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

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.

What's inside

Learning objectives

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.

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.

Syllabus

Welcome

Find more content in our social media:

Website: https://evlabs.io

Youtube channel: https://www.youtube.com/channel/UCksRNSzWuMV5IfdrPlglqqw

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Twitter: https://twitter.com/evelabs

Link to our programming environment (Google colab):

https://colab.research.google.com/github/escape-velocity-labs/data-visualization/blob/main/data_visualization.ipynb

Data Science and Machine Learning series

Our complete course catalog

Matplotlib

Learn the basics of NumPy (free):

https://www.evlabs.io/p/complete-numpy-course-with-applications

Line Plot

Our first graph

Anatomy of a figure in matplotlib

The Figure and Axes classes

Pyplot

Object-oriented interface

Add annotations to the graph

Draw shapes on the graph

Draw lines on the graph

Manipulate the axes of the graph

Data exploration with matplotlib: Iris dataset

Dataset presentation

Loading the dataset

Pie chart

How many records of each class do we have?

Modifying the style of the chart

Scatter plot

Can we differentiate the species by their petals?

3D Plots

Does it help to know the length of the sepal?

Box Plot

What is the range of values for each feature?

Violin Plot

Feature value distribution

Bar chart

Multiple graphs

Do different species have different features?

Global styles

Image manipulation with matplotlib

Using images in matplotlib

Grayscale vs RGB

Color maps

Creating complex graph structures

Creating color histograms for an image

Increasing image resolution

Saving images or graphs to a local file

Seaborn

Introduction to Seaborn

Figure level and axes level graphs

Pandas DataFrames

Modifying the style of the graphs

Data exploration with Seaborn: Titanic dataset

Data presentation

Density plots

Who was on the Titanic? - Part 1

Who was on the Titanic? - Part 2

How much did the guests pay?

Does paying more improve the odds of surviving?

Where did the guests stay?

What are the odds of surviving?

Data exploration with Seaborn: Penguin species

Presentation and loading of the dataset

The PairGrid class

How can we differentiate between penguin species?

The JointPlot class and marginal plots

Identifying penguins with joint plots

Data exploration with Seaborn: monthly number of flights

Long vs wide data format

Evolution of the number of flights

Plotly

Introduction to Plotly

Plotly express

Data exploration with Plotly: Wind dataset

Polar charts

Which way is the wind blowing? With what intensity?

Data exploration with Plotly: FMRI

How does the brain react to certain events?

Data exploration with Plotly: stocks

How have the stock prices evolved?

Data exploration with Plotly: price of diamonds

Dataset loading and presentation

How many diamonds do we have (by color, cut and clarity)?

What are the most common features of diamonds?

How does cut, color and clarity affect the price?

Which continuous variables affect the price?

Explore the relationship between carats, cut, clarity and price

Data exploration with Plotly: carshare activity in Montreal

Working with maps in Plotly

Carshare activity in Montreal

Data exploration with Plotly: car accidents in the US

Choropleths

Car accidents in the US by state

Dash

Introduction to Dash

Elements of a Dash application

Results presentation: World Bank data

Creating the dash application

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops Python skills that are valuable for both beginner and intermediate-level data scientists

Covers all the main Python data visualization libraries: matplotlib, seaborn, plotly, and dash

Offers hands-on experience with real-world datasets

Teaches visual presentation skills for non-technical audiences

Provides access to a collaborative workspace in Google Colab

Assumes basic knowledge of Python and NumPy

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) with these activities:

Data Visualization Handbook

Show steps

Expand your theoretical understanding of data visualization principles and best practices by reviewing this comprehensive reference book.

View Storytelling with Data: A Data Visualization... on Amazon

Show steps

Read chapters on topics relevant to your current or upcoming lessons.
Take notes or highlight key concepts and examples.

Review Basic Python Concepts

Show steps

Reinforce your understanding of programming basics with Python, setting a strong foundation for this course's data visualization techniques.

Browse courses on Python

Show steps

Revisit basic data types, variables, and operators.
Practice writing simple programs using loops and conditional statements.
Explore Python libraries for data manipulation, such as NumPy and Pandas.

Introduction to Matplotlib

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Delve deeper into Matplotlib's capabilities through guided tutorials, gaining hands-on experience with its plotting functionalities.

Browse courses on Data Visualization Tools

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Follow online tutorials to create basic plots, such as line charts and scatterplots.
Explore advanced features like subplots, annotations, and colormaps.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Visualization Challenges

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Sharpen your data visualization skills by solving coding challenges and exercises that focus on specific aspects of the course material.

Show steps

Find online platforms or repositories that offer visualization challenges.
Choose challenges that align with the techniques covered in class.
Implement solutions using Python and the appropriate visualization libraries.

