Analíticas de Datos con Pandas from Coursera

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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.

Componentes principales en Pandas

Una parte fundamental de Pandas es la manipulación de estructuras de datos y en este apartado estaremos enfocándonos a conocer la forma en la que Pandas maneja las estructuras de datos (series, dataframes, etc.). Adicionalmente estaremos aprendiendo las principales funciones que utiliza Pandas para manipular y analizar los datos.

Operaciones en Pandas

La popularidad de Pandas radica en que muchos lo llaman el Excel con esteroides, pues ha desarrollado funciones que permiten que ciertas operaciones sean muy sencillas y fáciles de implementar para realizar análisis muy complejos. En este apartado, revisaremos las operaciones básicas y avanzadas que maneja Pandas para realizar cálculos en estructuras de datos, columnas, renglones o datos de tipo cadena.

Casos de Uso con Pandas

El Análisis Exploratorio de Datos o EDA es una forma de analizar datos que fue definido por John W. Turkey; este es una parte fundamental para la realización de proyectos de ciencia de datos. En este apartado nos centraremos en aprender a realizar un EDA usando Pandas. Adicionalmente, otra de las etapas importantes de la ciencia de datos es la visualización de datos y en este apartado conoceremos como realizar este proceso en Pandas con la ayuda de librerías que apoyan a Pandas.

Good to know

Know what's good

, what to watch for

, 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

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

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Maximize your learning by organizing and reviewing course materials, ensuring you have a comprehensive understanding of the concepts and techniques covered.

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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

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Refresh your knowledge of data analysis concepts to ensure you have a solid foundation for understanding Pandas and its applications.

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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

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Reinforce your understanding of basic programming concepts to ensure a strong foundation before starting the course.

Browse courses on Programming Fundamentals

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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.

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Practice Data Exploration with Pandas

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Kickstart your learning by working on a project that involves data exploration using Pandas, providing hands-on experience and immediate application of course concepts.

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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

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Enhance your understanding of Pandas by following guided tutorials to gain practical experience.

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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

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Challenge yourself and refine your Pandas skills by solving coding challenges and exercises.

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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

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Solidify your learning by applying Pandas to a practical project, demonstrating your proficiency and problem-solving skills.

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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

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Reinforce your learning by sharing your knowledge and assisting other students, deepening your understanding through effective communication.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Analíticas de Datos con Pandas

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