Welcome to the Data Visualization project built with Django. This project aims to provide insights into the data_sales.xlsx
dataset using various visualizations implemented in a Django dashboard.
To set up the project, follow these steps:
-
Clone the repository.
-
Navigate to the project directory:
cd adidas-sales-visualization
-
Create virtual environment:
python -m venv venv
-
Activate the environment: Windows:
.\venv\Scripts\activate
macOS/linux
source venv/bin/activate
-
Install the required dependencies using the following command:
pip install -r requirements.txt
-
Run the Django development server:
python manage.py runserver
- First Step: Open the
dataset/data_sales.xlsx
dataset to gain insights into its structure and variables. - Preparing Your Data: Describe any data preprocessing steps undertaken for better analysis.
- Retailer Analysis: Utilized bar charts to compare total sales and operating profit by retailer.
- Trends: Implemented line graphs to visualize trends over time for variables like
Total Sales
andUnits Sold
. - Geographical Insights: Employed maps and choropleth maps to visualize sales by region or state.
- Product Analysis: Utilized pie charts and bar charts to display the distribution of sales among different products.
- Price Analysis: Created scatter plots to understand the relationship between
Price per Unit
andUnits Sold
orTotal Sales
. - Sales Method Analysis: Visualized the distribution of sales by different sales methods using pie charts or bar charts.
- Additional Insights: Utilized various appropriate charts for additional variables.
- Consistency: Maintained a consistent color scheme and style across all visualizations.
- Readability: Ensured charts are easily readable with clear labels, legends, and titles.
- Highlight Key Insights: Used annotations, highlighting, or visual cues to emphasize important findings.
- Analysis: Provided brief analyses for each visualization, identifying trends, outliers, or interesting patterns.
- Insights: Summarized key insights and considered implications on Adidas's sales strategy and operations.
- Django==5.0.2
- numpy==1.26.4
- pandas==2.2.1
- python-dotenv==1.0.1
- sqlparse==0.4.4
If you'd like to contribute to this project, please follow our Contributing Guidelines.
This project is licensed under the MIT License - see the LICENSE.md file for details.