Analytics dashboard using python and plotly

Analytics dashboard using python and plotly, available at $59.99, has an average rating of 4.75, with 20 lectures, based on 15 reviews, and has 85 subscribers.

You will learn about Create test data using pandas and numpy Create comprehensive visuals using plotly Create a dashboard layout using dash Add additional functionality to the dashboard using dash callbacks Deploy the dashboard on Heroku This course is ideal for individuals who are This course is targeted towards people who are interested in visualisation and want to create a visually appealing dashboard that showcases data. This course is additionally intended for data analysts that want to expand the visual aspects of their analytics. It is particularly useful for This course is targeted towards people who are interested in visualisation and want to create a visually appealing dashboard that showcases data. This course is additionally intended for data analysts that want to expand the visual aspects of their analytics.

Enroll now: Analytics dashboard using python and plotly

Summary

Title: Analytics dashboard using python and plotly

Price: $59.99

Average Rating: 4.75

Number of Lectures: 20

Number of Published Lectures: 20

Number of Curriculum Items: 20

Number of Published Curriculum Objects: 20

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Create test data using pandas and numpy
Create comprehensive visuals using plotly
Create a dashboard layout using dash
Add additional functionality to the dashboard using dash callbacks
Deploy the dashboard on Heroku

Who Should Attend

This course is targeted towards people who are interested in visualisation and want to create a visually appealing dashboard that showcases data. This course is additionally intended for data analysts that want to expand the visual aspects of their analytics.

Target Audiences

This course is targeted towards people who are interested in visualisation and want to create a visually appealing dashboard that showcases data. This course is additionally intended for data analysts that want to expand the visual aspects of their analytics.

In this course you will learn to create various visuals and construct an aesthetic dashboard to showcase the visuals. Towards the end of the course you will learn how to add additional functionality to the dashboard and finally deploy the dashboard for production capabilities.

You will learn to create various types of charts using the library plotly, and how to style and update them. The added functionality will be created using advanced and basic callbacks. For instance if you want to display data for multiple years, this course will show you how to add a slider that will update the data based on the value of the input. You will also be introduced to a brief use of pandas and numpy, which are two libraries used for manipulating and performing calculations on data. All the code and the instructions for deployment will be added a resource at the end of the course. As a final note, this course will use a sales analytics dashboard as an example to walkthrough the various components.

This course is targeted towards anyone who is interested in data analytics, data visualisation, python in general, and for those who are just curious to learn something new. The level of python needed for this course is beginner/intermediate. If you don’t have any experience with python you are definitely welcome to follow along, however I recommend that you should take a beginners python course before taking this course.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Layout design

Lecture 1: Layout Design and App Layout

Lecture 2: App Layout in Dash

Chapter 3: Creating Test Data and Visuals

Lecture 1: Creating Test Data

Lecture 2: Quick Error Fix

Lecture 3: Creating the Visuals using Plotly Part 1

Lecture 4: Creating the Visuals using Plotly Part 2

Chapter 4: Adding the Visuals to the App Layout

Lecture 1: Adding the Visuals to the App Layout

Chapter 5: Basic Callbacks

Lecture 1: Create Callback Data

Lecture 2: Adding a Slider

Lecture 3: Multiple Output Callback

Lecture 4: Multiple Input Callback

Lecture 5: Chained Callback

Chapter 6: Advanced Callbacks

Lecture 1: Catching Error with PreventUpdate

Lecture 2: Displaying Error with dash.no_update

Lecture 3: Determining which Input has fired using dash.callback_context

Lecture 4: Improving Performance using Memoization

Chapter 7: Creating a Multi Page App

Lecture 1: Create a Multi Page Dashboard

Chapter 8: Deploying the App on Heroku

Lecture 1: Deploying the Dashboard

Chapter 9: Conclusion

Lecture 1: Conclusion

Instructors

Andreas Miller
Instructor at Udemy

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 1 votes
4 stars: 3 votes
5 stars: 11 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu