Python Interactive Dashboards with Plotly Dash

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Course overview

Provider
Udemy
Course type
Paid course
Level
Intermediate
Duration
5 hours
Lessons
31 lessons
Certificate
Available on completion
Course author
Lianne and Justin (Just into Data)
  • How to set up the layout of dashboards with Dash components
  • How to create a dashboard with data visualizations
  • How to make the dashboards interactive
  • How to customize the appearance of the dashboard
  • Create a dashboard using real-world datasets
  • Make more dynamic dashboards with chained interactive features
  • Add buttons to dashboards
  • Create interactive graphs that are clickable
  • Create data tables in dashboards
  • Create a grid layout in dashboards
  • Create a dashboard with a navigation bar and cards
  • Use Plotly to create plots including line charts, choropleth maps
  • Basics of Python with a crash course

Description

Learn to create interactive Python dashboards (data visualizations) using plotly Dash, with real-world example datasets

Welcome to your plotly Dash course!

So you've got some hard analysis done, how can you nicely present them too?

Dash and Plotly in Python can help! They empower you to visualize your critical insights and KPIs in web apps that are easily sharable.

Following this course, you'll learn to build dashboards from scratch, by customizing their look and adding interactive features, with all free Python libraries.

Throughout the course, you'll be using three real-world datasets to create dashboards. They will make your learning experience more practical. So that you can easily apply the skills to build your own dashboards after taking this course.

Data visualization is critical for data science. Don't miss the opportunity to learn this new skill of creating dashboards with Python! This course includes instructional videos that walk you through the process step-by-step. You can learn at your own pace, and download the Python scripts to use for your own projects.

Besides Dash, you'll also get a chance to use other key data science libraries, including pandas and plotly. It's ok if you haven't used them before. We'll break down and explain the process within the course. So that you can still follow along!

Cheers,

Lianne and Justin


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