How samirshaikh2425/crop-price-prediction works
This is a Streamlit application for estimating crop prices, comparing mandi markets, and predicting crop yields. Users provide crop and market selections or cultivation inputs; the app combines dataset records with saved prediction models to show estimates and comparisons. A separate training script preprocesses both datasets, evaluates candidate regressors, and saves model bundles and metrics. The app excerpt supports its data/model loading and dashboard features, while README documents the broader capabilities; implementation details omitted from the excerpts are not assumed.
Main entry points: app.py Streamlit application · train_model.py Training workflow · daily_wholesale_crop_prices.csv Mandi price records · crop_yield.csv Yield records
Components 12
Streamlit experience
- Streamlit application
app.py - Price estimate
app.py - Market comparison
app.py - Yield prediction
app.py
Prediction data and models
- Mandi price records
data/daily_wholesale_crop_prices.csv - Yield records
data/crop_yield.csv - Price model bundle
models/crop_price_model.pkl - Yield model bundle
models/crop_yield_model.pkl
Model training
- Training workflow
train_model.py - Price evaluation metrics
models/crop_price_model_evaluation.csv - Yield evaluation metrics
models/crop_yield_model_evaluation.csv
Other components
- Farmer or trader
Connections 17
- Farmer or trader → Streamlit application: uses
README.md - Streamlit application → Mandi price records: loads
app.py - Streamlit application → Yield records: loads
app.py - Streamlit application → Price model bundle: loads
app.py - Streamlit application → Yield model bundle: loads
app.py - Streamlit application → Price estimate: offers
app.py - Streamlit application → Market comparison: offers
app.py - Streamlit application → Yield prediction: offers
app.py - Price estimate → Mandi price records: filters records
app.py - Market comparison → Mandi price records: summarizes markets
app.py - Yield prediction → Yield records: uses options
app.py - Training workflow → Mandi price records: reads
train_model.py - Training workflow → Yield records: reads
train_model.py - Training workflow → Price model bundle: saves bundle
train_model.py - Training workflow → Yield model bundle: saves bundle
train_model.py - Training workflow → Price evaluation metrics: writes metrics
train_model.py - Training workflow → Yield evaluation metrics: writes metrics
train_model.py