Data Visualisation with Plotly and Python

Level up your data visualisation. Learn to create interactive charts and dashboards with Python and Plotly.

4.30 (320 reviews)
Udemy
platform
English
language
Programming Languages
category
instructor
3,378
students
23 hours
content
Jul 2020
last update
$69.99
regular price

What you will learn

At the end of this course you'll be able to use Plotly to make interactive line plots, area plots and scatterplots.

You'll know how to make stacked and grouped bar charts, pie charts, donut charts and tables.

You'll also be able to bring together several different charts into a dashboard.

You'll have a working knowledge of the Python programming language, as well as an intermediate knowledge of the Pandas data analysis library.

Description

Looking to level up your data visualisation skills? Bored of dull, static charts and graphs? This course will teach you to how to use Python to create awesome, interactive data visualisations with the Plotly library. 

What's involved?

You get immediate access to twelve painstakingly crafted and researched chapters, each designed to level up your data visualisation and coding skills. Using my experience as a data visualisation specialist and teacher, I've created original content that uses real-world data to teach you the fundamentals of data visualisation in a clear and easy-to-understand way. 

You'll find this course interesting, fun and engaging. The lessons are paced to build confidence in the skills you're learning, and there are plenty of quizzes and practise activities to solidify your knowledge.


Here's what you get with Data Visualisation with Plotly 3 and Python

  • Access to twelve chapters which take you through each topic, providing plenty of chances to practise.

  • Over 140 Lectures, 27 hours of video content, 40 practise datasets and 11 quizzes

  • Step by step instruction to set up your coding environment and install the required software

  • The course starts with the basics; the first section will give you a basic understanding of the Python coding language. and you'll soon be making some interactive charts!

Over the twelve chapters you'll:

  • Use Plotly 3 to create:

    • Lineplots 

    • Areaplots

    • Scatterplots

    • Bubbleplots

    • Stacked bar charts

    • Grouped bar charts

    • Pie charts

    • Tables

    • Dashboards

  • Bring together everything you've learnt to create three awesome dashboards which showcase your work.

  • Learn how to use colour, interaction and design principles to make your charts really stand out.

  • Build a portfolio of charts that you can use to show off your data visualisation skills.

  • Develop your knowledge of Python and become a confident user of Pandas; the go-to data analysis tool for Python coders.

  • Please note that this course does not cover Plotly 4.0

What else will you get?

  • Lifetime access to the course materials


So what are you waiting for? Level up your data visualisation skills, transform your career and sign up now!




Content

Setting up your programming environment

Installing Anaconda, Jupyter & Plotly
Introduction to Jupyter Notebooks
Downloading the course materials
Setting up a Plotly account and configuring your Plotly installation

Introduction to Python

Download materials for Introduction to Python
Variables in Python
Variable Types - Numbers
Variable Types - Strings (1)
Variable Types - Strings (2)
Variable Types - Boolean
Variable Types - Lists (1)
Variable Types - Lists (2)
Variable Types - Dictionaries (1)
Variable Types - Dictionaries (2)
If-Else Statements
For Loops (1) - Looping through a range of values
For Loops (2) - Looping through the items in a sequence
For Loops (3) - Nested Loops
Functions (1) - Creating Functions
Functions (2) - Using Functions
Importing Modules
Introduction to Pandas (1) - Reading data into a DataFrame
Introduction to Pandas (2) - Useful DataFrame Functions
Introduction to Pandas (3) - Accessing and Creating Columns
Introduction to Pandas (4) - Changing the DataFrame
Introduction to Pandas (5) - Accessing and changing specific observations
Variables Types in Python
Conditional programming in Python
Working with the Pandas library
Further resources for learning Python

Lineplots and Area Plots

Download materials for Lineplots
Introduction to Lineplots in Plotly
Plotting different data
Plotting data from a Pandas DataFrame
Plotting multiple lines
Plotting multiple lines with a For loop
Changing line colour and thickness
Making dashed and dotted lines
Adding and changing marker symbols
Applying smoothing (1)
Applying smoothing (2) - stock market data
Stepwise line shapes
Creating an area plot
Creating a stacked area plot
Creating a stacked proportional area plot
Writing a function to create a stacked proportional area plot
Review of lineplots and areaplots
Practise datasets for lineplots and area plots

Styling your charts

Download materials for section Styling your charts
Changing the range
Setting the tick format
Modifying the tick labels
Creating and positioning custom tick values
Controlling hovertext on your chart
Creating custom hovertext
Applying custom hovertext
Practise (1)
Practise (2)
Styling your charts - review
Practising your chart presentation skills

