Python para el análisis de datos: Pandas y NumPy from Coursera

Al final de este proyecto guiado, podrás manipular datos usando las librerías NumPy y Pandas de Python.

NumPy es una biblioteca de Python utilizada para trabajar con matrices.

En Python, se puede trabajar con listas que actúan como arreglos, pero el procesamiento es lento. Con NumPy la manipulación de una matriz es mucho más rápido que las listas tradicionales de Python.

Por otro lado, Pandas es una herramienta de análisis y manipulación de datos de código abierto rápida, potente, flexible y fácil de usar, construida sobre el lenguaje de programación Python.

A lo largo de este proyecto desarrollaremos un caso estudio, que te permitirá comprender y aplicar los conceptos necesarios para el análisis de datos con las librerías Pandas y Numpy.

Iniciaremos este proyecto con la revisión de la biblioteca NumPy, haciendo referencia a la creación de arreglos de una y dos dimensiones. Aprenderás a acceder a los valores de los arreglos y harás uso de los métodos para manipular y transformar los datos.

Posteriormente con pandas, aprenderás a leer datos de un dataset, seleccionar y realizar operaciones con funciones.

Este proyecto es de nivel básico y está diseñado para desarrolladores y personas que deseen aprender Python para el análisis de datos haciendo uso de Pandas y NumPy.

Cada tarea del proyecto te ayudará a colocar en práctica los conocimientos adquiridos de forma fácil.

Adquirir conocimientos de Python para el análisis de datos, te llevará a ser más atractivo al momento de aplicar en ofertas laborales.

What's inside

Syllabus

Visión general del proyecto

Al final de este proyecto guiado, podrás manipular datos usando las librerías NumPy y Pandas de Python. NumPy es una biblioteca de Python utilizada para trabajar con matrices. En Python, se puede trabajar con listas que actúan como arreglos, pero el procesamiento es lento. Con NumPy la manipulación de una matriz es mucho más rápido que las listas tradicionales de Python. Por otro lado, Pandas es una herramienta de análisis y manipulación de datos de código abierto rápida, potente, flexible y fácil de usar, construida sobre el lenguaje de programación Python. A lo largo de este proyecto desarrollaremos un caso estudio, que te permitirá comprender y aplicar los conceptos necesarios para el análisis de datos con las librerías Pandas y Numpy. Iniciaremos este proyecto con la revisión de la biblioteca NumPy, haciendo referencia a la creación de arreglos de una y dos dimensiones. Aprenderás a acceder a los valores de los arreglos y harás uso de los métodos para manipular y transformar los datos. Posteriormente con pandas, aprenderás a leer datos de un dataset, seleccionar y realizar operaciones con funciones. Este proyecto es de nivel básico y está diseñado para desarrolladores y personas que deseen aprender Python para el análisis de datos haciendo uso de Pandas y NumPy. Cada tarea del proyecto te ayudará a colocar en práctica los conocimientos adquiridos de forma fácil. Adquirir conocimientos de Python para el análisis de datos, te llevará a ser más atractivo al momento de aplicar en ofertas laborales.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Enseña NumPy, que es una biblioteca estándar de la industria para manipular matrices

Enseña Pandas, que es una biblioteca estándar de la industria para el análisis de datos

Desarrolla habilidades de manipulación y análisis de datos, que son habilidades básicas para los desarrolladores

Incluye un estudio de caso para aplicar conceptos aprendidos

Está diseñado para principiantes, lo que lo hace accesible para aquellos nuevos en el análisis de datos

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 Python para el análisis de datos: Pandas y NumPy with these activities:

Leer y resumir el libro "Numpy para el análisis de datos"

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Leer y resumir el libro "Numpy para el análisis de datos" te proporcionará una base sólida en Numpy.

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Lee el libro.
Resume los conceptos clave del libro.
Aplica los conceptos aprendidos a tus propios proyectos.
Comparte tu resumen con otros estudiantes.

Participar en sesiones de estudio grupales con otros estudiantes

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Participar en sesiones de estudio grupales te permitirá colaborar con otros estudiantes y reforzar tu comprensión.

Browse courses on NumPy

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Formen un grupo de estudio con otros estudiantes.
Reúnanse regularmente para discutir el material del curso.
Colaboren en proyectos y tareas.

Realizar ejercicios de Numpy y Pandas

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Practicar ejercicios de Numpy y Pandas te ayudará a mejorar tus habilidades y comprensión de las bibliotecas.

