Article Details

Abstract

Quickly and accurately cleaning and analyzing large-scale raw data, extracting effective information, and forming scientific and concise visualization charts are the key links to improve the efficiency of Big Data analysis work. Based on Python programming language, this paper takes meteorological Big Data above millions as an example to carry out data cleaning, analysis and visualization processing and implementation, aiming at improving the processing efficiency and visualization effect of meteorological data. At the same time, it provides ideas and references for the high efficiency cleaning, analysis, and visualization work of Big Data above millions in all other industries. Python and its third-party libraries can be used to quickly and accurately clean and analyze massive structured Big Data, and present rich and customizable data visualization charts.

Keywords

Python; meteorological Big Data; data cleaning; data analysis; data visualization

References

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Funding

Special Project for Student Financial Assistance in the 14th Five Year Plan of Guangxi Education Science in 2024 (2024ZJY1224); Research Foundation Ability Enhancement Project for Young and Middle aged Teachers in Guangxi Universities (2023KY1048)

About the authors

Ling Ning (1987-), male, Zhuang ethnicity, from Nanning, Guangxi, is a senior engineer with a master's degree. His research interests include software technology and artificial intelligence technology; Guo Jin (1983-), female, Han ethnicity, from Shenyang, Liaoning Province, engineer, master's degree, research direction: big data technology and applications.