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bettyabay/chemical-import-insights

Domain:

socioeconomic
Creator:
bet
Host:
Analysis of Ethiopian chemical import data (HS Code 3905) using Python and AI to uncover market trends, categorize items, and identify potential suppliers. Designed for scalability to handle large trade datasets. # chemical-import-insights Analysis of Ethiopian chemical import data (HS Code 3905) using Python and AI to uncover market trends, categorize items, and identify potential suppliers. Designed for scalability to handle large trade datasets. ## Project Overview This project focuses on analyzing Ethiopian import data for items within HS Code 3905 (Polyvinyl acetate or other vinyl esters and other vinyl polymers). The goal is to extract valuable insights, categorize imported items, identify potential global suppliers, and understand the behavior of importing traders. We utilize Python and various data analysis and AI techniques to achieve these objectives, with a strong emphasis on scalability for handling large datasets. ## Key Objectives * **Data Cleaning and Organization:** Preprocess the raw data for analysis. * **Item Identification and Categorization:** Determine the exact nature of imported items and group them into relevant categories. * **Supplier Identification:** Identify potential global suppliers based on available data. * **Trader Analysis:** Categorize importers by business type to understand import purposes. * **AI-Driven Insights:** Uncover hidden patterns and trends using AI techniques. * **Scalability:** Develop a methodology applicable to large-scale trade data. ## Technologies Used * **Python:** Programming language for data analysis and AI. * **Pandas:** Data manipulation and analysis library. * **NumPy:** Numerical computing library. * **Openpyxl:** Excel file handling. * **(Potentially) Scikit-learn, NLTK, etc.:** For advanced AI tasks (clustering, NLP). ## Getting Started 1. **Clone the Repository:** ```bash git clone [repository URL] cd chemical-import-insights ``` 2. **Install Dependencies:** ```bash pip install pandas numpy openpyxl ``` 3. **Place Data:** Put your excel file in the same directory as the python scripts. 4. **Run the Analysis:** (Replace `data_analysis.py` with the name of your main script.) ## Methodology …

Visit

github.com

Languages

Amharic

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