Python Data Visualization: Dashboards with Plotly & Dash

Explore the anatomy of a Dash application, connecting a front end and back end via a callback that updates a graph from user inputs.

Explore how callback functions connect a color input dropdown to a color output div in a dash app, updating text dynamically via app.callback with inputs and outputs.

Apply prevent updates to avoid runtime errors when no value is selected, and configure run options like debug, host, port, mode inline, and sizing.

Explore the fundamental components of a dash application—the front end and back end—connected by callback functions that respond to user inputs, using pandas to build interactive charts with Plotly.

Explore how Plotly enables interactive dashboard visualizations, covering line, bar, pie, scatter, histogram, and maps, and compare graph objects with Plotly Express for building and customizing charts.

Explore creating interactive visuals with Plotly graph objects and Plotly Express, building a two-series scatter plot from education data with expenditure per student and above/below average math scores.

Build and customize bar charts from a data frame by mapping x and y columns, grouping by state to display average expenditure per student, with sorting, labeling, and color scales.

Plot bubble charts with Plotly by mapping x to total lifts, y to total capacity, and size to gondola lifts; use argmax to create the donut chart and a histogram.

Explore Plotly Dash update methods to customize charts by updating layout, traces, and x and y axes, altering title, legends, fonts, figure size, colors, opacity, markers, and axis formatting.

Explore updating layout and traces in Plotly dashboards, center titles, adjust color scales and color bars, tweak axes, and apply defaults for consistent Python data visualization.

Explore bar chart formatting by selecting the top ten countries, centering the title, and adjusting font color, white background, and black grid lines, while updating the y axis title.

Build a Plotly Express choropleth map of US states by converting state names to two-letter codes, then color by average math scores and scope the visualization to the USA.

Compare plot graph objects for deep customization with Plot Express for quick charting, and learn to build dashboards by creating line, bar, pie, scatter, and choropleth maps in Dash.

Build a Dash app with a dropdown to filter education data by state, then plot year vs total expenditure and explore multi-select, labels, and filtering with the query method.

Build a Dash app that visualizes the number of ski resorts by country, filtered by an elevation slider using count aggregation.

Explore how to implement and customize date pickers in a Dash app, including single and range date inputs, min/max ranges, date formats, and building dynamic filters with callbacks.

Explore how multiple input callbacks empower dashboards with Plotly Dash, using date range pickers and dropdowns to select the X and Y columns, metrics, and colors for a dynamic scatterplot.

Practice basics of HTML and Markdown by building a simple web page layout using headers, paragraphs, spans, and Markdown blocks; modify style arguments and run the server to preview results.

Style the ski resorts map app by adjusting background and font colors, font family, and resizing the slider and checklist components.

Apply and compare bootstrap themes in a Dash app by loading figure templates and using Dash bootstrap templates to achieve cohesive styling across charts, dropdowns, and layouts.

Learn to build grid-based dashboards in Dash using DBC rows and columns, with cards for KPIs and charts, enabling interactive layouts.

Organize dashboards with multiple tabs to separate sections from national KPIs to state insights. Build tabs using Dash Core Components (and Dash Bootstrap Components) to host charts and interactive elements.

Learn to build a multi-tab dashboard by creating tabs, labeling each tab, applying a class name for styling, and embedding layouts and content within each tab.

Modify the map application layout with a left sidebar for interactive elements and a right-side map, and apply a DVC theme using a grid-based layout.

Discover how to add interactive data tables to Dash dashboards with the dash_table module, defining columns and data, enabling sort, filter, and CSV export.

Explore building real-time dashboards in dash using an interval-driven callback. Update a histogram of random normal draws and a stock line chart from the Fin Hub API, with timestamped titles.

Explore advanced callbacks in a Dash dashboard, using a radial toggle to switch between chart and table outputs, with a run button triggering updates and easy free web deployment.

Discover how to deploy your dashboard from a local setup to a server, exploring cloud options like AWS, Azure, Dash Enterprise, Python anywhere, and Heroku.

Explore a final project solution for a Python Dash dashboard with Plotly, featuring a resort map and country profiler, using interactive sliders, checkboxes, dropdowns, and chained callbacks.