Please use this identifier to cite or link to this item: http://212.1.86.13:8080/xmlui/handle/123456789/5143
Title: Python for data processing and modeling indicators of economic security of the country
Authors: Chupilko, T. A.
Ulianovska, Yu. V.
Mormul, M. F.
Shchitov, O. M.
Keywords: Python
data processing
modeling
forecasting
regression model
Issue Date: 10-Apr-2023
Publisher: Online Scientific Publishers OWN
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.
Series/Report no.: International conference “Challenges and realities of the IT space: software engineering and cyber security”;2022, October
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.
URI: http://biblio.umsf.dp.ua/jspui/handle/123456789/5143
ISBN: 978-83-7712-049-1
Appears in Collections:Кафедра комп`ютерних наук та інженерії програмного забезпечення

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