Python for data analysis / Wes McKinney.
By: McKinney, Wes.
Material type:
TextPublisher: NEW DELHI O'Reilly, c2013Description: xiii, 447 p. : ill. ; 24 cm.ISBN: 9789351100065; 1449319793 (pbk.).Subject(s): Python (Computer program language) | Programming languages (Electronic computers) | Data miningDDC classification: 005.13/3 | Item type | Current location | Collection | Call number | Status | Notes | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Books
|
Symbiosis Centre for Information Technology ISSUABLE | Non-fiction | 005.13/3 (Browse shelf) | Available | 3603 DT 11-9-2017 | SCIT-B-10231 | |
|
Books
|
Symbiosis Centre for Information Technology ISSUABLE | Non-fiction | 005.13/3 (Browse shelf) | Checked out | 3603 DT 11-9-2017 | 01/07/2019 | SCIT-B-10232 |
|
Books
|
Symbiosis Centre for Information Technology ISSUABLE | Non-fiction | 005.13/3 (Browse shelf) | Available | 3603 DT 11-9-2017 | SCIT-B-10233 | |
|
Books
|
Symbiosis Centre for Information Technology ISSUABLE | Non-fiction | 005.13/3 (Browse shelf) | Available | 3603 DT 11-9-2017 | SCIT-B-10234 | |
|
Books
|
Symbiosis Centre for Information Technology ISSUABLE | Non-fiction | 005.13/3 (Browse shelf) | Available | 3603 DT 11-9-2017 | SCIT-B-10235 |
Browsing Symbiosis Centre for Information Technology Shelves , Shelving location: ISSUABLE , Collection code: Non-fiction Close shelf browser
|
|
|
|
No cover image available | No cover image available | No cover image available | ||
| 005.13/3 Python for data analysis / | 005.13/3 Python for data analysis / | 005.13/3 Python for data analysis / | 005.13/3 Python for data analysis / | 005.133 Introducing Python : | 005.133 Introducing Python : | 005.133 Introducing Python : |
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 for this item.