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Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender a visualizar los datos con Python y la librería de Seaborn. Seaborn es una de las herramientas de visualización de datos más populares de Python y en este curso se aprenderá de forma práctica a utilizarla.
Crearas múltiples tipos de gráficas, desde gráficos de líneas hasta heatmaps de correlación, y aprenderás a cuando utilizar cada tipo de gráfico
Register for this course and see more details by visiting:
OpenCourser.com/course/iije1l/visualizacion
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches Seaborn, which is one of the most popular Python data visualization libraries
Explores multiple data visualization types, including line graphs and heatmaps
Provides hands-on practice in data visualization with Python and Seaborn
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Save Visualización de datos con Seaborn to your list so you can find it easily later:
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Reviews summary
Practical seaborn course
This is a practical course that teaches you how to visualize your data using Python and Seaborn, one of the most popular data visualistion libraries in Python. You will learn by creating many different kinds of charts and graphs and when to use each of them.
Learn graphs you'll use in the real world.
"Crearas múltiples tipos de gráficas..."
Learn by doing.
"This project is a course práctico y efectivo..."
Lacks in-depth theory on visualizations.
"Not a lot of theory on visualizations done thought..."
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 Visualización de datos con Seaborn with these
activities:
Organize course materials
Show steps
Stay organized and engaged by compiling all relevant course materials in one place, ensuring easy access and efficient learning.
Show steps
-
Create a dedicated folder for course materials.
-
Download and save all course materials in the folder.
-
Review and organize the materials regularly.
Recall statistical concepts
Show steps
Refresh your understanding of statistical concepts to enhance your comprehension of data visualization techniques in this course.
Browse courses on
Statistics
Show steps
-
Review basic statistical concepts such as mean, median, and standard deviation.
-
Practice interpreting statistical graphs and charts.
Review Python basics
Show steps
Brush up on your Python skills to prepare for this course, ensuring a strong foundation for data visualization in Python.
Browse courses on
Python
Show steps
-
Review Python syntax and data structures.
-
Practice writing basic Python programs.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Read Python Data Science Handbook
Show steps
Learn the fundamentals of Python and data science to prepare for this course.
View
Python Data Science Handbook: Essential Tools...
on Amazon
Show steps
-
Acquire the book.
-
Read the first three chapters.
-
Summarize the main concepts covered in each chapter.
-
Complete the exercises at the end of each chapter.
Watch Seaborn video tutorials
Show steps
Supplement your understanding of Seaborn by watching video tutorials that demonstrate its features and functionalities.
Browse courses on
Seaborn
Show steps
-
Search for Seaborn video tutorials.
-
Watch the tutorials and take notes.
Join a Python study group
Show steps
Connect with other learners and discuss Python concepts and Seaborn techniques to enhance your understanding.
Browse courses on
Python
Show steps
-
Find a Python study group online or in your local area.
-
Attend the study group meetings regularly.
-
Participate in discussions and ask questions.
Complete Seaborn tutorial exercises
Show steps
Practice using the Seaborn library to create different types of data visualizations in Python.
Browse courses on
Seaborn
Show steps
-
Go to the Seaborn tutorial website.
-
Follow the tutorial and complete the exercises.
-
Experiment with different visualization types.
Visualize data from a real-world dataset
Show steps
Apply your Seaborn skills to a real-world dataset, gaining practical experience in data visualization.
Browse courses on
Seaborn
Show steps
-
Find a real-world dataset.
-
Clean and prepare the data for visualization.
-
Create visualizations using Seaborn to explore the data.
Create a data visualization dashboard
Show steps
Apply your Seaborn skills to create a data visualization dashboard that showcases your understanding of the library.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset to visualize.
-
Design the dashboard layout.
-
Create the visualizations using Seaborn.
-
Deploy the dashboard.
Organize course materials
Show steps
Stay organized and engaged by compiling all relevant course materials in one place, ensuring easy access and efficient learning.
Show steps
Show steps
Show steps
- Create a dedicated folder for course materials.
- Download and save all course materials in the folder.
- Review and organize the materials regularly.
Recall statistical concepts
Show steps
Refresh your understanding of statistical concepts to enhance your comprehension of data visualization techniques in this course.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review basic statistical concepts such as mean, median, and standard deviation.
- Practice interpreting statistical graphs and charts.
Review Python basics
Show steps
Brush up on your Python skills to prepare for this course, ensuring a strong foundation for data visualization in Python.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review Python syntax and data structures.
- Practice writing basic Python programs.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Read Python Data Science Handbook
Show steps
Learn the fundamentals of Python and data science to prepare for this course.
View
Python Data Science Handbook: Essential Tools...
on Amazon
Show steps
Show steps
Show steps
- Acquire the book.
- Read the first three chapters.
- Summarize the main concepts covered in each chapter.
- Complete the exercises at the end of each chapter.
Watch Seaborn video tutorials
Show steps
Supplement your understanding of Seaborn by watching video tutorials that demonstrate its features and functionalities.
Browse courses on
Seaborn
Show steps
Show steps
Show steps
- Search for Seaborn video tutorials.
- Watch the tutorials and take notes.
Join a Python study group
Show steps
Connect with other learners and discuss Python concepts and Seaborn techniques to enhance your understanding.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find a Python study group online or in your local area.
- Attend the study group meetings regularly.
- Participate in discussions and ask questions.
