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Analíticas de Datos con Pandas

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Based on 26 ratings
see reviews
Jesus Aguilar Gonzalez

La analítica de datos ha avanzado considerablemente en los últimos años y ahora existen diversas herramientas que nos permiten realizar tareas o procesos que antes eran complicados de realizar. Gracias a su versatilidad, el lenguaje de programación Python posee una serie de librerías que permiten realizar proyectos de analítica de datos de una forma muy sencilla y una de las librerías más populares es Pandas.

En este curso nos enfocaremos a:

* Conocer los conceptos, métodos y funciones de la librería Pandas.

* Analizar datos rápida y fácilmente con la librería de Pandas.

Read more

La analítica de datos ha avanzado considerablemente en los últimos años y ahora existen diversas herramientas que nos permiten realizar tareas o procesos que antes eran complicados de realizar. Gracias a su versatilidad, el lenguaje de programación Python posee una serie de librerías que permiten realizar proyectos de analítica de datos de una forma muy sencilla y una de las librerías más populares es Pandas.

En este curso nos enfocaremos a:

* Conocer los conceptos, métodos y funciones de la librería Pandas.

* Analizar datos rápida y fácilmente con la librería de Pandas.

* Usar la librería de Pandas para importar, construir y manipular DataFrames.

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What's inside

Syllabus

Primeros Pasos con Pandas
En este primer tema nos enfocaremos a entender cómo instalar y preparar todo para utilizar la librería Pandas y aprenderemos los elementos fundamentales de la librería; además, conoceremos un poco de la historia de esta librería y el porqué es tan popular.
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Conceptos, técnicas y funciones de Pandas, que es una biblioteca de Python de analítica de datos
Análisis de datos rápido y sencillo con la biblioteca Pandas
Importación, construcción y manipulación de DataFrames con Pandas

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Reviews summary

Fundamentos de pandas para análisis de datos

Según los estudiantes, este curso es una introducción excelente y sólida a la librería Pandas para el análisis de datos. Los conceptos son explicados con gran claridad por el instructor, lo que facilita el aprendizaje, incluso para quienes tienen una experiencia básica con Python. Se destaca por sus ejercicios y demos prácticos, que ayudan a consolidar el conocimiento y son muy aplicables, especialmente en los casos de uso para Análisis Exploratorio de Datos. Si bien es ideal para principiantes, algunos lo encuentran demasiado básico o lento si ya poseen experiencia previa, sugiriendo la necesidad de contenido más avanzado o complejo en ciertas operaciones.
Ideal para principiantes, básico para expertos en el tema.
"Lo recomiendo totalmente a cualquiera que empiece en analítica de datos, incluso con experiencia básica en Python."
"Si ya tengo algo de experiencia con Pandas, el curso puede parecer un poco lento y básico en algunas partes."
"Como ingeniero, buscaba una introducción rápida a Pandas para proyectos internos y este curso cumplió; no es para expertos, pero es perfecto para empezar."
"Siento que el curso es demasiado básico, ya tenía experiencia con Python y esperaba algo más avanzado."
Ejercicios y casos de uso útiles para la aplicación real.
"Los ejercicios prácticos realmente ayudan a consolidar el aprendizaje del curso."
"Me gustaron mucho los 'Casos de Uso', los encontré muy aplicables a situaciones reales."
"Las prácticas son muy valiosas para aplicar lo aprendido y mejorar mis habilidades en análisis de datos."
Explicaciones didácticas y un excelente punto de partida.
"Las explicaciones del profesor son muy claras y los ejercicios prácticos realmente ayudan a consolidar el aprendizaje."
"Las explicaciones sobre Series y DataFrames son muy detalladas y bien estructuradas, lo que me permitió entender mejor el manejo de grandes datos."
"El instructor es excelente, explica muy bien y de manera didáctica, por lo que recomiendo este curso para empezar."
Necesidad de ejemplos y temas más avanzados para algunos usuarios.
"Quizás me hubiera gustado ver ejemplos más complejos o de optimización de código en el curso."
"Creo que el tema de 'Operaciones en Pandas' podría ser más profundo."
"Los casos de uso eran interesantes, pero no profundizaban lo suficiente; necesitaré otros recursos para ir más allá."

