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Python as a key for Data Science

Gaurav 1 , Ritu Sindhu2

  1. Computer Science and Engineering, SGT University, Gurugram ,India.
  2. Computer Science and Engineering, Galgotias University, Greater Noida, India.

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-4 , Page no. 325-328, Apr-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i4.325328

Online published on Apr 30, 2018

Copyright © Gaurav, Ritu Sindhu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Gaurav, Ritu Sindhu, “Python as a key for Data Science,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.325-328, 2018.

MLA Style Citation: Gaurav, Ritu Sindhu "Python as a key for Data Science." International Journal of Computer Sciences and Engineering 6.4 (2018): 325-328.

APA Style Citation: Gaurav, Ritu Sindhu, (2018). Python as a key for Data Science. International Journal of Computer Sciences and Engineering, 6(4), 325-328.

BibTex Style Citation:
@article{Sindhu_2018,
author = {Gaurav, Ritu Sindhu},
title = {Python as a key for Data Science},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2018},
volume = {6},
Issue = {4},
month = {4},
year = {2018},
issn = {2347-2693},
pages = {325-328},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1894},
doi = {https://doi.org/10.26438/ijcse/v6i4.325328}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i4.325328}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1894
TI - Python as a key for Data Science
T2 - International Journal of Computer Sciences and Engineering
AU - Gaurav, Ritu Sindhu
PY - 2018
DA - 2018/04/30
PB - IJCSE, Indore, INDIA
SP - 325-328
IS - 4
VL - 6
SN - 2347-2693
ER -

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Abstract

Data science is the science of studying scientific data, business data and it’s an integration of Artificial Intelligence, statistics, computing technology. Data science is a field that relates to data cleansing, preparation and analysis. Data science algorithms are used in many industries like Internet searches, Digital Advertisements, Travelling, Healthcare, Gaming, Financial services etc. Data science can solve the problems like classification, identifying anomalies, to quantify, finding way of organization, decision making issues etc. In this paper, we have shown how python is useful and acts as a key to solve such problems. In addition to python, there are also some other platforms which are used to solve a task completely based on data science. Here we have focused on python and it’s packages that are highly useful for data science based problems. We have shown how python can be used for data analysis and data visualization.

Key-Words / Index Term

Data Science, Python, Data analysis, Data Visualization

References

[1]. Javin D. West, “The science of data science”, Journal of Integrated creative studies, No. 2016-010-e, May 2016.

[2]. Wes McKinney, “pandas: a Foundational Python Library for DataAnalysis and Statistics”, DLR Portal, www.dlr.de/sc/Portaldata/15/Resources/dokumente/.../pyhpc2011_submission_9.pdf.

[3]. Gaurav, Zunaid Alam, “Road Safety in india using Data Mining Approach”, International Conference, REDSET 2017, CCIS 799, https://doi.org/10.1007/978-981-10-8527-7_17

[4]. Rosa Filguiera, Iraklis Klampanos, Amrey Krause, Mario David, Alexander Moreno and Malcolm Atkinson, “A Python Framework for Data-Intensive Scientific Computing”, IEEE Conference, 978-1-4673-6750-9, Nov-2014.

[5]. Ing. Zdena Dobesova, “Programming Language Python for Data Processing”, IEEE Conference, 978-1-4244-8165-1/11, Sept-2011.

[6]. Fabien Dubosson , Stefano Bromuri, and Michael Schumacher, “A Python Framework for Exhaustive Machine Learning Algorithms and Features Evaluations “, IEEE Conference, 1550-445X/16, March-2016.


[7]. Ankur Bhatia, “Artificial Intelligence – Making an Intelligent personal assistant”, International Journal of Computer Science and Engineering, Vol. 6, No. 6, 2015.

[8]. Nurul Afiqah Mat Zaib , Nor Erne Nazira Bazin , Noorfa Haszlinna Mustaffa , Roselina Sallehuddin, “Integration of System Dynamics with Big Data Using Python: An Overview”, IEEE Conference, 978-1-5090-6255-3/17, May 2017.