Sales Forcasting WIth Time series analysis developed a sales forecasting system using Time Series and Causal Models, effectively predicting trends and external impacts on product sales. Primary task : Perform time series analysis to understand the data and trends Use multiple forecasting models on sales dataset
This project involves building a regression model to predict sales data over time. The dataset includes sales data from various stores and items over a specified period. The goal is to develop a model that can accurately forecast future sales based on historical data.
The dataset used in this project contains the following columns:
- date: The date of the sales record.
- store: The store identifier.
- item: The item identifier.
- sales: The number of sales.
- f0: Feature 0 (additional feature, if any).
- f1: Feature 1 (additional feature, if any).
The dataset is preprocessed to handle missing values and to convert the date column to a datetime format.
To run this project, you need to have Python and the following libraries installed:
- pandas
- numpy
- matplotlib
- scikit-learn
You can install these libraries using pip:
pip install pandas numpy matplotlib scikit-learn