Livestock Price Prediction in Iran

This project predicts livestock prices in Iran using a dataset of 31,534 entries spanning from 1392-01-01 to 1403-04-24 (Iranian calendar).

Features

• Predicts livestock prices based on daily timestamps
• Uses data mined from itpnews.com
• Provides price predictions with an error range

Data Mining

The dataset is sourced from itpnews.com. To update the dataset:

1. Navigate to the scrapping directory
2. Run main.py

python scrapping/main.py

Usage

After running all cells in the notebook:

1. Call the guess_the_price function
2. Pass the desired date as arguments (year, month, day)

Example

predicted_price = guess_the_price(1403, 5, 10)

This returns an int value representing the predicted price for the given date.

Error Range

The mae_error variable provides an error margin. To get a price range:

lower_bound = predicted_price - mae_error
upper_bound = predicted_price + mae_error