Browse courses on NumPy

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Crea un arreglo de Numpy con diferentes tipos de datos.
Manipula los datos del arreglo utilizando métodos de Numpy.
Lee un archivo CSV utilizando Pandas.
Selecciona y filtra datos del DataFrame de Pandas.
Agrupa y agrega datos utilizando funciones de Pandas.

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Asistir a talleres sobre técnicas avanzadas de análisis de datos

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Asistir a talleres te permitirá aprender de expertos y mejorar tus habilidades.

Browse courses on NumPy

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Busca talleres sobre técnicas avanzadas de análisis de datos.
Regístrate y asiste al taller.
Participa activamente en las actividades del taller.
Aplica los conceptos aprendidos a tus propios proyectos.

Seguir tutoriales sobre técnicas avanzadas de Pandas

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Seguir tutoriales sobre técnicas avanzadas de Pandas te permitirá ampliar tus conocimientos y habilidades.

Browse courses on Pandas

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Encuentra tutoriales en línea sobre técnicas avanzadas de Pandas.
Sigue los pasos de los tutoriales para implementar las técnicas.
Aplica las técnicas aprendidas a tus propios proyectos de análisis de datos.

Contribuir a proyectos de código abierto relacionados con Numpy o Pandas

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Contribuir a proyectos de código abierto te permitirá mejorar tus habilidades y colaborar con otros.

Browse courses on NumPy

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Encuentra proyectos de código abierto relacionados con Numpy o Pandas.
Lee la documentación y familiarízate con el proyecto.
Realiza cambios y envía solicitudes de extracción.
Revisa el código y responde comentarios.

Crear un proyecto de análisis de datos utilizando Numpy y Pandas

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Crear un proyecto de análisis de datos te permitirá aplicar tus habilidades y conocimientos de Numpy y Pandas.

Browse courses on NumPy

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Define el objetivo de tu proyecto.
Recopila y prepara los datos.
Analiza los datos utilizando Numpy y Pandas.
Visualiza y presenta tus resultados.

Participar en concursos y competencias de análisis de datos

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Participar en concursos y competencias te permitirá poner a prueba tus habilidades y aprender de otros.

Browse courses on NumPy

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Busca concursos y competencias relevantes.
Forma un equipo o participa individualmente.
Completa la tarea del concurso.
Analiza tus resultados y aprende de los comentarios.

Career center

Learners who complete Python para el análisis de datos: Pandas y NumPy will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use their knowledge of data analysis tools and techniques to transform raw data into meaningful insights. They work with a variety of data sources, including structured and unstructured data, to identify trends and patterns. Data Analysts often use programming languages such as Python to develop data analysis scripts and automate tasks. The 'Python for Data Analysis: Pandas and NumPy' course can help you develop the skills you need to be successful as a Data Analyst. This course will teach you how to use Pandas and NumPy to manipulate and analyze data, and you will learn how to use these tools to solve real-world problems.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their knowledge of data analysis and machine learning to build predictive models and solve business problems. They work with a variety of data sources, including structured and unstructured data, to identify trends and patterns. Data Scientists often use programming languages such as Python to develop data analysis scripts and machine learning models. The 'Python for Data Analysis: Pandas and NumPy' course can help you develop the skills you need to be successful as a Data Scientist. This course will teach you how to use Pandas and NumPy to manipulate and analyze data, and you will learn how to use these tools to solve real-world problems.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers use their knowledge of machine learning to build and deploy machine learning models. They work with a variety of data sources, including structured and unstructured data, to identify trends and patterns. Machine Learning Engineers often use programming languages such as Python to develop machine learning models and deploy them to production. The 'Python for Data Analysis: Pandas and NumPy' course can help you develop the skills you need to be successful as a Machine Learning Engineer. This course will teach you how to use Pandas and NumPy to manipulate and analyze data, and you will learn how to use these tools to build and deploy machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Quantitative Analyst

Quantitative Analysts use their knowledge of mathematics and statistics to develop and implement quantitative models. They work with a variety of data sources, including structured and unstructured data, to identify trends and patterns. Quantitative Analysts often use programming languages such as Python to develop quantitative models and analyze data. The 'Python for Data Analysis: Pandas and NumPy' course can help you develop the skills you need to be successful as a Quantitative Analyst. This course will teach you how to use Pandas and NumPy to manipulate and analyze data, and you will learn how to use these tools to develop and implement quantitative models.

