METHODS OF DATA VISUALIZATION USING MATPLOTLIB AND SEABORN
DOI:
https://doi.org/10.5281/zenodo.20292147Keywords:
Data visualization, Python, Matplotlib, Seaborn, statistical analysis, chart types, Data Analytics, visualization aesthetics, trends and anomalies.Abstract
This article explores the significance of data visualization in modern Data Science and the capabilities of using Python's Matplotlib and Seaborn libraries in this process. The text explains the criteria for selecting chart types based on data types (numerical, categorical, time-series, and geographic). Furthermore, it analyzes how the integration of Matplotlib's flexibility and Seaborn's statistical aesthetics simplifies data analysis and enhances the decision-making process.References
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