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Este proyecto es un curso práctico y efectivo para aprender a visualizar los datos en Python. Para ello utilizarás librerías de visualización como Seaborn, Altair, Bokeh, Matplotlib, etc. Crearas múltiples tipos de gráficas, desde gráficos de líneas hasta...
Read more
Este proyecto es un curso práctico y efectivo para aprender a visualizar los datos en Python. Para ello utilizarás librerías de visualización como Seaborn, Altair, Bokeh, Matplotlib, etc. Crearas múltiples tipos de gráficas, desde gráficos de líneas hasta...
Read more
Este proyecto es un curso práctico y efectivo para aprender a visualizar los datos en Python. Para ello utilizarás librerías de visualización como Seaborn, Altair, Bokeh, Matplotlib, etc. Crearas múltiples tipos de gráficas, desde gráficos de líneas hasta heatmaps de correlación, y aprenderás a cuando utilizar cada tipo de gráfico
Gracias a ello, aprenderás las librerías más populares de visualización de datos y podrás crear tus propios proyectos de visualización.
Register for this course and see more details by visiting:
OpenCourser.com/course/vinl50/visualizacion
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Reviews summary
Comprehensive python data visualization
This hands-on course in Python data visualization provides a comprehensive overview of visualization libraries like Seaborn, Altair, Bokeh, and Matplotlib. You'll learn how to choose the right type of graph for your data and create compelling visualizations. The course also provides additional resources and references to help you continue learning after the course ends. Note that practice and independent research are highly recommended to get the most out of this course.
Offers extra materials
"...proporciona recursos adicionales y referencias..."
Covers many libraries
"...ofrece una excelente introducción a varias bibliotecas de Python..."
Provides guidance on graph selection
"...no solo un conocimiento práctico de estas herramientas sino también orientación sobre qué tipo de gráfico es más adecuado..."
Requires additional effort
"...asumiendo que practiques bastante, después del curso y que investigues por tu propia cuenta."
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 Avanzada de datos con Python with these
activities:
Review Seaborn and Altair fundamentals
Show steps
Reviewing the basics of Seaborn and Altair will provide a solid foundation for the upcoming lessons on visualization techniques.
Browse courses on
Seaborn
Show steps
-
Read through the Seaborn and Altair documentation
-
Follow along with introductory tutorials
-
Experiment with simple data visualizations
Start a Python Visualization project
Show steps
Build a personal project to showcase your Python Visualization skills and deepen your understanding of the concepts covered in the course.
Show steps
-
Identify a dataset
-
Explore the dataset and identify key insights
-
Choose appropriate visualization tools
-
Create visualizations
-
Evaluate and iterate on your visualizations
Practice visualizing different types of data
Show steps
Reinforce your understanding of Python Visualization libraries by practicing with various data types and visualization techniques.
Show steps
-
Load a dataset into Python
-
Create different types of visualizations (e.g., line charts, bar charts, scatter plots)
-
Experiment with different libraries (e.g., Matplotlib, Seaborn, Altair)
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create various types of visualizations
Show steps
Practicing the creation of various types of visualizations will enhance your understanding of their strengths and weaknesses.
Browse courses on
Line Charts
Show steps
-
Plot different types of data using line charts, bar charts, and scatter plots
-
Create heatmaps to visualize correlations within datasets
-
Experiment with different customization options
Follow tutorials on advanced Python Visualization techniques
Show steps
Expand your skills by exploring advanced Python Visualization techniques through guided tutorials.
Show steps
-
Find tutorials on specific visualization techniques (e.g., interactive visualizations, geographic visualizations)
-
Follow the tutorials and implement the techniques
-
Apply the techniques to your own projects
Write a blog post or article on Python Visualization best practices
Show steps
Share your knowledge and insights by creating a blog post or article that provides practical guidance on effective Python Visualization.
Show steps
-
Identify common challenges in Python Visualization
-
Research and gather best practices
-
Write a clear and concise article
-
Share the article with the community
Create a visualization dashboard
Show steps
Synthesize your knowledge by creating a comprehensive dashboard that showcases your Python Visualization abilities.
Show steps
-
Gather data from multiple sources
-
Design a dashboard layout
-
Create visualizations and arrange them on the dashboard
-
Add interactive elements (optional)
Develop a data visualization dashboard
Show steps
Creating a data visualization dashboard will provide hands-on experience in combining different visualization techniques to communicate insights effectively.
Browse courses on
Dashboard Design
Show steps
-
Gather and prepare relevant data
-
Design the layout and structure of the dashboard
-
Incorporate interactive elements for user engagement
-
Present the dashboard and communicate insights
Review Seaborn and Altair fundamentals
Show steps
Reviewing the basics of Seaborn and Altair will provide a solid foundation for the upcoming lessons on visualization techniques.
Browse courses on
Seaborn
Show steps
Show steps
Show steps
- Read through the Seaborn and Altair documentation
- Follow along with introductory tutorials
- Experiment with simple data visualizations
Start a Python Visualization project
Show steps
Build a personal project to showcase your Python Visualization skills and deepen your understanding of the concepts covered in the course.
Show steps
Show steps
Show steps
- Identify a dataset
- Explore the dataset and identify key insights
- Choose appropriate visualization tools
- Create visualizations
- Evaluate and iterate on your visualizations
Practice visualizing different types of data
Show steps
Reinforce your understanding of Python Visualization libraries by practicing with various data types and visualization techniques.
Show steps
Show steps
Show steps
- Load a dataset into Python
- Create different types of visualizations (e.g., line charts, bar charts, scatter plots)
- Experiment with different libraries (e.g., Matplotlib, Seaborn, Altair)
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create various types of visualizations
Show steps
Practicing the creation of various types of visualizations will enhance your understanding of their strengths and weaknesses.