Complete Seaborn tutorial exercises
Show steps
Practice using the Seaborn library to create different types of data visualizations in Python.
Browse courses on
Seaborn
Show steps
Show steps
Show steps
- Go to the Seaborn tutorial website.
- Follow the tutorial and complete the exercises.
- Experiment with different visualization types.
Visualize data from a real-world dataset
Show steps
Apply your Seaborn skills to a real-world dataset, gaining practical experience in data visualization.
Browse courses on
Seaborn
Show steps
Show steps
Show steps
- Find a real-world dataset.
- Clean and prepare the data for visualization.
- Create visualizations using Seaborn to explore the data.
Create a data visualization dashboard
Show steps
Apply your Seaborn skills to create a data visualization dashboard that showcases your understanding of the library.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset to visualize.
- Design the dashboard layout.
- Create the visualizations using Seaborn.
- Deploy the dashboard.
Career center
Learners who complete Visualización de datos con Seaborn will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use data to solve business problems. This course in Visualizing Data with Seaborn can help build a foundation in data visualization, which is a key skill for Data Analysts. With a strong understanding of data visualization, Data Analysts can better communicate insights and trends to stakeholders, helping drive better decision-making.
Data Scientist
Data Scientist
Data Scientists use statistical and computational techniques to extract insights from data. This course in Visualizing Data with Seaborn can help build a foundation in data visualization, which is an essential skill for Data Scientists. With a strong understanding of data visualization, Data Scientists can more effectively communicate their findings and insights to stakeholders, enabling better decision-making.
Business Analyst
Business Analyst
Business Analysts use data to improve business processes. This course in Visualizing Data with Seaborn can help build a foundation in data visualization, which is a valuable skill for Business Analysts. With a strong understanding of data visualization, Business Analysts can more easily identify trends and patterns in data, leading to better recommendations for process improvement.
Statistician
Statistician
Statisticians use data to solve problems and make predictions. This course in Visualizing Data with Seaborn can help build a foundation in data visualization, which is an important skill for Statisticians. With a strong understanding of data visualization, Statisticians can more clearly present their findings and insights, helping inform decision-making.
Data Engineer
Data Engineer
Data Engineers design and build data systems. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to end-users.
Software Engineer
Software Engineer
Software Engineers design and develop software applications. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to end-users.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to end-users.
Sociologist
Sociologist
Sociologists study the behavior and organization of human societies. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to policymakers and other stakeholders.
Anthropologist
Anthropologist
Anthropologists study the behavior, origin, and development of humans. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to policymakers and other stakeholders.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to investors and other stakeholders.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to clients and other stakeholders.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and patterns of disease in populations. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to public health officials and other stakeholders.
Economist
Economist
Economists study the production, distribution, and consumption of goods and services. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to policymakers and other stakeholders.
Market Research Analyst
Market Research Analyst
Market Research Analysts collect and analyze data to understand consumer behavior. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to clients.
Demographer
Demographer
Demographers study the size, structure, and distribution of populations. This course in Visualizing Data with Seaborn may be useful in understanding how data is visualized and presented to policymakers and other stakeholders.
For more career information including salaries, visit:
OpenCourser.com/course/iije1l/visualizacion
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Visualización de datos con Seaborn.
Provides a comprehensive overview of the field of information visualization. It covers topics such as visual perception, design principles, and evaluation methods. It valuable resource for understanding the theoretical foundations of data visualization.
Save
Explores the art and science of data visualization. It provides insights into the history, principles, and best practices of data visualization, making it a valuable resource for understanding the broader context and significance of data visualization.
Save
This classic work on data visualization provides a timeless perspective on the principles of effective data visualization. While it does not cover Seaborn specifically, it offers valuable insights and guidance on how to design clear and informative visualizations.
Save
Provides a comprehensive guide to the art and science of data visualization. It covers topics such as data exploration, visual perception, and the use of color and typography. It valuable resource for understanding the broader context and significance of data visualization.
Provides a solid foundation in the fundamentals of data visualization. It covers topics such as visual perception, color theory, and the principles of effective data representation. It valuable resource for understanding the theoretical underpinnings of data visualization.
Save
Provides a collection of essays and case studies on data visualization. It covers topics such as storytelling with data, the use of color, and the impact of data visualization on decision-making. It offers valuable insights into the practical and ethical aspects of data visualization.
Save
Provides a comprehensive introduction to data visualization, covering the principles of effective data visualization and a wide range of visualization techniques. It valuable reference for learning about the fundamentals of data visualization and complements the course's focus on Seaborn.
Provides practical guidance on creating visually appealing and effective graphs and charts for publication. It covers topics such as choosing the right chart type, formatting, and best practices for presenting data visually.
While this book focuses on ggplot2, a data visualization library for R, it offers valuable insights into the principles of data visualization and the creation of effective graphics. It can serve as a complementary reference for understanding data visualization concepts.
Focuses on creating interactive data visualizations using web technologies. While it does not cover Seaborn, it provides a valuable perspective on the design and implementation of interactive visualizations, which can complement the course's focus on static visualizations.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/iije1l/visualizacion
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Leire Ahedo
Good to know
Teaches Seaborn, which is one of the most popular Python data visualization libraries
Explores multiple data visualization types, including line graphs and heatmaps
Provides hands-on practice in data visualization with Python and Seaborn
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