Supply Chain Analysis Python Script
This script provides a comprehensive analysis of a sample supply chain dataset using Python libraries like Pandas and Plotly. It offers insights into various aspects of the supply chain, including:
- Product Performance: Analyzes the relationship between product price and revenue generated, identifies top-selling product types (haircare, skincare, cosmetics), and explores revenue generation by SKU.
- Inventory Management: Examines stock levels for each SKU's.
- Customer Demographics: Analyzes customer demographics associated with product purchases (e.g., Non-binary, Female, Male).
- Lead Times: Investigates average lead times for different product types.
- Shipping Costs: Analyzes total revenue generated by each shipping carrier and compares shipping costs between carriers.
- Transportation Modes: Explores the cost distribution across different transportation modes (Road, Rail, etc.).
- Defect Rates: Calculates average defect rates for product types and analyzes defect rates by transportation mode (identifies Road transportation with a higher defect rate).
Key Libraries:
- Pandas: Data manipulation and analysis
- Plotly: Data visualization
Data Exploration and Visualization:
The script utilizes Pandas to perform data cleaning, calculations, and grouping operations. It then leverages Plotly to create various visualizations like scatter plots, bar charts, and pie charts to present insights effectively.
Instructions:
- Ensure you have Pandas and Plotly libraries installed (
pip install pandas plotly). - Replace the file path in
df=pd.read_csv("F:\\New folder\\ML\\CSV files\\supply_chain.csv")with the actual location of your CSV file containing the supply chain data. - Run the script to execute the analysis and generate visualizations.
Further Exploration:
This script provides a foundation for supply chain analysis. You can extend it to explore additional aspects like:
- Demand forecasting
- Supplier performance analysis
- Network optimization
- Cost-benefit analysis of different transportation modes
This code serves as a starting point for gaining valuable insights into your supply chain data and identifying areas for improvement.