Scatterplots

Download materials for Scatterplots
Scatterplots 1 - What is a scatterplot?
Scatterplots 2 - Making our first scatterplot
Scatterplots 3 - Styling the marker points
Scatterplots 4 - Plotting different categories on the same plot
Scatterplots 5 - Controlling traces and legend items
Scatterplots 6 - Fitting a regression line
Scatterplots 7 - Plotting and styling regression lines
Scatterplots 8 - Adding text to charts
Scatterplots 9 - Making bubbleplots
Scatterplots 10 - Recreating the Gapminder plot
Scatterplots 11 - Plotting multiple plots together
Scatterplots 12 - Making a scatterplot matrix
Scatterplots 13 - Styling our scatterplot matrix
Scatterplots 14 - Writing a function for a scatterplot matrix
Practise datasets for scatterplots and bubbleplots
Scatterplots - Review

Styling your charts (2)

Download materials for Styling your Charts 2
Styling the global font
Styling annotations, text, ticklabels and titles
Further styling of annotations
Positioning annotations outside of the chart
Changing the margins
Adding a source annotation
Different subplots options
Combining subplots grid spaces
Styling your charts - review
Practising your chart presentation skills

Bar Charts

Download materials for Bar Charts section
What is a bar chart?
Making our first bar chart
Styling options for a bar chart
Styling individual bars
Horizontal barcharts
Plotting multiple bar traces
Creating stacked bar charts
Stacked proportional bar charts
Plotting bar and line plots together
Barcharts - review
Practise datasets for bar charts

Making our first dashboard

Creating our first dashboard (1)
Creating out first dashboard (2)
Styling our first dashboard

Styling your charts (3)

Download materials for Styling your Charts 3
Styling the legend
Changing the position of traces in the legend
Positioning the legend
Horizontal legends
Changing the background colour of a chart
Styling your charts - review
Practise your chart presentation skills

Pie charts

Download materials for Pie Charts
What is a pie chart?
Making our first pie chart
Styling a pie chart
Highlighting specific segments of a pie chart
Labels, text and hoverinfo
Text inside and outside the segments
Using pie charts in a subplots object
Sizing pie charts relative to each other
Making a donut chart
Pie charts - review
Practise datasets for pie charts and donut charts

Tables

Download materials for Tables section
Why use tables for data visualisation?
Making our first table
Adding an index column
Changing the colours in a table
Styling text in a table
Changing the row height
Adding hoverinfo
Combining tables and charts
Tables - review
Practise datasets for tables

Dashboards

Download materials for Dashboards section
UK Demographics Dashboard (1)
UK Demographics Dashboard 2
UK Demographics Dashboard 3
Crime in London Dashboard 1
Crime in London Dashboard 2
Crime in London Dashboard 3
Crime in London Dashboard 4
Crime in London Dashboard 5
Crime in London Dashboard 6
Football Hooligans Dashboard 1
Football Hooligans Dashboard 2
Football Hooligans Dashboard 3
Football Hooligans Dashboard 4
Football Hooligans Dashboard 5
Football Hooligans Dashboard 6
Football Hooligans dashboard 7
Football Hooligans Dashboard 8
Football Hooligans Dashboard 9
Practise creating a dashboard with these datasets

Screenshots

Data Visualisation with Plotly and Python - Screenshot_01Data Visualisation with Plotly and Python - Screenshot_02Data Visualisation with Plotly and Python - Screenshot_03Data Visualisation with Plotly and Python - Screenshot_04