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 Analíticas de Datos con Pandas with these activities:
Organize Course Materials
Maximize your learning by organizing and reviewing course materials, ensuring you have a comprehensive understanding of the concepts and techniques covered.
Show steps
  • Gather all course handouts, lecture notes, assignments, and quizzes.
  • Create a system for organizing the materials, such as folders or a digital notebook.
  • Review the materials regularly to reinforce your learning and identify areas for further study.
Review Data Analysis Concepts
Refresh your knowledge of data analysis concepts to ensure you have a solid foundation for understanding Pandas and its applications.
Show steps
  • Review notes, textbooks, or online resources on data analysis.
  • Recall key concepts such as data types, data distributions, and statistical measures.
  • Complete practice problems to reinforce your understanding.
Revise Basic Programming Concepts
Reinforce your understanding of basic programming concepts to ensure a strong foundation before starting the course.
Browse courses on Programming Fundamentals
Show steps
  • Review core programming principles such as variables, data types, and operators.
  • Practice writing simple programs using Python.
  • Complete coding challenges and exercises to test your comprehension.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice Data Exploration with Pandas
Kickstart your learning by working on a project that involves data exploration using Pandas, providing hands-on experience and immediate application of course concepts.
Show steps
  • Choose a dataset that aligns with your interests or learning objectives.
  • Load the dataset into a Pandas DataFrame and explore its structure, data types, and missing values.
  • Perform basic data cleaning and preprocessing tasks to prepare the data for analysis.
  • Conduct exploratory data analysis using Pandas functions to identify patterns, trends, and outliers.
Explore Pandas Tutorials
Enhance your understanding of Pandas by following guided tutorials to gain practical experience.
Show steps
  • Search for tutorials that cover key Pandas concepts and features.
  • Work through the tutorials step-by-step, practicing the techniques and functions.
  • Apply what you learn by completing practice exercises within the tutorials.
Solve Pandas Challenges
Challenge yourself and refine your Pandas skills by solving coding challenges and exercises.
Show steps
  • Find online platforms or resources that offer Pandas coding challenges.
  • Select challenges that align with your skill level and learning objectives.
  • Work through the challenges, debugging and refining your solutions.
Build a Pandas Project
Solidify your learning by applying Pandas to a practical project, demonstrating your proficiency and problem-solving skills.
Show steps
  • Identify a project idea that aligns with your interests and course objectives.
  • Design and plan your project, outlining the data you need, the analysis you will perform, and the expected outcomes.
  • Implement your project using Pandas, leveraging its functions and techniques to solve the problem.
  • Write a project report or create a presentation to showcase your work.
Tutor Fellow Students
Reinforce your learning by sharing your knowledge and assisting other students, deepening your understanding through effective communication.
Show steps
  • Volunteer as a tutor or join a study group to support fellow students.
  • Prepare lesson plans and materials to facilitate effective tutoring sessions.
  • Provide guidance, answer questions, and demonstrate problem-solving techniques to your tutees.

Career center

Learners who complete Analíticas de Datos con Pandas will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst uses data to solve business problems, which can include collecting, cleaning, and analyzing data. As a Data Analyst, you would be able to use the skills you learn in this course to import, build, and manipulate dataframes, as well as analyze data quickly and efficiently.
See salaries and explore the career path for Data Analyst
Data Scientist
Data Scientists use scientific methods and processes to extract knowledge and insights from data in various forms, both structured and unstructured, and apply knowledge and expertise to predict future trends and behaviors. This course can help you become a Data Scientist because it will teach you how to use Pandas to perform data analysis and modeling.
See salaries and explore the career path for Data Scientist
Business Analyst
A Business Analyst uses data to understand customer needs and pain points, as well as to improve business processes. This course can help you become a Business Analyst because it will teach you how to use Pandas to clean, analyze, and visualize data.
See salaries and explore the career path for Business Analyst
Statistician
A Statistician collects, analyzes, interprets, and presents data in order to help businesses make informed decisions. This course can help you become a Statistician because it will help you build a foundation in data analysis and manipulation.
See salaries and explore the career path for Statistician
Machine Learning Engineer
Machine Learning Engineers use data to train and build machine learning models, which can be used to automate tasks, make predictions, and improve decision-making. This course can help you become a Machine Learning Engineer because it will teach you how to use Pandas to prepare data for machine learning models.
See salaries and explore the career path for Machine Learning Engineer
Data Visualization Engineer
A Data Visualization Engineer designs and creates visual representations of data in order to communicate insights and trends to stakeholders. This course can help you become a Data Visualization Engineer because it will teach you how to use Pandas to create visualizations such as charts and graphs.
See salaries and explore the career path for Data Visualization Engineer
Quantitative Analyst
A Quantitative Analyst develops and uses mathematical and statistical models to analyze data and make investment decisions. This course can help you become a Quantitative Analyst because it will teach you how to use Pandas to perform data analysis and modeling.
See salaries and explore the career path for Quantitative Analyst
Financial Analyst
A Financial Analyst helps businesses evaluate and forecast the financial performance of investments. In this role, you would use the skills learned in this course to analyze data and understand trends.
See salaries and explore the career path for Financial Analyst
Market Research Analyst
A Market Research Analyst conducts research to understand market trends and consumer behavior, and uses this information to develop marketing strategies. In this role, you would use the skills learned in this course to analyze data and understand trends.
See salaries and explore the career path for Market Research Analyst
Actuary
An Actuary uses mathematical and statistical techniques to assess risk and uncertainty, and to develop insurance and pension plans. In this role, you would use the skills learned in this course to analyze data and understand trends.
See salaries and explore the career path for Actuary
Data Architect
A Data Architect designs and manages data systems to ensure that data is stored and managed efficiently and securely. In this role, you would use the skills learned in this course to design and implement data pipelines.
See salaries and explore the career path for Data Architect
Software Developer
A Software Developer designs, develops, and maintains software applications. In this role, you would use the skills learned in this course to develop and maintain data-driven applications.
See salaries and explore the career path for Software Developer
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines to ensure that data is available for analysis and reporting. In this role, you would use the skills learned in this course to design and implement data pipelines.
See salaries and explore the career path for Data Engineer
Database Administrator
A Database Administrator manages and maintains databases to ensure that data is stored and managed efficiently and securely. This course may be useful for a Database Administrator who wants to learn more about data analysis and manipulation.
See salaries and explore the career path for Database Administrator
Information Systems Manager
An Information Systems Manager plans and manages the IT infrastructure and services for an organization, which may include managing data systems. This course may be useful for an Information Systems Manager who wants to learn more about data analysis and manipulation.
See salaries and explore the career path for Information Systems Manager

