Python data science handbook : (Record no. 13689)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03702cam a22002777i 4500 |
| 001 - CONTROL NUMBER | |
| control field | TB11237 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | IN-BhIIT |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240508171540.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 230831t20222023caua bf 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789355422552 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | IN-BhIIT |
| 041 ## - LANGUAGE CODE | |
| Language code of text | eng |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.312 |
| Book number | VAN/P |
| 100 1# - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Vanderplas,Jake |
| Relator term | Author. |
| 245 10 - TITLE STATEMENT | |
| Title | Python data science handbook : |
| Sub Title | essential tools for working with data / |
| Statement of responsibility, etc | by Jake VanderPlas. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2nd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Mumabi : |
| Name of publisher | O'Reilly, |
| Year of publication | 2022. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xvi, 529 p. : |
| Other physical details(ill.) | ill. ; |
| Dimensions(size) | 24 cm |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Part I: Jupyter: Beyond normal Python -- 1. Getting started in in IPython and Jupyter -- 2. Enhanced interactive features -- 3. Debugging and profiling -- Part II: Introduction to NumPy -- 4. Understanding data types in Python -- 5. The basics of NumPy arrays -- 6. Computation on NumPy arrays: Universal functions -- 7. Aggregations: min, max, and everything in between -- 8. Computation on arrays: broadcasting -- 9. Comparisons, masks, and boolean logic -- 10. Fancy indexing -- 11. Sorting arrays -- 12. Structured data: NumPy's structured arrays -- Part III: Data manipulation with Pandas -- 13. Introducing Pandas objects -- 14. Data indexing and selection -- 15. Operating on data in Pandas -- 16. Handling missing data -- 17. Hierarchial indexing -- 18. Combining datasets: concat and append -- 19. Combining datasets: merge and join -- 20. Aggregation and grouping -- 21. Pivot tables -- 22. Vectorized string operations -- 23. Working with time series -- 24. High-performace Pandas: eval and query -- Part IV: Visualization with Matplotlib -- 25. General Matplotlib tips -- 26. Simple line plots -- 27. Simple scatter plots -- 28. Density and contour plots -- 29. Customizing plot legends -- 30. Customizing colorbars -- 31. Multiple subplots -- 32. Text and annitatuin -- 33. Customizing ticks -- 34. Customizing Matplotlib: Configurations and stylesheets -- 35. Three-dimensional plottin in Matplotlib -- 36. Visualization with Seaborn -- Part V: Machine learning -- 37. What is machine learning? -- 38. Introducing Scitit-Learn -- 39. Hyperparameters and model validation -- 40. Feature engineering -- 41. In depth: Naive beyes classification -- 42. In depth: Linear regression -- 43> In depth: Support vector machines -- 44. In depth: Decision trees and random forests -- 45> In depth: Principal component analysis -- 46> In depth: Manifold learning -- 47. In depth: k-means clustering -- 48. In depth: Gaussian mixture models -- 49. In depth: Kernel density estimation -- 50. Application: a face detection pipeline. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "Python is a first-class tool for many researchers, primarily 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 new edition of 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 the second edition of 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."--Publisher marketing. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Data mining |
| Form subdivision | Handbooks, manuals, etc. |
| Topical Term | Python (Computer program language) |
| Form subdivision | Handbooks, manuals, etc. |
| Topical Term | Data mining. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Course Reserve |
| Koha issues (borrowed), all copies | 2 |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Home library | Current library | Date acquired | Source of acquisition | Cost, normal purchase price | Accession Number | Cost, replacement price | Price effective from | Koha item type | Full call number |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Not withdrawn | Not Lost | not damaged | SES | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | 16/01/2024 | 26 | 975.00 | TB11241 | 1250.00 | 16/01/2024 | Text Book | ||
| Not withdrawn | Not Lost | not damaged | SES | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | 16/01/2024 | 26 | 975.00 | TB11238 | 1250.00 | 16/01/2024 | Text Book | ||
| Not withdrawn | Not Lost | not damaged | SES | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | 16/01/2024 | 26 | 975.00 | TB11240 | 1250.00 | 16/01/2024 | Text Book | ||
| Not withdrawn | Not Lost | not damaged | SES | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | 16/01/2024 | 26 | 975.00 | TB11239 | 1250.00 | 16/01/2024 | Text Book | ||
| Not withdrawn | Not Lost | not damaged | SES | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | 16/01/2024 | 26 | 975.00 | TB11237 | 1250.00 | 16/01/2024 | Course Reserve | 006.312 VAN/P |