to advanced
501 pages
17h 6m
English
Apress
Content preview from Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024
R. JohanssonNumerical Pythonhttps://doi.org/10.1007/979-8-8688-0413-7_7

7. Interpolation

Robert Johansson1  
(1)
Urayasu-shi, Chiba, Japan
 

Interpolation is a mathematical method for constructing a function from discrete data points. The interpolation function, or interpolant, should coincide with the given data points and can be evaluated for other intermediate input values within the sampled range. There are many applications of interpolation. A typical use case that provides an intuitive picture is plotting a smooth curve through a given set of data points. Another use case is to approximate complicated functions, which, for example, could be computationally ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Robert Johansson
Machine Learning with Python

Machine Learning with Python

Tarkeshwar Barua, Kamal Kant Hiran, Ritesh Kumar Jain, Ruchi Doshi

Publisher Resources

ISBN: 9798868804137Purchase LinkPublisher Website