Data Visualization with Python - Plotly & Dash

scrape stock data from the screener to learn sector and industry weights. merge screener data with last positions and latest prices to create sunburst charts in dash.

Learn to build bar charts comparing population by year for Germany and the United States, then create a faceted, multi-chart view by continent and year with 4-column facets.

Explore graph objects in Plotly to build charts from the ground up with go.Bar traces. Customize layout, bar mode, height, and templates to tailor multi-trace charts for dashboards.

Explore advanced figure customization in Plotly and Dash, adjusting margins, axes, grid, and colors, updating traces and text for interactive dashboards.

Create a portfolio value chart using Plotly graph objects in dark mode, featuring a date-based x-axis and portfolio value y-axis, with a customizable hover template.

Create and customize a dash data table in a dashboard by building a data frame of dictionaries, defining a dash_table element, running the app, and exploring sorting and filtering options.

Explore how a sunburst chart aggregates a portfolio from stocks to sectors and industries, enabling interactive exploration to identify underperformers like DocuSign and leaders like Nvidia, guiding rebalancing decisions.

Create a continuous color scale sunburst to show portfolio value and gains by region, using levels, color and value columns in Plotly, then build a Dash dashboard.

Learn to build a dash page with two rows and one column per row using an html component and a header, applying width, offset, and order for a symmetric layout.

Adapt a Dash documentation example by importing data, creating a simple dashboard with a div and a graph component, and arranging it in responsive columns to render a chart.

Learn to add interactivity to dashboards with callbacks and dropdowns in Plotly Dash, enabling interactive charts such as scatter plots using the Gap data set.

Create the Dash callback to link a year dropdown to updating a scatterplot figure. Build the app layout, filter the dataframe by the selected year, and render the updated chart.

Master dashboard customization with Dash bootstrap themes, add a sidebar and multi-page navigation. Use a local assets folder for offline styling by placing a CSS file in assets.

Learn to customize dashboards by changing themes and using Bootstrap class name to apply background color, margins, and text styles, with guidance from Dash and Bootstrap documentation.

Set up the dashboard's bootstrap-based sidebar and homepage, wiring a ticker dropdown to filter charts and tables while arranging a three-row layout with a sunburst, charts, and KPIs.

Build the ticker view with a dropdown tied to a ticker dictionary and a main chart, then show three dash tables alongside a sunburst explorer of industry, sector, and stock.

Learn how to implement callback functions in a Dash app, including advanced multi-output callbacks driven by a ticker selector to update charts and data tables.

Explore how a dash callback returns seven outputs, including the main figure and each table's columns and data, to drive interactive stock information.