ARRAYS IN PYTHON PROGRAMMING

Authors

  • Fathiddinov Saidma‘ruf Lazizxo‘ja ugli Department of General Technical Sciences, Asia International University

DOI:

https://doi.org/10.55640/

Keywords:

Python, arrays, lists, NumPy, data structures, programming, data processing.

Abstract

This article presents a comprehensive overview of arrays in Python programming, their structure, functionality, and practical applications. Arrays play a vital role in data processing, scientific computing, machine learning, and software development. Python provides several ways to work with arrays, including built-in lists and specialized libraries such as NumPy, which significantly enhance performance and flexibility. The study highlights the importance of arrays in organizing data efficiently, improving computational speed, and simplifying complex operations. The results demonstrate that a proper understanding of arrays is essential for developing efficient and scalable Python applications.

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References

1.Dubois, P. F., Hinsen, K. & Hugunin, J. Numerical Python. Comput. Phys. 10, 262–267 (1996).

2.Ascher, D., Dubois, P. F., Hinsen, K., Hugunin, J. & Oliphant, T. E. An Open Source Project: Numerical Python (Lawrence Livermore National Laboratory, 2001).

3.Oliphant, T. E. Guide to NumPy 1st edn (Trelgol Publishing, 2006).

4.Dubois, P. F. Python: batteries included. Comput. Sci. Eng. 9, 7–9 (2007).

5.Oliphant, T. E. Python for scientific computing. Comput. Sci. Eng. 9, 10–20 (2007).

6.Millman, K. J. & Aivazis, M. Python for scientists and engineers. Comput. Sci. Eng. 13, 9–12 (2011).

7.Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).

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Published

2026-01-25

How to Cite

ARRAYS IN PYTHON PROGRAMMING. (2026). Journal of Multidisciplinary Sciences and Innovations, 5(01), 2037-2038. https://doi.org/10.55640/

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