Python Data Visualization: Dashboards With Plotly & Dash

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Python Data Visualization: Dashboards With Plotly & Dash
Published 2/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.37 GB | Duration: 8h 35m

Create custom Python visuals, interactive dashboards and web apps using Plotly & Dash, with unique, real-world projects

[b]What you'll learn[/b]

Master the essentials of Plotly & Dash for building interactive visuals, dashboards and web apps

Design and format Plotly visuals, including line charts, bar charts, scatter plots, histograms, maps and more

Learn how to add interactive elements like dropdown menus, checklists, sliders and date pickers

Apply HTML and markdown components to design custom dashboard layouts and themes

Practice building and deploying your own custom web applications with Dash

Explore advanced topics like conditional and chained callbacks, cross-filtering and real-time automation

[b]Requirements[/b]

We'll use Anaconda & Jupyter Notebooks (a free, user-friendly coding environment)

Familiarity with base Python and the Pandas library are strongly recommended, but not a strict prerequisite

[b]Description[/b]

This is a hands-on, project-based course designed to help you master Plotly and Dash, two of Python's most popular packages for creating interactive visuals, dashboards and web applications.We'll start by introducing the core components of a Dash application, review basic front-end and back-end elements, and demonstrate how to tie everything together to create a simple, interactive web app.From there we'll explore a variety of Plotly visuals including line charts, scatterplots, histograms and maps. We'll apply basic formatting options like layouts and axis labels, add context to our visuals using annotations and reference lines, then bring our data to life with interactive elements like dropdown menus, checklists, sliders, date pickers, and more.Last but not least we'll use Dash to build and customize a web-based dashboard, using tools like markdown, HTML components & styles, themes, grids, tabs, and more. We'll also introduce some advanced topics like data tables, conditional and chained callbacks, cross-filters, and app deployment options.Throughout the course you'll play the role of a Data Analyst for Maveluxe Travel, a high-end agency that helps customers find flights and resorts based on their travel preferences. Your task? Use Python to create interactive visuals and dashboards to help Maveluxe's travel agents best support their customers.COURSE OUTLINE:Intro to Plotly & DashIntroduce the Plotly & Dash libraries, and cover the key steps and components for creating a basic Dash application with interactive Plotly visualsPlotly Figures & Chart TypesDive into the Plotly library and use it to build and customize several chart types, including line charts, bar charts, pie charts, scatterplots, maps and histogramsInteractive ElementsGet comfortable embedding Dash's interactive elements into your application, and using them to manipulate Plotly VisualizationsMID-COURSE PROJECTBuild two working Dash applications to help the Maveluxe team visualize and explore data from ski resorts across the US and CanadaDashboard LayoutsLearn how to organize your visualizations and interactive components into a visually appealing and logical structureAdvanced FunctionalityTake your applications to the next level by learning how to update your application with real-time data, develop chained-callback functions, and more!FINAL PROJECTBuild a multi-tab dashboard to expand your mid-course project to ski resorts around the world, leveraging grid layouts, interactive elements and visuals, and advanced callback functionsJoin today and get immediate, lifetime access to the following:8.5 hours of high-quality videoPlotly & Dash PDF ebook (180+ pages)Downloadable project files & solutionsExpert support and Q&A forum30-day Udemy satisfaction guaranteeIf you're a data scientist, analyst or business intelligence professional looking to add Plotly & Dash to your Python skill set, this is the course for you!Happy learning!-Chris Bruehl (Python Expert & Lead Python Instructor, Maven Analytics)

Overview

Section 1: Getting Started

Lecture 1 Course Structure & Outline

Lecture 2 READ ME: Important Notes for New Students

Lecture 3 DOWNLOAD: Course Resources

Lecture 4 Introducing the Course Project

Lecture 5 Setting Expectations

Lecture 6 Jupyter Installation & Launch

Section 2: Intro to Plotly & Dash

Lecture 7 Why Interactive Visuals?

