Exploring the Impact of Weather on Short-time Demand Forecast for Fashion Retailers.
OurDashboard
will predict your inventory requirements with the help ofpast sales
and real-timeweather forecast
Go to the app folder and run:
python app.py
Make sure to install the requirements before you start the flask app.
Clone the repository:
git clone https://github.com/inderpartap/trendcast.git
Install the application requirements in a linux environment:
pip install requirements.txt
Make sure to add a retail dataset in the data folder to start working.
Columns used in our the dataset are (date, province, city, category, department, class, article, totalSales, totalQuantity)
That's it. You can now start contributing to the project.
Thanks to the following people who have contributed to this project:
- @inderpartap 🎨 💻
- @najq 📹 💻
- @pallavibharadwaj 📆 💻
- @THEMrinaal 🔣 💻
Contributions, issues and feature requests are welcome.
Feel free to check
issues page if you want to
contribute.
To contribute to Trendcast, follow these steps:
- Fork this repository.
- Create a branch:
git checkout -b <branch_name>
. - Make your changes and commit them:
git commit -m '<commit_message>'
- Push to the original branch:
git push --set-upstream origin <branch_name>
- Create the pull request.
Alternatively see the GitHub documentation on creating a pull request.
Please ⭐️ this repository if this project helped you!