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María Ignacia España

En este curso basado en un proyecto y de 1 hora de duración, aprenderás a crear gráficas con python y la librería matplotlib, aprendiendo también a personalizar tanto la gráfica como la ventana en la cual se presentará. También se mostrará cómo crear los tipos más comunes de gráficos. Para finalizar se desarrollará un ejercicio práctico en el cual se utilizará todo el aprendizaje, creando una gráfica de resumen de datos de COVID-19 en Latinoamérica extraídos de un repositorio web. Es un curso intermedio, por lo cual necesitas tener conocimientos previos de programación en python.

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What's inside

Syllabus

Project Overview
En este proyecto aprenderás a crear gráficas de python, personalizarlas, además de extraer, trabajar y graficar datos de repositorios web.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Enseña a usar Python para crear gráficos, que es una habilidad útil en varios campos
Desarrolla habilidades prácticas de visualización de datos, lo que es esencial en diversos roles
Proporciona una base sólida para comprender y usar Matplotlib, una importante biblioteca de gráficos en Python
Incluye un proyecto práctico que permite a los alumnos aplicar sus conocimientos de inmediato
Requiere conocimientos previos de programación en Python, lo que puede ser una barrera para algunos alumnos
Se centra en gráficos básicos y no cubre técnicas avanzadas de visualización de datos

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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 Graficando con Python with these activities:
Familiarizar con python
Repasar los conceptos básicos de programación en python reforzará tu comprensión de los materiales del curso.
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  • Revisa la sintaxis básica de Python.
  • Practica la creación de variables, listas y diccionarios.
  • Realiza ejercicios de programación simples para practicar el flujo de control.
Organiza y revisa los materiales del curso
Organizar y revisar los materiales del curso te ayudará a consolidar tu comprensión y preparar tu estudio.
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  • Toma notas durante las lecciones y conferencias.
  • Guarda y organiza tus notas, asignaciones y materiales de estudio.
  • Revisa regularmente los materiales para reforzar tu comprensión.
Tutorial: Crea tus primeras gráficas con matplotlib
Este tutorial guiado te brindará una introducción práctica a matplotlib, la biblioteca de Python para crear y personalizar gráficas.
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  • Visita el sitio web de matplotlib y explora la documentación
  • Sigue el tutorial paso a paso para crear tu primera gráfica simple
  • Experimenta con diferentes tipos de gráficas y personaliza su apariencia
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Ejercicios de práctica de Matplotlib
Fortalece tus habilidades en Matplotlib practicando la creación y personalización de diversos tipos de gráficos, como barras, líneas y dispersión.
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  • Encuentra tutoriales o recursos en línea para ejercicios de práctica de Matplotlib
  • Completa los ejercicios y experimenta con diferentes opciones de personalización
Participa en un grupo de estudio
Participar en un grupo de estudio te permitirá interactuar con otros estudiantes, discutir conceptos y mejorar tu comprensión.
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  • Forma o únete a un grupo de estudio.
  • Reúnete regularmente para discutir el material del curso y trabajar juntos en proyectos.
  • Ayúdate mutuamente a comprender conceptos difíciles.
Tutoriales de Matplotlib
Seguir tutoriales de Matplotlib te permitirá familiarizarte con las funciones y características de la librería.
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  • Encuentra tutoriales en línea o en la documentación oficial de Matplotlib.
  • Sigue los tutoriales paso a paso para aprender a crear diferentes tipos de gráficos.
  • Experimenta con diferentes opciones de personalización para mejorar la apariencia de tus gráficos.
Ejercicios de programación
Realizar ejercicios de programación fortalecerá tus habilidades de codificación y mejorará tu comprensión de los conceptos del curso.
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  • Encuentra ejercicios de programación en línea o en libros.
  • Resuelve los ejercicios utilizando Python y Matplotlib.
  • Comprueba tus soluciones y depura cualquier error.
Práctica: Crea y personaliza varias gráficas
Esta práctica de ejercicios te permite reforzar tus habilidades recién adquiridas creando y personalizando una variedad de gráficas.
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  • Crea un conjunto de datos de muestra y utilízalo para generar diferentes tipos de gráficas
  • Personaliza las etiquetas, los colores, el tamaño y el estilo de las gráficas
Conexión con expertos en visualización de datos
Amplía tus conocimientos conectando con expertos en visualización de datos que puedan brindar orientación y comentarios sobre tu trabajo.
Show steps
  • Asiste a eventos de visualización de datos o únete a comunidades en línea
  • Contacta con personas que admiren su trabajo y solicita orientación
Crea un gráfico de resumen de datos
Crear un gráfico de resumen de datos te ayudará a visualizar y comprender los datos de COVID-19 en Latinoamérica, consolidando tu conocimiento sobre la creación de gráficos con Python.
Show steps
  • Extrae los datos de un repositorio web
  • Limpia y prepara los datos para su uso
  • Crea un gráfico con matplotlib que visualice los datos
  • Personaliza el gráfico para mejorar la legibilidad y claridad
  • Genera un resumen escrito de los hallazgos representados en el gráfico
Crea una visualización de datos personalizada
Crear una visualización de datos personalizada te permitirá aplicar tus conocimientos de Matplotlib y mejorar tus habilidades de visualización.
Show steps
  • Selecciona un conjunto de datos.
  • Decide qué tipo de gráfico es el más adecuado para los datos.
  • Crea el gráfico utilizando Matplotlib, personalizándolo para que sea informativo y atractivo.
  • Presenta tu visualización a otros para obtener comentarios.
Proyecto de visualización de datos COVID-19
Aplica tus conocimientos de Matplotlib y extracción de datos para crear una visualización de datos completa que resuma los datos de COVID-19 de América Latina.
Show steps
  • Recopila datos sobre COVID-19 de un repositorio web
  • Limpia y procesa los datos
  • Crea gráficos que visualicen los datos de manera significativa
  • Redacta un informe o presentación que resuma tus hallazgos
Gráfico de resumen de datos COVID-19 en Latinoamérica
Crear un gráfico de resumen de datos COVID-19 en Latinoamérica te permitirá aplicar tus habilidades de visualización y extracción de datos.
Show steps
  • Extrae los datos de un repositorio web.
  • Preprocesa y limpia los datos.
  • Crea un gráfico que resuma los datos.
  • Presenta tu gráfico a otros para obtener comentarios.

