Exploratory Data Analysis with Python Cookbook: Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
genuine image
Exploratory Data Analysis with Python Cookbook: Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
Gain practical experience in conducting EDA on a single variable of interest in Python
Exploratory Data Analysis with Python Cookbook: Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
Nº de artículo: 73993632

Exploratory Data Analysis with Python Cookbook: Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data

87% of respondents would recommend this to a friend

Nº de artículo: 73993632

HNL 1814

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

*All items will import from Estados Unidos

En stock
Estados Unidos Importado de la tienda USA

QTY:

Haz tu pedido ahora y recíbelo por ahí Viernes, Octubre 09
Secured transactionsecured transaction

Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

Our Top Logistics Partners
  • fedex
  • dhl
Gain practical experience in conducting EDA on a single variable of interest in Python
Garantía U-Care:
Ninguno
Selecciona un plan
fast shipping

Fast
Shipping

free return

Free
Return*

secure packaging

Secure Packaging

100% original products

100% Original Products

pci-dss

PCI DSS Compliance

iso certified

ISO 27001 Certified

paypal payment
visa payment
mastercard payment

What Stands Out

Diverse Recipes
Includes over 50 practical recipes that cater to various data analysis needs, making it suitable for beginners and experienced analysts alike.
Visual Insights
Focuses on visualizing data effectively, helping users to gain clear, actionable insights from both structured and unstructured datasets.
Python-Based Solutions
Offers Python-centric techniques and tools, ensuring users benefit from widely adopted libraries in data science like Pandas and Matplotlib for optimal analysis.

Detalles de producto

Shop Exploratory Data Analysis with Python Cookbook: Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data online at a best price in Honduras. 1803231106
Publisher Packt Publishing
Publication date June 30, 2023
Language English
Print length 382 pages
ISBN-10 1803231106
ISBN-13 978-1803231105
Item Weight 1.44 pounds (650 grams)
Dimensions 7.5 x 0.87 x 9.25 inches (19.1 x 2.2 x 23.5 cm)

Who Should Buy?

Suitable For
  • Data Analysts

    Ideal for data analysts seeking practical recipes for effective data analysis and visualization using Python.

  • Beginner Programmers

    Great for beginners in programming who want to learn how to analyze data with Python step-by-step.

  • Data Scientists

    Useful for data scientists looking to enhance their exploratory data analysis skills with practical, real-world examples.

Not Suitable For
  • Advanced Users

    Not suitable for advanced users who need in-depth theoretical knowledge rather than practical recipes.

DESCRIPCIÓN DEL PRODUCTO

Exploratory Data Analysis with Python Cookbook: Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data

Dietary Supplement Disclaimer

Statements regarding dietary supplements have not been evaluated by the Food and Drug Administration and are not intended to diagnose, treat, cure, or prevent any disease or health condition.


¿Tienes alguna consulta? Chatea con nosotros

Preguntas y respuestas de los clientes

  • Pregunta: What is the purpose of the Exploratory Data Analysis with Python Cookbook?

    Respuesta: The purpose of this cookbook is to provide practical recipes for analyzing and visualizing both structured and unstructured data using Python. It is designed to help data professionals and enthusiasts gain insights from their datasets efficiently. Each recipe guides users through specific tasks, such as data cleaning, visualization techniques, and statistical analysis, illustrating how to derive meaningful insights. By following these recipes, users can tackle complex data analysis challenges and enhance their analytical skills.
  • Pregunta: Who is the target audience for this cookbook?

    Respuesta: This cookbook primarily targets data analysts, data scientists, and students in the field of data science who are looking for hands-on guidance on exploratory data analysis. Additionally, it caters to professionals seeking to improve their data visualization and analysis skills in Python. Beginners will benefit from clear examples, while experienced users can find advanced techniques to further their knowledge, making it a versatile resource for anyone interested in data exploration.
  • Pregunta: What kind of data analysis techniques are covered in the book?

