Plotly Dash TA Stock Market App
- The objective of this post is to deploy a Plotly Dash stock market app in Python using the dashboard of user-defined stock prices with popular technical indicators available in TA.
- Read more the tutorial on plotting stock price chart along with volume, MACD & stochastic.
- The entire workflow consists of the following 5 steps:
- Step 1: Select a stock ticker symbol (NVDA) and retrieve stock data frame (df) from yfinance API at an interval of 1m
- Step 2: Add Moving Averages (5day and 20day) to df and plot live share price
- Step 3: Add Volume, MACD, and Stochastic Oscillator from TA
- Step 4: Save our stock chart in HTML form, which means all the interactive features will be retained in the graph
- Step 5: Implement the Plotly Dash app containing live NVDA stock prices with MA 5–15–50–200, Volume, RSI, and MACD.
Summary
- In this post, we have used Plotly to generate interactive visualizations of NVIDIA stock prices and basic technical indicators from TA
- The Plotly Dash framework has been employed for building web app with the added benefit that no JavaScript is needed.
- Plotly Dash provides increased interactivity and the ability to manipulate data with modern UI elements like dropdowns, sliders and real-time graphs.
- Plotly figures are interactive when viewed in a web browser: we can hover over data points, pan and zoom axes, and show and hide traces by clicking or double-clicking on the legend. We have exported them to HTML files which can be opened in a browser.
- The most significant benefits include our preference for the dashboard layout of all of the charts instead of separate cells of the Jupyter notebook.
- By default, Dash apps run on
localhost. To share a Dash app, we need to deploy it to a server using Dash Enterprise.
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