Lecture 8 Installing Plotly & Dash

Lecture 9 The Anatomy of a Dash Application

Lecture 10 The World's Simplest Dash App

Lecture 11 Dash Component Deep Dive

Lecture 12 Interactive Elements

Lecture 13 Callback Functions

Lecture 14 DEMO: Callback Functions

Lecture 15 Options for Running Your Application

Lecture 16 ASSIGNMENT: Simple Dash Application

Lecture 17 SOLUTION: Simple Dash Application

Lecture 18 Plotly Visuals & Dash Graph Components

Lecture 19 Tying Interactive Elements to Visuals

Lecture 20 ASSIGNMENT: A More Realistic Dash App

Lecture 21 SOLUTION: A More Realistic Dash App

Lecture 22 Key Takeaways

Section 3: Plotly Figures & Charts

Lecture 23 Intro to Plotly Charts

Lecture 24 DEMO: Plotly Graph Objects

Lecture 25 DEMO: Plotly Express

Lecture 26 Basic Plotly Charts

Lecture 27 DEMO: Scatterplots & Line Charts

Lecture 28 ASSIGNMENT: Line Charts

Lecture 29 SOLUTION: Line Charts

Lecture 30 Plotting Multiple Series

Lecture 31 DEMO: Bar Charts

Lecture 32 ASSIGNMENT: Bar Charts

Lecture 33 SOLUTION: Bar Charts

Lecture 34 Pro Tip: Bubble Charts

Lecture 35 Pie & Donut Charts

Lecture 36 ASSIGNMENT: Donut & Bubble Charts

Lecture 37 SOLUTION: Donut & Bubble Charts

Lecture 38 Histograms

Lecture 39 Update Methods

Lecture 40 DEMO: Updating Layout & Traces

Lecture 41 DEMO: Updating X and Y Axes

Lecture 42 Adding Annotations

Lecture 43 ASSIGNMENT: Chart Formatting

Lecture 44 SOLUTION: Chart Formatting

Lecture 45 Choropleth Maps

Lecture 46 DEMO: Choropleth Maps

Lecture 47 Mapbox Maps

Lecture 48 DEMO: Density Maps

Lecture 49 ASSIGNMENT: Maps

Lecture 50 SOLUTION: Maps

Lecture 51 Key Takeaways

Section 4: Interactive Elements

Lecture 52 Intro to Interactive Elements

Lecture 53 Interactive Element Overview

Lecture 54 Dropdown Menus

Lecture 55 DEMO: Dropdowns

Lecture 56 Checklists

Lecture 57 ASSIGNMENT: Checklists

Lecture 58 SOLUTION: Checklists

Lecture 59 Radio Buttons

Lecture 60 Sliders

Lecture 61 Range Sliders

Lecture 62 ASSIGNMENT: Sliders

Lecture 63 SOLUTION: Sliders

Lecture 64 Date Pickers

Lecture 65 DEMO: Date Pickers

Lecture 66 Multiple Input Callbacks

Lecture 67 Multiple Output Callbacks

Lecture 68 ASSIGNMENT: Multiple Interactive Elements

Lecture 69 SOLUTION: Multiple Interactive Elements

Lecture 70 Key Takeaways

Section 5: MID-COURSE PROJECT

Lecture 71 Mid-Course Project Introduction

Lecture 72 Mid-Course Project Solution

Section 6: Dashboard Layouts

Lecture 73 Intro to Dashboard Layouts

Lecture 74 Visual Elements & Layout Options

Lecture 75 Revisiting Dash App Layouts

Lecture 76 HTML & Markdown

Lecture 77 ASSIGNMENT: HTML & Markdown

Lecture 78 SOLUTION: HTML & Markdown

Lecture 79 HTML Styles

Lecture 80 Styling Interactive Elements

Lecture 81 Styling Plotly Figures

Lecture 82 ASSIGNMENT: App Styling

Lecture 83 SOLUTION: App Styling

Lecture 84 Dash Bootstrap Components

Lecture 85 Dash Bootstrap Themes

Lecture 86 DEMO: Applying a Bootstrap Theme

Lecture 87 Grid-Based Layouts

Lecture 88 DEMO: Grid-Based Layouts

Lecture 89 Multiple Tabs

Lecture 90 DEMO: Multiple Tabs

Lecture 91 ASSIGNMENT: Building a Layout

Lecture 92 SOLUTION: Building a Layout

Lecture 93 Key Takeaways

Section 7: Advanced Topics

Lecture 94 Intro to Advanced Topics

Lecture 95 Dash Data Tables

Lecture 96 DEMO: Data Tables

Lecture 97 ASSIGNMENT: Data Tables

Lecture 98 SOLUTION: Data Tables

Lecture 99 Conditional Callbacks

Lecture 100 Chained Callbacks

Lecture 101 Pro Tip: Debug Mode

Lecture 102 Interactive Cross-Filtering

Lecture 103 Manually Firing Callbacks

Lecture 104 Periodically Firing Callbacks

Lecture 105 DEMO: Real-Time Updates

Lecture 106 ASSIGNMENT: Advanced Callbacks

Lecture 107 SOLUTION: Advanced Callbacks

Lecture 108 App Deployment Options

Lecture 109 DEMO: App Deployment

Lecture 110 Key Takeaways

Section 8: FINAL COURSE PROJECT

Lecture 111 Final Project Introduction

Lecture 112 Final Project Solution

Section 9: BONUS LESSON

Lecture 113 BONUS LESSON

Analysts or Data Scientists who want to build interactive visuals, dashboards or web apps,Aspiring data scientists who want to build or strengthen their Python data visualization skills,Anyone interested in learning one of the most popular open source programming languages in the world,Students looking to learn powerful, practical skills with unique, hands-on projects and course demos

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