    Respuesta: The book covers a wide range of data analysis techniques, including data manipulation, data cleaning, and various visualization methods. Techniques such as descriptive statistics, correlation analysis, and hypothesis testing are thoroughly explained. Users also learn how to utilize libraries like Pandas, Matplotlib, and Seaborn to create impactful visualizations. The diverse recipes ensure that readers can apply the techniques to both structured data (like spreadsheets) and unstructured data (such as text data), making the skills applicable in numerous contexts.
  • Pregunta: What are some practical applications of the recipes in the cookbook?

    Respuesta: The recipes in this cookbook can be applied in various domains such as finance for risk analysis, healthcare for patient data insights, marketing for customer segmentation, and more. For instance, a data analyst in marketing could use the visualizations to identify trends in consumer behavior, while a researcher in healthcare might analyze patient data to improve treatment outcomes. These practical applications illustrate how the cookbook serves not only as a learning tool but also as an essential resource in real-world data projects.
  • Pregunta: Are the recipes in the cookbook suitable for beginners?

    Respuesta: Yes, the recipes in this cookbook are suitable for beginners, as they are written in a step-by-step manner that encourages hands-on practice. Each recipe provides clear explanations and practical examples that help newcomers understand the concepts of exploratory data analysis. The cookbook also includes tips on using Python libraries, making it accessible to those who might be starting out. Beginners can build their confidence as they progress through the recipes, gaining valuable skills in data analysis.
  • Pregunta: What Python libraries are utilized in this cookbook?

    Respuesta: The cookbook extensively leverages popular Python libraries such as Pandas for data manipulation, Matplotlib for data visualization, and Seaborn for enhanced graphical representations. These libraries form the backbone of the data analysis processes described in the recipes. By utilizing these tools, users can effectively clean, analyze, and visualize their data, ultimately gaining deeper insights. Familiarity with these libraries not only aids in following the cookbook but also serves as a foundation for further learning in Python.
  • Pregunta: Can the cookbook help with both structured and unstructured data?

    Respuesta: Absolutely! One of the strengths of this cookbook is its focus on addressing both structured and unstructured data analysis. Structured data refers to data that is organized in a fixed format, like databases or spreadsheets, while unstructured data includes text, images, and other non-standard formats. The recipes guide users on how to handle, analyze, and visualize each type of data effectively, allowing for a comprehensive understanding of exploratory data analysis that can be applied in varied scenarios.
  • Pregunta: How does the cookbook facilitate learning through recipes?

    Respuesta: Learning through recipes allows readers to take a practical approach to mastering exploratory data analysis. Each recipe serves as a mini-project, breaking down complex processes into manageable steps that are easier to comprehend. This hands-on style not only reinforces the theoretical aspects but also gives readers the confidence to try their own analyses. By implementing the recipes, learners actively engage with the material, which leads to better retention of techniques and concepts, thus enhancing their overall learning experience.
  • Pregunta: Is there a digital version of the Exploratory Data Analysis with Python Cookbook available?

    Respuesta: Yes, digital versions of the Exploratory Data Analysis with Python Cookbook are typically available for purchase. These formats often offer the added benefit of being searchable, allowing users to quickly find specific recipes or topics of interest. Digital copies can be easily accessed on various devices such as tablets, laptops, and smartphones, making it convenient for on-the-go learning. Readers can enjoy the flexibility of studying at their own pace while carrying the entire cookbook with them.
  • Pregunta: Where can I buy Exploratory Data Analysis with Python Cookbook?

    Respuesta: You can purchase the Exploratory Data Analysis with Python Cookbook on Ubuy. Ubuy provides a user-friendly platform for buying books and various other products, ensuring a seamless shopping experience. With numerous shipping options and customer support, you'll find that Ubuy not only stocks this cookbook but also offers various resources to help you understand and utilize your purchase effectively.

