Module 2: Investment Dashboards with Streamlit
Part of Specialization: Data Visualization Using Python
Self-paced - Mentor-led - 7 weeks - 3 Modules
Module 2: Investment Dashboards with Streamlit
🕑 9 Lessons · Deliverable: Deployed live investment dashboard
A chart answers a question. A dashboard answers every question a stakeholder might walk in with. In Module 2, you design and build a fully interactive investment dashboard using Streamlit — Python’s fastest route from analysis to a deployed, shareable web application. No front-end knowledge required. A live URL to show employers and clients within hours, not weeks.
You source live stock data using yfinance — price, volume, and fundamentals including P/E ratio, market cap, and earnings — and apply the full Python visualization library stack to present it. The final lesson covers the skill that separates junior from senior analysts: knowing how to present your work to a room that did not build it.
Tools for Creating Dashboards
The Python dashboard landscape: Streamlit, Dash, Panel, Voilà. When to use each. Why we build with Streamlit in this module — and when Dash is the right answer instead.
Project Planning and Sourcing Data with yfinance
Scoping a dashboard project before writing code. Using yfinance to pull stock price, volume, and fundamentals — P/E ratio, market cap, earnings — and structure it for a dashboard.
Static Charts with Matplotlib
The object-oriented approach to Matplotlib — fig, ax. Multi-panel subplots, dual-axis charts for price and volume, and the styling that takes a chart from functional to publication-quality.
Statistical Visualization with Seaborn
Seaborn’s statistical plot types for surfacing patterns in financial data — distributions, categorical comparisons, and FacetGrid for comparing tickers side by side. Consistent themes and palettes across your visualization set.
Interactive Charts with Plotly
Plotly Express and Plotly Graph Objects. Candlestick charts, hover data, subplots, and animations — the building blocks of every interactive dashboard.
Advanced Geospatial Plotting with Folium
Choropleth and point maps with Folium and Plotly. Market presence, revenue by country, headquarter locations — when a map is the only chart that tells the story.
Building Dashboards with Streamlit
A multi-chart Streamlit investment dashboard from scratch. Ticker dropdowns, date pickers, metric selectors, and live chart updates — connecting widgets to real market data.
Refining and Deploying a Streamlit Dashboard
The gap between a working dashboard and a presentation-ready one. Colour, labelling, caching for performance, and one-click deployment to Streamlit Community Cloud. Your live URL.
Portfolio and Branding
Your live dashboard URL is your business card. Writing a case study — problem, data, methodology, insight — for a business or investment audience, not a technical one.
📄 Module 2 Deliverable: A fully interactive investment dashboard, deployed and publicly accessible via Streamlit Community Cloud. Live yfinance-sourced data including price, volume, and fundamentals. At least one geospatial visualization. Annotated Colab notebooks. One LinkedIn case study post written for a business, not a technical, audience.
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