MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02916cam a2200397Mi 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OCoLC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20220901133549.0 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781491947821 |
| Qualifying information |
(e-book) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1491947829 |
| Qualifying information |
(e-book) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1491947853 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781491947852 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9781491947852 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
E7B |
| Language of cataloging |
eng |
| Description conventions |
rda |
| -- |
pn |
| Transcribing agency |
E7B |
| Modifying agency |
OCLCO |
| -- |
UMI |
| -- |
CUS |
| -- |
COO |
| -- |
DEBBG |
| -- |
OCLCF |
| -- |
OCLCQ |
| -- |
CEF |
| -- |
UAB |
| -- |
AU@ |
| -- |
UKAHL |
| -- |
CZL |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
Eng |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA76.9.D3 |
| Item number |
.J367 2015eb |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Janssens, Jeroen, |
| Relator term |
author |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Data science at the command line : |
| Remainder of title |
facing the future with time-tested tools / |
| Statement of responsibility, etc. |
Jeroen Janssens ; Mike Loukides, Ann Spencer, and Marie Beaugureau, editors ; Matthew Hacker, production editor ; Kiel Van Horn, copyeditor |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Sebastopol, California : |
| Name of producer, publisher, distributor, manufacturer |
O'Reilly, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2015 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
©2015 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 online resource (212 pages) : |
| Other physical details |
illustrations (some color) |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index |
| 506 ## - RESTRICTIONS ON ACCESS NOTE |
|---|
| Terms governing access |
Available to OhioLINK libraries |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data. To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools. Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on plain text, CSV, HTML/XML, and JSON Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow using Drake Create reusable tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines using GNU Parallel Model data with dimensionality reduction, clustering, regression, and classification algorithms |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Database management |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Spencer, Ann, |
| Relator term |
editor |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Beaugureau, Marie, |
| Relator term |
editor |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Hacker, Matthew, |
| Relator term |
editor |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Horn, Kiel Van, |
| Relator term |
editor |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Ohio Library and Information Network |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| Main entry heading |
Janssens, Jeroen. |
| Title |
Data science at the command line : facing the future with time-tested tools. |
| Place, publisher, and date of publication |
Sebastopol, California : O'Reilly, ©2015 |
| Physical description |
xvii, 191 pages |
| International Standard Book Number |
9781491947852 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Public note |
Connect to resource |
| Uniform Resource Identifier |
<a href="https://learning.oreilly.com/library/view/~/9781491947845/?ar">https://learning.oreilly.com/library/view/~/9781491947845/?ar</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Books |