Amazon cover image
Image from Amazon.com

Python for data analysis / Wes McKinney.

By: Material type: TextTextPublication details: NEW DELHI O'Reilly, c2013.Description: xiii, 447 p. : ill. ; 24 cmISBN:
  • 9789351100065
  • 1449319793 (pbk.)
Subject(s): DDC classification:
  • 005.13/3 23
LOC classification:
  • QA76.73.P98 M42 2013
Contents:
Preliminaries -- Introductory examples -- IPython : an interactive computing and development environment -- NumPy basics : arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data wrangling : clean, transform, merge, reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Financial and economic data applications -- Advancded NumPy.
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Item type Current library Collection Call number Status Notes Date due Barcode
Books Books Symbiosis Centre for Information Technology ISSUABLE  Non-fiction 005.13/3 (Browse shelf(Opens below)) Available 3603 DT 11-9-2017 SCIT-B-10231
Books Books Symbiosis Centre for Information Technology ISSUABLE  Non-fiction 005.13/3 (Browse shelf(Opens below)) Available 3603 DT 11-9-2017 SCIT-B-10232
Books Books Symbiosis Centre for Information Technology ISSUABLE  Non-fiction 005.13/3 (Browse shelf(Opens below)) Available 3603 DT 11-9-2017 SCIT-B-10233
Books Books Symbiosis Centre for Information Technology ISSUABLE  Non-fiction 005.13/3 (Browse shelf(Opens below)) Available 3603 DT 11-9-2017 SCIT-B-10234
Books Books Symbiosis Centre for Information Technology ISSUABLE  Non-fiction 005.13/3 (Browse shelf(Opens below)) Available 3603 DT 11-9-2017 SCIT-B-10235

Includes index.

Preliminaries -- Introductory examples -- IPython : an interactive computing and development environment -- NumPy basics : arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data wrangling : clean, transform, merge, reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Financial and economic data applications -- Advancded NumPy.

There are no comments on this title.

to post a comment.