Data Processing Editorial Review

Exploratory Data Analysis with Python Cookbook: Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data is a comprehensive guide published by Packt Publishing. This cookbook contains over 50 practical recipes which empower readers to effectively analyze various data types. It's ideal for data analysts and engineers looking to enhance their skills with hands-on examples. The book is printed in English, spans 382 pages, and was published on June 30, 2023, making it a timely resource for current data practices. It is designed to help users become proficient in extracting insightful information from both structured and unstructured data.

Customer Reviews & Ratings

1 valoraciones de los clientes
  • 5 estrella
    100%
  • 4 estrella
    0%
  • 3 estrella
    0%
  • 2 estrella
    0%
  • 1 estrella
    0%

Revisar este producto

Comparte tus ideas con otros clientes

ventajas

  • Over 50 practical recipes for data analysis
  • Covers both structured and unstructured data
  • Ideal for data analysts and engineers
  • Comprehensive guide with hands-on examples
  • Published recently for current practices

Contras

  • May require prior knowledge of Python programming

Platform Trust & Buyer Confidence

trustpilot logo
4.2/5 9477 reseñas
Read reviews
JK
Jasmin
Verified buyer

“Great products and very good service: very easy and very fast international delivery.”

9 September 2026 · via Trustpilot
AG
Anke
Verified buyer

“Wonderful online shopping experience, smooth transaction from the start. Payment method works conveniently and delivery is unexpectedly fast and reliable. You go the extra mile for service. What makes this even more amazing, you deliver to Namibia. I will remain a happy Ubuy customer and will increase my purchases for sure! Thank you!”

10 September 2026 · via Trustpilot
H
Hazel
Verified buyer

“Very easy to find the products what you need, and so fast delivery, that’s why I highly recommended to others costumers to used ubuy.”

10 September 2026 · via Trustpilot
O
Opaleye
Verified buyer

“I received exactly what I ordered I was skeptical about your site because that was my first time to order. But the order came timely and neatly packaged. I was not disappointed. Thank you.”

11 September 2026 · via Trustpilot
AC
Adele
Verified buyer

“Easy to find and order what you want on the website. Delivery is quick to the UK”

8 September 2026 · via Trustpilot
Pago seguro Global Delivery Easy Returns Genuine Products

Product Price History

Información importante

  • Limitaciones: Para los productos enviados al extranjero, ten en cuenta que cualquier garantía del fabricante puede no ser válida; las opciones de servicio del fabricante pueden no estar disponibles; los manuales del producto, las instrucciones y las advertencias de seguridad pueden no estar en los idiomas del país de destino; los productos (y los materiales que los acompañan) pueden no estar diseñados de acuerdo con las normas, especificaciones y requisitos de etiquetado del país de destino; y los productos pueden no ajustarse al voltaje del país de destino y a otras normas eléctricas (lo que requiere el uso de un adaptador o convertidor, si procede). El destinatario es responsable de asegurarse de que el producto puede ser importado legalmente al país de destino. Cuando hagas un pedido a Ubuy o a sus filiales, el destinatario es el importador registrado y debe cumplir todas las leyes y normativas del país de destino.
  • No todos los productos que aparecen en Ubuy están a la venta, ya que Ubuy es un motor de búsqueda a nivel mundial. Los productos están sujetos a las normas de exportación/comercio.

HNL 1814

Haz tu pedido ahora y recíbelo por ahí Viernes, Octubre 09

QTY:

Secured transactionsecured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners
  • fedex
  • dhl
Fastest cross-border delivery

características y beneficios

  • Comprehensive guide to Exploratory Data Analysis using Python
  • Hands-on guidance and code for analyzing and visualizing structured and unstructured data
  • Suitable for data scientists, data analysts, researchers, and curious learners
  • Explores popular Python libraries such as Pandas, Matplotlib, and Seaborn
  • Gain comprehensive knowledge about EDA and master powerful techniques and tools
  • Learn to overcome challenges of outliers and missing values during data analysis

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns *, and secure packaging on every order.