Project Title:

Forecasting System: Project demand of products at retail outlet based on historical data

Description:

Aim of this project is to forecast demand of products at a retail store based on their past data. Here a forecasting system is created with the help of time series models ARIMA, SARIMA and Fbprophet Library.

Steps involved:

• Load dataset to python environment, clean and sanitize it.
• Choose suitable forecasting model for the dataset.
• Fit the model to dataset and make predictions.
• Visualize the predictions.

Project Outcome:

• Learn about different time series models like ARIMA, SARIMA.
• Used statsmodel library
• Get familiar with Fbprophet library.

Requirements:

• Python
• Jupyter Notebook
• Google Colab
• Windows O.S.(optional)

Libraries Used

• Pandas
• NumPy
• MatPlotlib
• Seaborn
• Statsmodel
• Sci-Kit Learn
• Fbprophet

Data Used: Superstore data downloaded from tableau community is used for this work.

https://community.tableau.com/s/question/0D54T00000CWeX8SAL/sample-superstore-sales-excelxls

Link to code:

https://drive.google.com/file/d/1V5czGqmmbTNAujEt0o5bpzEKbXrF1W-S/view?usp=sharing