Data Visualization with Python - Plotly & Dash

You will learn how to create awesome dashboards using Plotly and Dash. The result will be a multipage interactive dashboard to help you monitor a stocks portfolio. The main goal is to give you the right tools to help you build any dashboard you need, or simply adapt existing ones! No coding experience is required.

This is an end-to-end project. This means I will guide you through all the steps and show you how you can adapt the code to your own needs.
Below you can find a high-level summary of what we will cover in over 4 hours of content:

Data Preparation and Scraping

• Get started with the course materials

• Read csv files and transform them into dataframes and dictionaries

• Use a set of custom functions to scrape stocks information from multiple sources and store it

• Use a special script to gain additional insights about your portfolio (works with Stocks, Crypto, ETF’s, etc), including average costs of your positions

  
  

Plotly

• Quickly start using Plotly Express

• Understand how Plotly Graph Objects can help you customize your graphs

• Create any type of chart to tell your story, with your own data

• Customize your graphs with very few lines of code

• Learn how to explore the documentation to find what you need
  

Dash

• Create your first Dash app

• Organize the dashboard elements inside the app

• Use Bootstrap themes to customize the app style

• Create a Sidebar with navigation buttons

• Create a dashboard with multiple pages

• Explore Dash documentation and pick examples to adapt to your projects
  

You will be able to

• Create a professional dashboard from scratch with just a few basic inputs

• Keep track of your own portfolio performance, if you own one!

• Retire your old Excel dashboards and explore new possibilities with Plotly and Dash

And much more: background colors, dark themes, multiple callbacks, multiple outputs, graph height and width, rows and columns, dash layout, bootstrap components, plotly express, plotly graph objects, dropdowns, custom labels, html components, plotly indicators, candlestick graphs, scatter plots, bar charts...