Report file quality
upload/bibliotik/P/Python Data Science Handbook - Jake VanderPlas.pdf
Python Data Science Handbook : Essential Tools for Working with Data 🔍
VanderPlas, Jacob T O'Reilly Media, Incorporated, Sebastopol, CA, 2017
English [en] · PDF · 20.9MB · 2017 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save
description
"For many researchers, Python is a first-class 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 all--IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, 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 day-to-day 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 must-have reference for scientific computing in Python. With this handbook, you'll 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 Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms." -- Prové de Proquest
Alternative filename
lgli/Z:\Bibliotik_\33\P\Python Data Science Handbook - Jake VanderPlas.pdf
Alternative filename
lgrsnf/Z:\Bibliotik_\33\P\Python Data Science Handbook - Jake VanderPlas.pdf
Alternative filename
nexusstc/Python data science handbook: essential tools for working with data/fc921256bbe1c91a6a460de80de24bda.pdf
Alternative filename
zlib/Computers/Programming/VanderPlas, Jacob T/Python data science handbook: essential tools for working with data_5969737.pdf
Alternative title
Python для сложных задач: наука о данных и машинное обучение: 16+
Alternative author
Дж. Вандер Плас; [перевела с английского И. Пальти]
Alternative author
Jacob T. Vanderplas; Jake VanderPlas
Alternative author
Плас, Джейк Вандер
Alternative publisher
Питер
Alternative edition
First edition, Beijing; Boston; Farnham; Sebastopol; Tokyo, 2016
Alternative edition
Бестселлеры O'Reilly, Санкт-Петербург [и др.], Russia, 2020
Alternative edition
Бестселлеры O'Reilly, Санкт-Петербург [и др.], Russia, 2018
Alternative edition
United States, United States of America
Alternative edition
O'Reilly Media, Sebastopol, CA, 2016
Alternative edition
First edition, Sebastopol, CA, 2016
Alternative edition
1st Edition, Dec 10, 2016
Alternative edition
Beijing, 2017
Alternative edition
1, PS, 2017
metadata comments
lg2701518
metadata comments
producers:
Antenna House PDF Output Library 6.2.609 (Linux64)
metadata comments
{"isbns":["1491912057","149191209X","9781491912058","9781491912096"],"publisher":"O'Reilly Media"}
metadata comments
Фактическая дата выхода в свет - 2019
Пер.: Plas, Jake Vander Python data science handbook Beijing [etc.] : O'Reilly, cop. 2017 978-1491912058
metadata comments
РГБ
metadata comments
Russian State Library [rgb] MARC:
=001 010135037
=005 20200818133845.0
=008 191025s2020\\\\ru\\\\\\\\\\\\|||\|\rus|d
=017 \\ $a КН-П-20-041981 $b RuMoRKP
=017 \\ $a КН-П-19-080267 $b RuMoRKP
=020 \\ $a 978-5-4461-0914-2
=040 \\ $a RuMoRGB $b rus $e rcr
=041 1\ $a rus $h eng
=044 \\ $a ru
=084 \\ $a З973.2-018.19Python,0 $2 rubbk
=100 1\ $a Плас, Джейк Вандер
=245 00 $a Python для сложных задач: наука о данных и машинное обучение : $b 16+ $c Дж. Вандер Плас ; [перевела с английского И. Пальти]
=260 \\ $a Санкт-Петербург [и др.] $b Питер $c 2020
=300 \\ $a 572, [1] с. $b ил., табл. $c 24 см
=336 \\ $a Текст (визуальный)
=337 \\ $a непосредственный
=490 0\ $a Бестселлеры O'Reilly
=500 \\ $a Фактическая дата выхода в свет - 2019
=534 \\ $p Пер.: $a Plas, Jake Vander $t Python data science handbook $c Beijing [etc.] : O'Reilly, cop. 2017 $z 978-1491912058
