Using Data Science tools in a Mexican Company.

Welcome to the repository dedicated to the culmination of the "Project Development" course within the Master's in Data Science (MCD) program at the University of Guadalajara. Within these files, you'll find the comprehensive work and results derived from the final project, which revolves around the exploration and analysis of a dataset closely tied to our thesis project.

The thesis project consist in characterize and analyze the supply chain supply of a Mexican company in the area of internal purchasing to balance spending in the different types of stores through data science tools and develop a proposal for improvement in decision making and the return on investment.

The primary objective of this project is to harness the power of Python's visual tools, encompassing diverse graphical representations and mapping techniques. Additionally, sophisticated analytical tools, including text analysis and Natural Language Processing (NLP), are employed to gain deeper insights into the dataset.

As part of our pursuit and academic goals, this project delves into the intricacies of our master's thesis, utilizing advanced data science methodologies. The repository provides a detailed account of the data exploration, visualization, and analytical processes undertaken to unravel the nuances of our research topic.

Feel free to explore the various files and outcomes enclosed here, gaining a firsthand understanding of the application of visual and analytical tools in the context of our compelling thesis project.

Repository Structure

├── LICENSE           <- MIT License.  
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├── README.md         <- Main Readme file with the description of the project.  
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├── CONTRIBUTING.md   <- Steps yo contribute to the project.  
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├── CITATION.md       <- Way to cite the project.  
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├── data              <- Original data bases.  
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├── doc               <- Text files.  
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├── results           <- Clean and analyzes data bases.  
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└── src               <- Coding files.  

References

• using the paper "Good Enough Practices in Scientific Computing" of Greg Wilson, Jennifer Bryan, Karen Cranston, Justin Kitzes, Lex Nederbragt, Tracy K. Teal. as base.
• using the page "Usos y tipos de gráficos con la librería Altair" as base.
• using the work "Visualización con Altair" of Victor Cuspinera as base.
• Using the page "Visualización de Datos con Altair" of Sergio Sánchez as base.
• https://geopandas.org/en/stable/gallery/polygonplottingwith_folium.html
• https://matplotlib.org/stable/users/explain/colors/colormaps.html
• https://github.com/vcuspinera/UDGMCDProjectDevI/tree/main/proyectos/final