USING PROGRAMMING LANGUAGES TO ANALYZE INFLATION: AN APPLIED APPROACH BASED ON OPEN DATA

UDC 336.74: 004.42
DOI: 10.36871/ek.up.p.r.2025.06.04.008

Authors

Sveta S. Gatsaeva,
Grozny State Oil Technical University named after Academician M. D. Millionshchikov, Grozny, Russian Federation
Osman M. Minaev,
Chechen State University named after A. A. Kadyrov, Grozny, Russian Federation
Adela R. Nurullina,
Naberezhnye Chelny Branch of the University of Management “TISBI”, Naberezhnye Chelny, Russian Federation

Abstract

Analyzing inflation processes requires prompt and structured handling of heterogeneous macroeconomic data. With the expansion of open-source data and the development of data processing technologies, programming languages are becoming increasingly important tools for applied analysis. The article discusses methodological and technical aspects of using Python and R for inflation monitoring, processing of aggregated and raw indicators, building analytical models, and result visualization. It reviews representative open data sources used in inflation analysis, including national and international statistical platforms. A practical case is presented for implementing an automated procedure for calculating inflation indicators using official data. The role of programming tools is substantiated in ensuring the reproducibility of analytical procedures, reducing modeling costs, and increasing accessibility to macroeconomic research.

Keywords

inflation, Python, R, open data, consumer price index, API, statistical modeling, digital economy, macroeconomic monitoring, parsing