Python Data Science Handbook: Essential Tools for Working with Data,Used
Python Data Science Handbook: Essential Tools for Working with Data,Used
Python Data Science Handbook: Essential Tools for Working with Data,Used

Python Data Science Handbook: Essential Tools for Working with Data,Used

SKU: SONG1491912057 In Stock
Sale price$30.86 Regular price$44.09
Save $13.23
Quantity
Add to wishlist
Add to compare
Shipping & Tax will be calculated at Checkout.
Delivery time: 3-5 business days (USA)
Delivery time: 8-12 business days (International)
15 days return policy
Payment Options

Help

If you have any questions, you are always welcome to contact us. We'll get back to you as soon as possible, withing 24 hours on weekdays.

Customer service

All questions about your order, return and delivery must be sent to our customer service team by e-mail at yourstore@yourdomain.com

Sale & Press

If you are interested in selling our products, need more information about our brand or wish to make a collaboration, please contact us at press@yourdomain.com

For many researchers, Python is a firstclass tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them allIPython, NumPy, Pandas, Matplotlib, ScikitLearn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling daytoday issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the musthave reference for scientific computing in Python.With this handbook, youll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python ScikitLearn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Shipping & Returns

Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.

Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.

Shipping & Returns

Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.

Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.

Warranty

We provide a 2-year limited warranty, from the date of purchase for all our products.

If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.

This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).

Warranty

We provide a 2-year limited warranty, from the date of purchase for all our products.

If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.

This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).

Secure Payment

Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.

We accept payments with :
Visa, MasterCard, American Express, Paypal, Shopify Payments, Shop Pay and more.

Secure Payment

Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.

We accept payments with :
Visa, MasterCard, American Express, Paypal, Shopify Payments, Shop Pay and more.

Related Products

You may also like

Frequently Asked Questions

  • Q: What is the main focus of the Python Data Science Handbook? A: The Python Data Science Handbook focuses on essential tools for data science, including libraries like IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn, providing a comprehensive guide for manipulating, analyzing, and visualizing data.
  • Q: Who is the author of the Python Data Science Handbook? A: The author of the Python Data Science Handbook is Jake VanderPlas, who is known for his contributions to the field of data science and Python programming.
  • Q: Is the Python Data Science Handbook suitable for beginners? A: While the Python Data Science Handbook is ideal for those with some familiarity in Python, it serves as a comprehensive reference that can also benefit beginners who are eager to learn the essential tools of data science.
  • Q: What type of binding does this book have? A: The Python Data Science Handbook is available in paperback binding, making it durable and easy to handle for both reading and reference.
  • Q: How many pages are included in the Python Data Science Handbook? A: The Python Data Science Handbook contains a total of 546 pages, packed with valuable information and tutorials on data science tools.
  • Q: When was the Python Data Science Handbook published? A: The Python Data Science Handbook was published on January 3, 2017.
  • Q: What topics are covered in the Python Data Science Handbook? A: The book covers a range of topics including data manipulation with Pandas, data visualization with Matplotlib, and machine learning with Scikit-Learn, among others.
  • Q: Can this book help with machine learning concepts? A: Yes, the Python Data Science Handbook includes guidance on using Scikit-Learn, which is a popular library for implementing machine learning algorithms in Python.
  • Q: Is the Python Data Science Handbook a good reference for scientific computing? A: Absolutely, the Python Data Science Handbook is considered a must-have reference for scientific computing in Python, providing practical insights for working with data.
  • Q: What is the condition of the book listed? A: The book is listed in good condition, indicating that it is well-maintained and suitable for use.