Acta Scientific Computer Sciences

Research Article Volume 4 Issue 3

Data Analysis Using Pandas Library of Python

Rupal Snehkunj1* and Khushboo Vachiyatwala2

1Department of Computer Science, Sarvajanik University, India
2Department of Computer Science, VNSG University, India

*Corresponding Author: Rupal Snehkunj, Department of Computer Science, Sarvajanik University, India.

Received: November 25, 2021; Published: February 25, 2022

Abstract

This research paper mainly focuses on usage of Pandas library of python. This rich library provides various integrated support for analysis of data. It is useful for grouping queries, graphical design of data in tabular format. This library is foundational layer for future statistical computing of data in python through various Pandas API. The work is researched with structure data set file accessing various formats as xls, csv, pdf and many more. The work is implemented on randomly created employee database for performing various operations and data visualization in Python using pandas library.


Keywords: Pandas; NumPy; Matplotlib; Scipy

References

  1. Stančin Igor and Alan Jović. "An overview and comparison of free Python libraries for data mining and big data analysis”. 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE (2019).
  2. McKinney Wes. "Pandas: a foundational Python library for data analysis and statistics”. Python for High Performance and Scientific Computing 9 (2011).
  3. Kumar Rakesh. "Future for scientific computing using Python”. International Journal of Engineering Technologies and Management Research 2 (2015): 30-41.
  4. Hoyer Stephan and Joe Hamman. "xarray: ND labeled arrays and datasets in Python”. Journal of Open Research Software1 (2017).
  5. Mitrpanont Jarernsri., et al. "A study on using Python vs Weka on dialysis data analysis”. 2017 2nd International Conference on Information Technology (INCIT). IEEE (2017).
  6. https://rabernat.github.io/research_computing/pandas.html
  7. https://www.simplilearn.com/why-python-is-essential-for-data-analysis-article
  8. https://towardsdatascience.com/a-guide-to-pandas-and-matplotlib-for-data-exploration-56fad95f951c
  9. S van der Walt., et al. "The NumPy Array: A Structure for Efficient Numerical Computation". in Computing in Science and Engineering 13.2 (2011): 22-30.
  10. Sessa Jadran and Dabeeruddin Syed. "Techniques to deal with missing data”. 2016 5th international conference on electronic devices, systems and applications (ICEDSA). IEEE (2016).

Citation

Citation: Rupal Snehkunj and Khushboo Vachiyatwala. “Data Analysis Using Pandas Library of Python”. Acta Scientific Computer Sciences 4.3 (2022): 37-41.

Copyright

Copyright: © 2022 Rupal Snehkunj and Khushboo Vachiyatwala. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




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Acceptance rate35%
Acceptance to publication20-30 days

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