Processing large amounts of data in Python for the purposes of applied socio-economic research: advantages and current issues

Abstract

The article is devoted to the study of the features of processing large amounts of data using the Python programming language. Unlike tabular processors or finished software products, programming languages offer the user a flexible toolkit for the implementation of tasks. At the same time, this creates certain risks associated with the effectiveness of using appropriate tools and optimising the operation of the programme. The purpose of the article is to study the features of processing large amounts of data in Python on the examples of immediate research tasks. The relevance of the topic and purpose of the article is due to the existing scientific gap related to a comprehensive consideration of the technical aspects of the use of programming languages and associated tools for socio-economic research. Thus, many authors who use programming languages in their works rarely provide information regarding the advantages of certain algorithms or approaches. Within the framework of the article, the author examines the procedures and algorithm of processing a large array of data on the example of specific research tasks. The conclusions are drawn about the features and advantages of Python when working with large amounts of data as well as about the prospects for the development of the relevant scientific topics.

Keywords

• programming language
• python
• data analysis
• data processing
• large data sets
• processing algorithm
• applied research
• socio-economic research
• technical aspects
• scientific work