Explaining how data analysis can be useful for decision-making and improvement in the logistics industry!
The data analysis approach in logistics is required in various aspects such as inventory management, route optimization, and demand forecasting. However, insights gained from data are essential for its realization. This article focuses on the statistical analysis of logistics data using the programming language Python, examining how data analysis can aid decision-making and improvements in the logistics industry. Specifically, it will explain data processing and statistical analysis examples using Python libraries such as Pandas and NumPy, through case studies using real data. *For more details about the blog, you can view it through the related links. Please feel free to contact us for more information.*
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