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Python for data processing and modeling indicators of economic security of the country

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dc.contributor.author Chupilko, T. A.
dc.contributor.author Ulianovska, Yu. V.
dc.contributor.author Mormul, M. F.
dc.contributor.author Shchitov, O. M.
dc.date.accessioned 2023-04-10T11:25:07Z
dc.date.available 2023-04-10T11:25:07Z
dc.date.issued 2023-04-10
dc.identifier.citation Chupilko T. A., Ulianovska Yu. V., Mormul M. F., Shchitov O. M. Python for data processing and modeling indicators of economic security of the country. International conference “Challenges and realities of the IT space: software engineering and cyber security”, 2022, October. uk_UA
dc.identifier.isbn 978-83-7712-049-1
dc.identifier.uri http://biblio.umsf.dp.ua/jspui/handle/123456789/5143
dc.description.abstract The article considers aspects of efficient data processing. There are defined the stages of working with data and the features specific to each stage. There are considered packages NumPy, Pandas, Matplotlib, SciPy, Statsmodels and Scikit-learn. An example of using Python for customs tasks is given, taking into account the indicators of the country's economic security. The authors have created a calculation program that applies the above packages. A line of re-gression models are built to analyze the replenishment of the state budget of Ukraine with cus-toms revenues at the expense of import and export duties. The analysis of models on the basis of econometric methods of modeling is carried out and forecast estimates of revenues are cal-culated. uk_UA
dc.language.iso en uk_UA
dc.publisher Online Scientific Publishers OWN uk_UA
dc.relation.ispartofseries International conference “Challenges and realities of the IT space: software engineering and cyber security”;2022, October
dc.subject Python uk_UA
dc.subject data processing uk_UA
dc.subject modeling uk_UA
dc.subject forecasting uk_UA
dc.subject regression model uk_UA
dc.title Python for data processing and modeling indicators of economic security of the country uk_UA
dc.type Article uk_UA


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