Abstract
Python application was used for Gross Domestic Product (GDP) to indicator cooralation calculation. Python application also stored coorelation calculations to CSV files, having data values groped by year. GDP data was loaded in to QGIS from CSV files, which were than shown on Europe map for a span of ten year period. It was concluded that „Rurhal“ and „Urban Population“ have greatest impact on GDP. It was also shown how we can use software in order to analyse big data problems.
References
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