Udemy

Data Visualization in Python (Mplib, Seaborn, Plotly, Dash)

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  • 681 Students
  • Updated 5/2025
4.6
(67 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
6 Hour(s) 51 Minute(s)
Language
English
Taught by
Escape Velocity Labs
Rating
4.6
(67 Ratings)
2 views

Course Overview

Data Visualization in Python (Mplib, Seaborn, Plotly, Dash)

Master data visualization in Python with the matplotlib, seaborn, plotly and dash libraries.

Learn how to synthesize complex data sets easily in a visual way. In this course, you will develop this basic data science skill (data visualization) by exploring real data sets with the most popular Python tools (matplotlib, seaborn, plotly, and dash). You will learn how to extract the most relevant information from data and present it with a variety of graphs and charts to non-technical people.


Learn how to extract visual knowledge from complex data for decision-making with Python.


- Master the main visualization libraries in Python for Data Science.

- Discover and extract the most important knowledge from complex data.

- Learn to build web interfaces with charts to present important results to a wider audience.


Master a basic data science skill.


In the course, you will explore 8 different datasets. You will learn to understand their content and answer questions by building a variety of graphs, basic and advanced. This is a basic data science skill as data science professionals analyze and model data to assist decision-making and solve complex problems. Data visualization is a fundamental part of this process, guiding the data scientist's analysis and presenting the results in a way that people with diverse profiles can understand.

For the presentation of results, we will create a web interface with the plotly library that will show in real-time the most relevant information of a web page: visits, user types, session duration, purchases, etc.

At the end of the course, you will master all these tools fluently and will be able to visually analyze your own datasets and extract the most relevant information from them.

Course Content

  • 10 section(s)
  • 111 lecture(s)
  • Section 1 Welcome
  • Section 2 Matplotlib
  • Section 3 Data exploration with matplotlib: Iris dataset
  • Section 4 Image manipulation with matplotlib
  • Section 5 Seaborn
  • Section 6 Data exploration with Seaborn: Titanic dataset
  • Section 7 Data exploration with Seaborn: Penguin species
  • Section 8 Data exploration with Seaborn: monthly number of flights
  • Section 9 Plotly
  • Section 10 Data exploration with Plotly: Wind dataset

What You’ll Learn

  • Explore data sets visually in Python.
  • Create web interfaces to visually present results.
  • Master the most important Python data visualization libraries (matplotlib, seaborn, plotly and dash).
  • Synthesize data sets for presentation to non-technical audiences.

Reviews

  • R
    Robert Benson
    5.0

    excellent description of the data.

  • A
    Alton V. Kesselly
    5.0

    It is a very wonderful course. The style of teaching is great. The lecturer has an amazing ability to make hard topics easy to understand.👍

  • A
    Abdelghafour Halimi
    1.0

    I'm disappointed. We don't have access to the necessary materials. The only resource provided is an empty Jupyter notebook. Please be aware.

  • L
    Lars Tuff
    5.0

    Very good, keep it up.

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