Reviews

David
August 2, 2023
This course is actually really good. I want to give it 5 stars, but I can't because sadly, a certain portion of its code in the notebooks is outdated. Now granted, most of this outdated code provides no problems (only a warning that some part of it is deprecated) or only requires only a little modification (e.g. changing the `import plotly.plotly as py` to `import chart_studio.plotly as py`). But then some of the outdated code does not work at all, and requires certain degree of overhaul to get to work (e.g. realizing that you cannot directly add a trace to fig['data'], you need to use the new function .add_trace, or finding out the yahoo API has changed and some information cannot be retrieved as a result). Now granted, I know that this course is about 6 years old at the time of writing, and there is probably little to no incentive for Richard Muir to update this course since the vast majority of the ideas and code are still pertinent to plotly to this day. However, it does make for a somewhat stilted learning experience to try and get a certain Jupyter block to work. That being said, one can still learn quite a lot from this course. As previously mentioned, the vast majority of this code still works, and even when it doesn't, it does not often take too much work to get it rolling again. Richard does a good job delineating ideas and the notebooks often contain helpful notes. I definitely would recommend this course, with the caveat that some of the older code can be a bit troublesome.
Josh
July 7, 2023
The material here is a good start, but is now a bit outdated. There are quite a few lectures where students have requested updated content in the Q&A, but have yet to be answered. Some of these issues can be fixed with a quick search online; others not so much!
Francisco
April 11, 2021
For the moment the course is okay, but I find it kind of annoying that the author(s) didn't make an actualisation about the new Plotly. I just concluded section 1 and send a lot of time searching in Plotly site (which is not the same as in the videos) to manage to progress. hope the next sections don't need all that searching. I mean, you learn by searching, but sometimes can get frustrating.
Jason
January 8, 2021
This course is out of date. I have had to comment out of anything related to the old business structure of Plotly. For example, plotly.plotly doesn't exist anymore, there is no mention of dash, and plotly.graph_objects.graph is deprecated. I have only made it to the first lecture of the Plotly portion of the class, and I am already needing to do a lot of research on the back end to make sure everything I am doing is up to date. Honestly, I would kind of like my money back because what is being advertised is not even close to what is being offered. The only reason I am giving this two stars, and not directly asking for my money back is: I am genuinely interested in learning data science, and find it a fun challenge to teach myself the right way after getting error code after error code because the instruction is out of date. However, I feel there may be a more effective way to learn what is being offered. I don't know... I am re-writing my five star review to a two star review. Richard is a pleasure to follow, and taught the first half, intro to Python and Pandas, wonderfully. I would really like to see an updated version of the course. I would love to buy other classes offered by Richard, but I haven't found any. Please make more instructional videos!!!
Olabode
November 21, 2017
The content is just as he promised, it goes really indepth into how to use plotly in an orderly fashion. I am however looking forward to dedicated class exercises to aid the learning.
Nouro
November 17, 2017
too fast, not too much explanation when writing a line of code ... I have to back and forward between resources and video
Peter
August 30, 2017
This course is very practice oriented. I can recommend it to Python beginners and for advanced programmers. The instructor knows exactly, what he teaches and is well prepared. He saves time by copying and pasting instructions into the window. Therefore the student does not loose time. Every minute is worth to follow.
Jacob
August 28, 2017
Outstanding visualization skills imparted; but I particularly enjoyed your extremely pythonic syntax application, and the occasional police siren in the background!
Paul
August 10, 2017
Thank you for the great course! I've been using Plotly for a while now and have made some amazing charts but your course was very helpful for me since their documentation is a bit sparse at times. If I might, it would be helpful if you could also create a section on creating maps with Plotly.
Ram
August 2, 2017
Great video tutorials on the visualization using Python and plotly .This is the best course for Data Visualization i have seen in udemy.I am going to give it 5 Start Rating. Instructor has given inDepth understanding on the visualization .I am sure any body going to take his course will from day one will become master on the data visualization using python . Thanks Mori for your Great Tutorials.
Eddy
June 30, 2017
A fantastic course and the best resource I've seen online for learning the features of Plotly with Python. I'm not done with the course yet, but so far I think that Richard Muir delivers all that you'll need to make some fantastic charts! My only wish would have been to cover choropleth maps, or for the quizzes to be just a tad bit harder, but I wouldn't let that hold anyone back from taking the course. I'm hoping to see more from the author and think that he should consider making a data analysis course - I would purchase that in a heartbeat.
Hannah
June 23, 2017
I like that the tutorials are short and instructions are clear and concise - but I can't see how to get to the chart documentation discussed - not sure if this will be important - but could be getting a little lost...
Jose
June 13, 2017
Great course for learning data visualizations using Python and Plotly. Instructor goes over the Python programming skills that you need to learn, and explains things thoroughly. Thanks!
Andrei
June 5, 2017
The tuition is brilliant. It is being taught in details, i would highly recommend this course to everyone who is dealing with charting on a daily basis. The course is an example (benchmark) of the professional work.
James
May 29, 2017
I am really excited about this class. I know Python pretty well, but I can tell that Richard really knows his stuff, so I am watching these introductory videos. Plotly is amazing! Can't wait.

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863512
udemy ID
5/30/2016
course created date
11/24/2019
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