logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Python for Data Analysis, 3rd Edition (Second Early Release) by Wes McKinney ISBN 9781098104023, 1098104021

  • SKU: EBN-36296812
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

5.0

11 reviews
Instant download (eBook) Python for Data Analysis, 3rd Edition (Second Early Release) after payment.
Authors:Wes McKinney
Pages:361 pages.
Year:2021
Editon:3rd
Publisher:O'Reilly Media, Inc.
Language:english
File Size:2.94 MB
Format:pdf
ISBNS:9781098104023, 1098104021
Categories: Ebooks

Product desciption

(Ebook) Python for Data Analysis, 3rd Edition (Second Early Release) by Wes McKinney ISBN 9781098104023, 1098104021

First six chapters (out of thirteen) and appendices only.Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the Jupyter notebook and IPython shell for exploratory computing Learn basic and advanced features in NumPy Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas group by facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products