=650 \7 $a Техника. Технические науки -- Энергетика. Радиоэлектроника -- Радиоэлектроника -- Вычислительная техника -- Вычислительные машины электронные цифровые -- Программирование -- Языки программирования -- Python $2 rubbk
=852 \\ $a РГБ $b FB $j 3 19-60/157 $x 90
=852 7\ $a РГБ $b CZ2 $h З973.2-018/П37 $x 83
=852 \\ $a РГБ $b FB $j 3 20-32/18 $x 90
=852 \\ $a РГБ $b ORF $x 82
metadata comments
Пер.: Plas, Jake Vander Python data science handbook Beijing [etc.]: O'Reilly 978-1491912058
metadata comments
Russian State Library [rgb] MARC:
=001 009883865
=005 20190214131403.0
=008 190211s2018\\\\ru\\\\\\\\\\\\000\|\rus|d
=017 \\ $a КН-П-19-007117 $b RuMoRKP
=020 \\ $a 978-5-4461-0914-2
=040 \\ $a RuMoRGB $b rus $e rcr
=041 1\ $a rus $h eng
=044 \\ $a ru
=084 \\ $a З973.2-018.19Python,0 $2 rubbk
=100 1\ $a Плас, Джейк Вандер
=245 00 $a Python для сложных задач: наука о данных и машинное обучение $h [Текст] $c Дж. Вандер Плас ; [перевела с английского И. Пальти]
=260 \\ $a Санкт-Петербург [и др.] $b Питер $c 2018
=300 \\ $a 572, [1] с. $b ил., табл. $c 23 см
=336 \\ $a текст (text) $b txt $2 rdacontent
=337 \\ $a неопосредованный (unmediated) $b n $2 rdamedia
=338 \\ $a том (volume) $b nc $2 rdacarrier
=490 0\ $a Бестселлеры O'Reilly
=534 \\ $p Пер.: $a Plas, Jake Vander $t Python data science handbook $c Beijing [etc.]: O'Reilly $z 978-1491912058
=650 \7 $a Вычислительная техника -- Вычислительные машины электронные цифровые -- Программирование -- Языки программирования -- Python $2 rubbk
=852 \\ $a РГБ $b FB $j 3 19-6/167 $x 90
=852 \\ $a РГБ $b ORF $x 82
Alternative description
For Many Researchers, Python Is A First-class 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 All—ipython, Numpy, Pandas, Matplotlib, Scikit-learn, 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 Day-to-day 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 Must-have Reference For Scientific Computing In Python.-- Ipython: Beyond Normal Python -- Introduction To Numpy -- Data Manipulation With Pandas -- Visualization With Matplatlib -- Machine Learning. Jake Vanderplas. Includes Index.
Alternative description
**Revision History**
December 2016: First Edition
2016-11-17: First Release
date open sourced
2020-07-26
Read more…

🚀 Fast downloads

Become a member to support the long-term preservation of books, papers, and more. To show our gratitude for your support, you get fast downloads. ❤️

🐢 Slow downloads

From trusted partners. More information in the FAQ. (might require browser verification — unlimited downloads!)

All download options have the same file, and should be safe to use. That said, always be cautious when downloading files from the internet, especially from sites external to Anna’s Archive. For example, be sure to keep your devices updated.
show external downloads
  • For large files, we recommend using a download manager to prevent interruptions.
    Recommended download managers: Motrix
  • You will need an ebook or PDF reader to open the file, depending on the file format.
    Recommended ebook readers: Anna’s Archive online viewer, ReadEra, and Calibre
  • Use online tools to convert between formats.
    Recommended conversion tools: CloudConvert and PrintFriendly
  • You can send both PDF and EPUB files to your Kindle or Kobo eReader.
    Recommended tools: Amazon‘s “Send to Kindle” and djazz‘s “Send to Kobo/Kindle”
  • Support authors and libraries
    ✍️ If you like this and can afford it, consider buying the original, or supporting the authors directly.
    📚 If this is available at your local library, consider borrowing it for free there.