Collaborative Visualization Project

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Foster collaboration and exchange of ideas by working on a data visualization project with peers, enhancing your communication and teamwork skills.

Browse courses on Group Projects

Show steps

Form a group of 2-3 classmates.
Choose a dataset and topic for your visualization project.
Assign roles and responsibilities within the group.
Meet regularly to discuss progress and provide feedback.
Present your final visualization and insights to the class.

Visualize Data for a Specific Domain

Show steps

Apply your data visualization skills to a specific domain of interest, creating visualizations that solve real-world problems.

Browse courses on Case Studies

Show steps

Identify a domain you're interested in, such as healthcare, finance, or marketing.
Gather data relevant to your chosen domain.
Use Python and visualization libraries to create data visualizations.
Share your visualizations and insights on a platform like GitHub or Medium.

Contribute to Plotly's Open-Source Repository

Show steps

Gain practical experience and deepen your understanding of Plotly by contributing to its open-source repository, enhancing the tool for others.

Browse courses on Plotly

Show steps

Review Plotly's documentation and tutorials.
Identify an area where you can contribute, such as bug fixes or feature enhancements.
Create a pull request on GitHub.
Collaborate with Plotly's developers to refine and merge your contribution.

Career center

Learners who complete Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use their deep understanding of data and statistics to extract meaningful insights from complex datasets. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) will provide you with the skills to visualize and analyze data effectively, which is a critical aspect of the data science workflow. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and make informed decisions.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) will provide you with the skills to transform raw data into visually appealing and informative visualizations. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts use data to understand business needs and identify opportunities for improvement. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) will provide you with the skills to create data visualizations that can communicate complex business concepts in a clear and concise way. By learning how to create clear and concise data visualizations, you can help stakeholders make informed decisions and improve business outcomes.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, and interpret data to provide insights and make predictions. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) will provide you with the skills to visualize and analyze data effectively, which is a critical aspect of the statistical workflow. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions.

See salaries and explore the career path for Statistician

Software Engineer

Software Engineers design, develop, and maintain software systems. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Software Engineers who want to learn how to visualize and analyze data in their software applications. By learning how to create clear and concise data visualizations, you can improve the user experience and make your software applications more valuable.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers build and maintain the infrastructure that stores and processes data. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Data Engineers who want to learn how to visualize and analyze data to improve the performance of their data pipelines. By learning how to create clear and concise data visualizations, you can identify bottlenecks and optimize your data pipelines.

See salaries and explore the career path for Data Engineer

Web Developer

Web Developers design and develop websites and web applications. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Web Developers who want to learn how to visualize and analyze data on their websites and web applications. By learning how to create clear and concise data visualizations, you can improve the user experience and make your websites and web applications more valuable.

See salaries and explore the career path for Web Developer

Product Manager

Product Managers lead the development and launch of new products and features. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Product Managers who want to learn how to visualize and analyze data to understand customer needs and improve product development. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions about product development.

See salaries and explore the career path for Product Manager

UX Designer

UX Designers create user interfaces that are both aesthetically pleasing and easy to use. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for UX Designers who want to learn how to visualize and analyze data to understand user behavior and improve the user experience. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions about product development.

See salaries and explore the career path for UX Designer

Marketing Analyst

Marketing Analysts analyze data to understand marketing campaigns and identify opportunities for improvement. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Marketing Analysts who want to learn how to visualize and analyze data to track the performance of marketing campaigns and identify areas for improvement. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions about marketing strategy.

See salaries and explore the career path for Marketing Analyst

Financial Analyst

Financial Analysts evaluate the financial performance of companies and make recommendations for investment. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Financial Analysts who want to learn how to visualize and analyze data to understand financial trends and make informed investment decisions. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions about investment strategy.

See salaries and explore the career path for Financial Analyst

Risk Analyst

Risk Analysts identify and assess risks to businesses and organizations. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Risk Analysts who want to learn how to visualize and analyze data to identify and assess risks. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions about risk management.

See salaries and explore the career path for Risk Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve business problems. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Operations Research Analysts who want to learn how to visualize and analyze data to solve business problems. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions.

See salaries and explore the career path for Operations Research Analyst

Management Consultant

Management Consultants advise businesses and organizations on how to improve their performance. This course in Data Visualization in Python (Mplib, Seaborn, Plotly, Dash) may be useful for Management Consultants who want to learn how to visualize and analyze data to identify areas for improvement. By learning how to create clear and concise data visualizations, you can communicate your findings to stakeholders and help them make informed decisions about business strategy.

See salaries and explore the career path for Management Consultant