<![CDATA[This study aims to analyze global temperature data by employing computer visualization as a tool to simplify complex information. The dataset was obtained from Kaggle, specifically the Global Land Temperatures by City dataset, which contains monthly average temperature data from various cities worldwide. The methods applied include data preprocessing, descriptive statistical analysis, and data visualization using the Python programming language with the Pandas, Matplotlib, and Seaborn libraries. The visualization results reveal an upward trend in the global average temperature from 1900 to 2020, with an increase of approximately 1°C, indicating the occurrence of global warming. Computer visualization has proven to be effective in helping researchers and policymakers better understand temperature change patterns compared to numerical table-based analysis. Therefore, this study emphasizes that the application of computer visualization is an efficient solution for presenting and analyzing large-scale data, making it more interpretable.]]>
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