How rishabhzn200/stock-data-visualization-using-bokeh works
This is a small Bokeh application for interactively comparing five years of S&P 500 stock prices. It loads the CSV, presents an initial chart and stock selector, then lets users add tickers and toggle them to refresh the chart. The runtime is concentrated in Stocks.py; the graph separates its interaction stages from rendering. The available excerpt shows the CSV loading and callback wiring, but not a separate server or deployment setup.
Main entry points: Stocks.py App startup · all_stocks_5yr.csv Stock history CSV
Components 9
Visualization runtime
- App startup
Stocks.py - Ticker dropdown
Stocks.py - Menu handler
Stocks.py - Ticker checkboxes
Stocks.py - Checkbox handler
Stocks.py - Plot updater
Stocks.py - Bokeh chart document
Stocks.py
Stock data
- Stock history CSV
all_stocks_5yr.csv
Other components
- Viewer
Connections 11
- App startup → Stock history CSV: loads
Stocks.py - App startup → Ticker dropdown: creates
Stocks.py - App startup → Bokeh chart document: adds initial chart
Stocks.py - Viewer → Ticker dropdown: selects ticker
Stocks.py - Ticker dropdown → Menu handler: dispatches change
Stocks.py - Menu handler → Ticker checkboxes: creates checkbox
Stocks.py - Viewer → Ticker checkboxes: toggles ticker
Stocks.py - Ticker checkboxes → Checkbox handler: dispatches change
Stocks.py - Checkbox handler → Plot updater: calls update
Stocks.py - Plot updater → Stock history CSV: filters ticker data
Stocks.py - Plot updater → Bokeh chart document: rebuilds chart
Stocks.py