Browse courses on
Line Charts
Show steps
Show steps
Show steps
- Plot different types of data using line charts, bar charts, and scatter plots
- Create heatmaps to visualize correlations within datasets
- Experiment with different customization options
Follow tutorials on advanced Python Visualization techniques
Show steps
Expand your skills by exploring advanced Python Visualization techniques through guided tutorials.
Show steps
Show steps
Show steps
- Find tutorials on specific visualization techniques (e.g., interactive visualizations, geographic visualizations)
- Follow the tutorials and implement the techniques
- Apply the techniques to your own projects
Write a blog post or article on Python Visualization best practices
Show steps
Share your knowledge and insights by creating a blog post or article that provides practical guidance on effective Python Visualization.
Show steps
Show steps
Show steps
- Identify common challenges in Python Visualization
- Research and gather best practices
- Write a clear and concise article
- Share the article with the community
Create a visualization dashboard
Show steps
Synthesize your knowledge by creating a comprehensive dashboard that showcases your Python Visualization abilities.
Show steps
Show steps
Show steps
- Gather data from multiple sources
- Design a dashboard layout
- Create visualizations and arrange them on the dashboard
- Add interactive elements (optional)
Develop a data visualization dashboard
Show steps
Creating a data visualization dashboard will provide hands-on experience in combining different visualization techniques to communicate insights effectively.
Browse courses on
Dashboard Design
Show steps
Show steps
Show steps
- Gather and prepare relevant data
- Design the layout and structure of the dashboard
- Incorporate interactive elements for user engagement
- Present the dashboard and communicate insights
Career center
Learners who complete Visualización Avanzada de datos con Python will develop knowledge and skills
that may be useful to these careers:
Data Visualization Consultant
Data Visualization Consultant
Data Visualization Consultants help businesses improve their data visualization practices. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Data Visualization Consultants to succeed in their roles. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create and interpret data visualizations. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Data Visualization Specialists to succeed in their roles. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers design and develop data visualization solutions. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Data Visualization Engineers to succeed in their roles. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of businesses and organizations. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Operations Research Analysts to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Data Analysts to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Data Scientist
Data Scientist
Data Scientists use data to build models and solve problems. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Data Scientists to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Machine Learning Engineers to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Business Analyst
Business Analyst
Business Analysts help businesses improve their performance by analyzing data and making recommendations. They may work in a variety of industries, including finance, healthcare, and technology. This course provides a strong foundation in data visualization techniques, which are essential for Business Analysts to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data. They may work for investment banks, hedge funds, or other financial institutions. This course provides a strong foundation in data visualization techniques, which are essential for Quantitative Analysts to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Market Researcher
Market Researcher
Market Researchers collect and analyze data about markets and consumers. They may work for businesses, government agencies, or non-profit organizations. This course provides a strong foundation in data visualization techniques, which are essential for Market Researchers to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
User Experience Designer
User Experience Designer
User Experience Designers create products and services that are easy to use and understand. They may work in a variety of industries, including technology, healthcare, and finance. This course provides a strong foundation in data visualization techniques, which are essential for User Experience Designers to understand how users interact with data. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Information Architect
Information Architect
Information Architects design and organize information systems. They may work in a variety of industries, including technology, healthcare, and finance. This course provides a strong foundation in data visualization techniques, which are essential for Information Architects to understand how users interact with data. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Risk Analyst
Risk Analyst
Risk Analysts identify and manage risks. They may work for banks, insurance companies, or other financial institutions. This course provides a strong foundation in data visualization techniques, which are essential for Risk Analysts to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Product Manager
Product Manager
Product Managers develop and manage products. They may work in a variety of industries, including technology, healthcare, and finance. This course provides a strong foundation in data visualization techniques, which are essential for Product Managers to understand how users interact with their products. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
Data Journalist
Data Journalist
Data Journalists use data to tell stories. They may work for newspapers, magazines, or online news organizations. This course provides a strong foundation in data visualization techniques, which are essential for Data Journalists to communicate their findings effectively. The course covers a variety of visualization libraries, including Seaborn, Altair, Bokeh, and Matplotlib, so learners can choose the right tool for the job.
For more career information including salaries, visit:
OpenCourser.com/course/vinl50/visualizacion
Reading list
We've selected eight 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 Avanzada de datos con Python.
Save
Comprehensive guide to the principles of data visualization. It covers a wide range of topics, from the basics of visual perception to the latest trends in data visualization.
Save
This classic text by Edward Tufte seminal work on data visualization. It provides a deep dive into the principles of visual perception and how to use them to create effective and informative graphics.
Save
Provides a comprehensive introduction to data visualization, covering the principles of visual encoding, choosing the right charts and graphs, and best practices for presenting data effectively. It useful reference for both beginners and experienced practitioners.
Practical guide to data visualization using the ggplot2 library in R. It provides a comprehensive overview of the ggplot2 grammar of graphics, and shows how to create a wide range of visualizations.
Focuses on creating interactive data visualizations using web technologies. It covers the latest techniques and best practices for building dynamic and engaging visualizations that can be easily shared and explored.
Practical guide to data visualization using Tableau. It provides a comprehensive overview of Tableau's features and capabilities, and shows how to create a wide range of visualizations.
Beginner-friendly guide to data visualization. It provides a clear and concise overview of the principles of data visualization, and shows how to create a variety of visualizations.
Quick start guide to data visualization using Power BI. It provides a step-by-step guide to getting started with Power BI, and shows how to create a variety of visualizations.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/vinl50/visualizacion
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