See salaries and explore the career path for Quantitative Analyst

Business Analyst

Business Analysts use their knowledge of business and data analysis to identify and solve business problems. They work with a variety of stakeholders, including business leaders, IT professionals, and end users, to gather requirements and develop solutions. Business Analysts often use programming languages such as Python to develop data analysis scripts and automate tasks. The 'Python for Data Analysis: Pandas and NumPy' course can help you develop the skills you need to be successful as a Business Analyst. This course will teach you how to use Pandas and NumPy to manipulate and analyze data, and you will learn how to use these tools to solve real-world business problems.

See salaries and explore the career path for Business Analyst

Data Engineer

Data Engineers use their knowledge of data engineering to design and build data pipelines. They work with a variety of data sources, including structured and unstructured data, to ensure that data is available and accessible to data analysts and other stakeholders. Data Engineers often use programming languages such as Python to develop data pipelines and automate tasks. The 'Python for Data Analysis: Pandas and NumPy' course can help you develop the skills you need to be successful as a Data Engineer. This course will teach you how to use Pandas and NumPy to manipulate and analyze data, and you will learn how to use these tools to design and build data pipelines.

See salaries and explore the career path for Data Engineer

Statistician

Statisticians use their knowledge of statistics to collect, analyze, and interpret data. They work with a variety of data sources, including structured and unstructured data, to identify trends and patterns. Statisticians often use programming languages such as Python to develop statistical models and analyze data. The 'Python for Data Analysis: Pandas and NumPy' course can help you develop the skills you need to be successful as a Statistician. This course will teach you how to use Pandas and NumPy to manipulate and analyze data, and you will learn how to use these tools to develop and implement statistical models.

See salaries and explore the career path for Statistician

Financial Analyst

Financial Analysts use their knowledge of finance and data analysis to evaluate investments and make financial recommendations. They work with a variety of data sources, including financial data and news articles, to identify trends and patterns. Financial Analysts often use programming languages such as Python to develop financial models and analyze data. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Financial Analysts who want to learn how to use Python to analyze financial data.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries use their knowledge of mathematics and statistics to assess risk and develop insurance policies. They work with a variety of data sources, including mortality data and financial data, to identify trends and patterns. Actuaries often use programming languages such as Python to develop actuarial models and analyze data. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Actuaries who want to learn how to use Python to analyze actuarial data.

See salaries and explore the career path for Actuary

Market Researcher

Market Researchers use their knowledge of market research and data analysis to understand consumer behavior. They work with a variety of data sources, including survey data and sales data, to identify trends and patterns. Market Researchers often use programming languages such as Python to develop market research models and analyze data. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Market Researchers who want to learn how to use Python to analyze market research data.

See salaries and explore the career path for Market Researcher

Operations Research Analyst

Operations Research Analysts use their knowledge of operations research and data analysis to improve the efficiency of organizations. They work with a variety of data sources, including operational data and financial data, to identify trends and patterns. Operations Research Analysts often use programming languages such as Python to develop operations research models and analyze data. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Operations Research Analysts who want to learn how to use Python to analyze operations research data.

See salaries and explore the career path for Operations Research Analyst

Software Engineer

Software Engineers use their knowledge of software development to design and build software applications. They work with a variety of programming languages and technologies to develop software solutions for a variety of industries. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Software Engineers who want to learn how to use Python for data analysis.

See salaries and explore the career path for Software Engineer

Data Management Analyst

Data Management Analysts use their knowledge of data management to design and implement data management solutions. They work with a variety of data sources and technologies to ensure that data is available and accessible to data analysts and other stakeholders. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Data Management Analysts who want to learn how to use Python for data analysis.

See salaries and explore the career path for Data Management Analyst

Computer Scientist

Computer Scientists use their knowledge of computer science to develop new algorithms and technologies. They work with a variety of programming languages and technologies to develop computer science solutions for a variety of industries. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Computer Scientists who want to learn how to use Python for data analysis.

See salaries and explore the career path for Computer Scientist

Database Administrator

Database Administrators use their knowledge of database administration to design and implement database solutions. They work with a variety of database technologies to ensure that data is available and accessible to data analysts and other stakeholders. The 'Python for Data Analysis: Pandas and NumPy' course may be useful for Database Administrators who want to learn how to use Python for data analysis.

See salaries and explore the career path for Database Administrator

Python para el análisis de datos

Pandas y NumPy

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