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Python Data Visualization: Dashboards With Plotly & Dash - BaDshaH - 07-25-2024
![[Image: 8629ce650072d6bfb2b8b24fc8a58c50.jpg]](https://i123.fastpic.org/big/2024/0725/50/8629ce650072d6bfb2b8b24fc8a58c50.jpg)
Last updated 5/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.00 GB | Duration: 8h 33m
Build Python visuals, dashboards and web apps using Plotly & Dash, w/ a top Python data science & analytics instructor!
What you'll learn
Master Python's Plotly & Dash libraries 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 Python & Dash
Explore advanced topics like conditional and chained callbacks, cross-filtering and real-time automation
Requirements
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
Description
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 data analysis and visualization tools, 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 for data analysis and visualization, 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 dashboard 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 videoPython Plotly & Dash PDF ebook (180+ pages)Downloadable project files & solutionsExpert support and Q&A forum30-day Udemy satisfaction guaranteeIf you're a data analyst, data scientist 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)__________Looking for our full business intelligence stack? Search for "Maven Analytics" to browse our full course library, including Excel, Power BI, MySQL, Tableau and Machine Learning courses!See why our courses are among the TOP-RATED on Udemy:"Some of the BEST courses I've ever taken. I've studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I've seen!" Russ C."This is my fourth course from Maven Analytics and my fourth 5-star review, so I'm running out of things to say. I wish Maven was in my life earlier!" Tatsiana M."Maven Analytics should become the new standard for all courses taught on Udemy!" Jonah M.
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
Data 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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