Data Wrangling using Python
Siddhartha Ghosh1, Kandula Neha2, Y Praveen Kumar3
1Dr. Siddhrtha Ghosh, Professor, Department of CSE, Vidya Jyothi Institute of Technology College, (Telangana), India.
2Kandula Neha, Assistant Professor, Department of CSE, Vidya Jyothi Institute of Technology College, (Telangana), India.
3Praveen Kumar Yechuri, Assistant Professor, Department of CSE, Vidya Jyothi Institute of Technology College, (Telangana), India.
Manuscript received on 19 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3491-3495 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B14270982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1427.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The term Data Engineering did not get much popularity as the terminologies like Data Science or Data Analytics, mainly because the importance of this technique or concept is normally observed or experienced only during working with data or handling data or playing with data as a Data Scientist or Data Analyst. Though neither of these two, but as an academician and the urge to learn, while working with Python, this topic ‘Data engineering’ and one of its major sub topic or concept ‘Data Wrangling’ has drawn attention and this paper is a small step to explain the experience of handling data which uses Wrangling concept, using Python. So Data Wrangling, earlier referred to as Data Munging (when done by hand or manually), is the method of transforming and mapping data from one available data format into another format with the idea of making it more appropriate and important for a variety of relatedm purposes such as analytics. Data wrangling is the modern name used for data pre-processing rather Munging. The Python Library used for the research work shown here is called Pandas. Though the major Research Area is ‘Application of Data Analytics on Academic Data using Python’, this paper focuses on a small preliminary topic of the mentioned research work named Data wrangling using Python (Pandas Library).
Keywords: Data Engineering, Python, Data Wrangling.
Scope of the Article: Data Base Management System