Career center

Learners who complete Graficando con Python will develop knowledge and skills that may be useful to these careers:
Data Journalist
Data Journalists use data to tell stories and inform the public. This course provides a foundation in data visualization using Matplotlib, an essential tool for Data Journalists to create visually appealing and informative graphics that communicate data-driven stories. The course also covers customizing graphics and the plot window, enabling Data Journalists to tailor visualizations to specific audiences and publications, enhancing the impact and accessibility of their data-driven narratives.
Statistician
Statisticians collect, analyze, interpret, and present data to uncover patterns and trends. This course complements a Statistician's skill set by providing a foundation in data visualization with Matplotlib. Effectively visualizing statistical data is crucial for communicating insights and making data-driven decisions. The course also covers customizing graphics and the plot window, enhancing the Statistician's ability to present statistical findings in a visually appealing and informative manner.
Epidemiologist
Epidemiologists study the distribution and determinants of health-related states or events in a population. This course provides a foundation in data visualization using Matplotlib, a valuable tool for Epidemiologists to effectively communicate health data, disease trends, and outbreak patterns to policymakers, healthcare professionals, and the public. The course also covers customizing graphics and the plot window, enabling Epidemiologists to tailor visualizations to specific audiences and purposes, enhancing the impact and accessibility of their findings.
Market Researcher
Market Researchers gather and analyze data to understand consumer behavior, market trends, and industry dynamics. This course provides a foundation in data visualization using Matplotlib, a tool commonly used in market research to create charts, graphs, and infographics that present market data in a clear and compelling way. These visualizations help Market Researchers communicate insights, identify trends, and make data-driven recommendations to clients.
Data Visualization Engineer
Data Visualization Engineers specialize in designing and developing data visualization solutions that communicate complex information in a clear and compelling way. The course provides a solid foundation in data visualization with Matplotlib, enabling learners to create effective and visually appealing graphics, a crucial skill for Data Visualization Engineers. The hands-on project, where learners create a COVID-19 data summary visualization, simulates real-world projects, allowing them to apply their skills and demonstrate their proficiency to potential employers.
Financial Analyst
Financial Analysts use data to make investment recommendations and provide financial advice. This course offers a foundation in data visualization with Matplotlib, a valuable skill for Financial Analysts to effectively communicate financial data, market trends, and investment insights to clients and stakeholders. The course also covers customizing graphics and the plot window, enabling Financial Analysts to tailor visualizations to specific audiences and purposes.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment recommendations. This course provides a foundation in data visualization using Matplotlib, a valuable asset for Quantitative Analysts to effectively communicate complex financial data and analysis results to clients and stakeholders. The course also covers customizing graphics and the plot window, allowing Quantitative Analysts to tailor visualizations to meet specific requirements and audience needs.
Business Analyst
Business Analysts use data to analyze and improve business processes. This course provides a foundation in data visualization using Matplotlib, which is widely used in business intelligence and data analysis. By learning to create effective and visually appealing visualizations, Business Analysts can communicate data-driven insights to stakeholders, identify trends and patterns, and support decision-making.
Data Scientist
Data Scientists use data to gain insights, solve problems, and make predictions to support decision-making. The course introduces essential data visualization techniques using Matplotlib, which is widely used in this field for exploring and presenting data insights. Understanding data visualization is crucial for Data Scientists as it helps them communicate their findings effectively and enables them to identify patterns and trends more easily. The course also covers customizing graphics and the plot window, providing a well-rounded foundation for aspiring Data Scientists.
