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Scientific Computing with Python

You're reading from   Scientific Computing with Python High-performance scientific computing with NumPy, SciPy, and pandas

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Length 392 pages
Edition 2nd Edition
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Authors (4):
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Olivier Verdier Olivier Verdier
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Olivier Verdier
Jan Erik Solem Jan Erik Solem
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Jan Erik Solem
Claus Führer Claus Führer
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Claus Führer
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
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Table of Contents (23) Chapters Close

Preface 1. Getting Started 2. Variables and Basic Types FREE CHAPTER 3. Container Types 4. Linear Algebra - Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Series and Dataframes - Working with Pandas 11. Communication by a Graphical User Interface 12. Error and Exception Handling 13. Namespaces, Scopes, and Modules 14. Input and Output 15. Testing 16. Symbolic Computations - SymPy 17. Interacting with the Operating System 18. Python for Parallel Computing 19. Comprehensive Examples 20. About Packt 21. Other Books You May Enjoy 22. References

7.2.5 Variable number of arguments

Lists and dictionaries may be used to define or call functions with a variable number of arguments. Let's define a list and a dictionary as follows:

data = [[1,2],[3,4]]    
style = dict({'linewidth':3,'marker':'o','color':'green'})

Then we can call the plot function using starred (*) arguments:

plot(*data,**style)

A variable name prefixed by *, such as *data in the preceding example, means that a list that gets unpacked to provide the function with its arguments. In this way, a list generates positional arguments. Similarly, a variable name prefixed by **, such as **style in the example, unpacks a dictionary to keyword arguments; see Figure 7.1:

Figure 7.1: Starred arguments in function calls

You might also want to use the reverse process, where all given positional arguments are packed into a list and all keyword arguments are packed into a dictionary when passed to a function. In the function...

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