Learn Effective Data Visualization using Plotly Express



Learn Effective Data Visualization using Plotly Express — Udemy — Last updated 1/2021 — Free download


Create beautiful charts and animations using Plotly, Plotly Express and Python for Data analysis and Data science

What you’ll learn

  • Students would learn the different types of visualization charts which exist and when to use each.
  • Students would learn how to create visualization charts using plotly express and python.
  • Students would learn how to approach a data science question and respond with visualization.
  • Students would be able to create animations using Plotly Express.


  • Should be comfortable using a python IDE.
  • Student should be comfortable installing python libraries using the pip command.
  • Access to a computer with internet access and ability to download source code from GitHub.
  • In this course, Pycharm is used as the IDE, however, any IDE with support for Python can be used.

Learn Effective Data Visualization using Plotly Express

Data visualization is a very important yet understated skill required for everyday life and transition into data science and analytics in general.

This is the most comprehensive course on Data visualization using Plotly Express, in this course, you not only learn how to create visuals and how to write the code, but you would learn when to use what visualization method.

In this course, you learn how to create the following chart types using Plotly and Plotly express:

  • Scatterplots.
  • Lineplots.
  • Areaplots.
  • Histogram.
  • Boxplots.
  • Violinplots.
  • Pie charts.
  • Sunburst.
  • Treemaps.
  • Choropleth maps.
  • and much more…

Each section in this course covers a specific chart and is self contained (meaning you can take each section in isolation), there are tons of exercises and case studies to show when to use which visualization chart.

Some of the datasets which we would analyze visually are:

  1. All stocks 5 year price.
  2. Apple stock price 5 years.
  3. Auto MPG Dataset.
  4. Gapminder dataset.
  5. Iris flower dataset.
  6. Share of individuals using the internet dataset.
  7. Tips dataset.
  8. World Happiness ranking 2019.

By the end of the course, you would have mastered the art of data visualization.

Who this course is for:

  • Beginner Python developers curious about data visualization using Plotly express.
  • Python developers interested in Data Visualization.
  • Anybody interested in learning to create interactive visualizations


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