Reading list

We've selected seven 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 Analíticas de Datos con Pandas.
Cover image
Python Data Science Handbook
Save
Este libro cubre tanto los fundamentos de Pandas como las técnicas avanzadas de ciencia de datos. Es un recurso valioso para aquellos que buscan una comprensión integral del análisis de datos con Pandas.
(English) Python Data Science Handbook: Essential Tools for...
Paperback
$$$
Cover image
Pandas 1.x Cookbook
Save
Esta segunda edición actualizada del Pandas Cookbook ofrece soluciones prácticas a problemas comunes de Pandas. Es un recurso esencial para usuarios de todos los niveles que buscan expandir sus habilidades.
(English) Pandas 1.x Cookbook - Second Edition: Practical...
Paperback
$$$
(English) Pandas 1.x Cookbook: Practical recipes for...
Kindle Edition
$$
Cover image
Python for Data Analysis
Save
Este libro proporciona una base sólida en Python y Pandas para el análisis de datos. Es esencial para principiantes que buscan comprender los fundamentos y desarrollar habilidades de programación.
(English) Python for Data Analysis: Data Wrangling with...
Paperback
$$
(English) Python for Data Analysis
Kindle Edition
$$
(English) Python for Data Analysis: Data Wrangling with...
Paperback
$$$
Cover image
Contemporary Perspectives on Ophthalmology, 10e
Save
Este libro se enfoca en las técnicas y patrones efectivos para utilizar Pandas. Proporciona soluciones prácticas y consejos para mejorar el código y optimizar el rendimiento.
(English) Contemporary Perspectives on Ophthalmology,10e
Hardcover
$$$
(English) Contemporary Perspectives on Ophthalmology, 10e
Kindle Edition
$$$
Cover image
Python Data Analysis
Save
Este libro proporciona una introducción completa a las librerías de análisis de datos de Python, incluyendo Pandas. Es un recurso valioso para principiantes que buscan comprender los conceptos básicos y las aplicaciones.
(English) Python Data Analysis - Third Edition: Perform data...
Paperback
$$
(English) Python Data Analysis: Perform data collection, data...
Kindle Edition
$$
Cover image
Pandas for Everyone
Save
Este libro está dirigido a usuarios no técnicos que buscan aprender Pandas para el análisis de datos. Proporciona una introducción fácil de seguir y ejemplos prácticos.
(English) Pandas for Everyone: Python Data Analysis (Addison...
Paperback
$$
(English) Pandas for Everyone: Python Data Analysis (Addison...
Paperback
$$
(English) Pandas for Everyone: Python Data Analysis (Addison...
Kindle Edition
$$
(English) Pandas for Everyone: Python Data Analysis (Addison...
Kindle Edition
$$
Machine Learning Con Pytorch Y Scikit Lean
Save
Este libro cubre el aprendizaje automático utilizando Python y la biblioteca scikit-learn. Proporciona una base para comprender los algoritmos de aprendizaje automático y su implementación con Pandas.
Machine Learning con PyTorch y Scikit-Learn:...
Paperback
$$$

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Course image
Rating
4.5 Filled star Filled star Filled star Filled star Empty star
Effort
24 hours to complete
Level
Introductory
Via
Coursera
Institution
Tecnológico de Monterrey
Instructor
Jesus Aguilar Gonzalez
Language
Español
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Conceptos, técnicas y funciones de Pandas, que es una biblioteca de Python de analítica de datos
Análisis de datos rápido y sencillo con la biblioteca Pandas
Importación, construcción y manipulación de DataFrames con Pandas
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