Data Analyst
Data Analysts play a key role in gathering, cleaning, and analyzing data to help businesses make better decisions by visualizing trends and identifying patterns. Professionals interested in becoming Data Analysts may benefit from this course, as it provides a foundation in data visualization using Matplotlib, a commonly used library for creating interactive charts and graphs. The hands-on exercise in the course, which involves creating a COVID-19 data summary graphic, can help learners apply their knowledge to real-world scenarios and build their portfolio.
Actuary
Actuaries assess and manage financial risks. This course may be useful for Actuaries who want to enhance their data visualization skills using Matplotlib. Effectively visualizing data is crucial for Actuarial work, including analyzing insurance data, modeling financial risks, and communicating complex concepts to clients. The course covers customizing graphics and the plot window, providing Actuaries with the ability to tailor visualizations to meet specific analysis and client reporting requirements.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course may be useful for Machine Learning Engineers who want to enhance their data visualization skills using Matplotlib. Effectively visualizing data is crucial for exploring datasets, identifying patterns, and evaluating model performance. The course also covers customizing graphics and the plot window, providing Machine Learning Engineers with the ability to tailor visualizations for specific analysis and debugging purposes.
UX Designer
UX Designers focus on improving the user experience of websites, applications, and other digital products. While not directly related to UX design, this course provides a foundation in data visualization using Matplotlib, which can be valuable for UX Designers who need to visualize user data, such as website traffic, user behavior, and survey results. This data visualization skill can aid in identifying usability issues, optimizing user flows, and enhancing the overall user experience.
Software Engineer
Software Engineers design, develop, and maintain software systems. While not specific to software engineering, this course can provide a valuable foundation in data visualization with Matplotlib, a versatile library used for creating interactive charts and graphs. This skill can be useful for Software Engineers who need to visualize data for debugging, performance analysis, or user interface design.
Web Developer
Web Developers design, develop, and maintain websites and web applications. While not specific to web development, the fundamental knowledge of data visualization provided in this course can prove useful. Matplotlib is commonly used for creating interactive charts and graphs, which can be integrated into web applications to visualize data, such as user statistics, website traffic, or performance metrics.

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 Graficando con Python.
This classic book on data visualization by Edward Tufte. It provides a wealth of insights into the principles of effective data visualization and must-read for anyone who wants to learn more about the field.
Comprehensive introduction to Python for data analysis. It covers the basics of Python programming, as well as more advanced topics such as data manipulation, data visualization, and machine learning.
Thought-provoking look at the ethical and social implications of data science. It must-read for anyone who wants to understand the broader impact of data science.
Comprehensive introduction to deep learning with Python. It covers the basics of deep learning, as well as more advanced topics such as convolutional neural networks and recurrent neural networks.
Comprehensive reference for data science with Python. It covers a wide range of topics, from data cleaning and manipulation to data visualization and machine learning.
Thought-provoking look at the ethical and social implications of data science. It must-read for anyone who wants to understand the broader impact of data science.
Comprehensive introduction to machine learning with Python. It covers the basics of machine learning, as well as more advanced topics such as deep learning and natural language processing.
Focuses on creating interactive data visualizations for the web using JavaScript and D3.js. It covers a wide range of topics, from basic data visualization techniques to advanced topics such as creating interactive maps and charts.
Hands-on introduction to data visualization with Python and JavaScript. It covers the basics of data visualization, as well as more advanced topics such as interactive visualization and geospatial data visualization.

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