MARC details
| 000 -LEADER |
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| fixed length control field |
04964cam a2200337M 4500 |
| 001 - CONTROL NUMBER |
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| control field |
a46449575 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
SIRSI |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250807142529.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION |
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| fixed length control field |
m o d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
240725s2024 xx o 0|| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781032572239 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
YDX |
| Language of cataloging |
eng |
| Transcribing agency |
YDX |
| Modifying agency |
TYFRS |
| -- |
OCLCO |
| -- |
TYFRS |
| -- |
OCLCO |
| -- |
N$T |
| -- |
UKAHL |
| -- |
YT1 |
| -- |
EG-NcFUE |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
519.50285 T.T.D |
| Edition number |
23 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Timbers, Tiffany |
| Relator term |
author. |
| 9 (RLIN) |
34115 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Data Science |
| Remainder of title |
a first introduction with python / |
| Statement of responsibility, etc |
Tiffany Timbers ; Trevor Campbell, Melissa Lee, Lindesy Heagy. |
| 264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Boca Raton : |
| Name of publisher, distributor, etc |
CRC, |
| Date of publication, distribution, etc |
2025. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiii, xv, xvii, xix, 431 Pages : |
| Other physical details |
Illustration ; |
| Dimensions |
24 cm |
| 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 |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Data Science Series. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. It emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. Based on educational research and active learning principles, the book uses a modern approach to Python and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The text will leave readers well-prepared for data science projects. It is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates at the University of British Columbia. Key Features: Includes autograded worksheets for interactive, self-directed learning. Introduces readers to modern data analysis and workflow tools such as Jupyter notebooks and GitHub, and covers cutting-edge data analysis and manipulation Python libraries such as pandas, scikit-learn, and altair. Is designed for a broad audience of learners from all backgrounds and disciplines. |
| 545 0# - BIOGRAPHICAL OR HISTORICAL DATA |
|---|
| Biographical or historical note |
Tiffany Timbers is an Associate Professor of Teaching in the Department of Statistics and Co-Director for the Master of Data Science program (Vancouver Option) at the University of British Columbia. In these roles she teaches and develops curriculum around the responsible application of Data Science to solve real-world problems. One of her favourite courses she teaches is a graduate course on collaborative software development, which focuses on teaching how to create R and Python packages using modern tools and workflows. Trevor Campbell is an Associate Professor in the Department of Statistics at the University of British Columbia. His research focuses on automated, scalable Bayesian inference algorithms, Bayesian nonparametrics, streaming data, and Bayesian theory. He was previously a postdoctoral associate in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and Institute for Data, Systems, and Society (IDSS) at MIT and a Ph.D. candidate in the Laboratory for Information and Decision Systems (LIDS) at MIT. Melissa Lee is an Assistant Professor of Teaching in the Department of Statistics at the University of British Columbia. She teaches and develops curriculum for undergraduate statistics and data science courses. Her work focuses on student-centered approaches to teaching, developing and assessing open educational resources, and promoting equity, diversity, and inclusion initiatives. Joel Ostblom is an Assistant Professor of Teaching in the Statistics Department at the University of British Columbia. He teaches and develops data science courses at the graduate and undergraduate level, with a focus on data visualization, data science ethics, and machine learning. Joel cares deeply about spreading data literacy and excitement over programmatic data analysis, which is reflected in his contributions to open source projects and openly accessible data science learning resources. Lindsey Heagy is an Assistant Professor in the Department of Earth, Ocean and Atmospheric Sciences and Director of the Geophysical Inversion Facility at UBC. Her research combines computational methods in numerical simulations, inversions, and machine learning for using geophysical data to characterize the subsurface. Primary applications of interest include mineral exploration, carbon sequestration, groundwater, and environmental studies. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Mathematical statistics |
| General subdivision |
Data processing |
| Form subdivision |
Textbooks. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
R (Computer program language) |
| Form subdivision |
Textbooks. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Quantitative research |
| General subdivision |
Data processing |
| Form subdivision |
Textbooks. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
MATHEMATICS / Probability & Statistics / General. |
| Source of heading or term |
bisacsh |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="https://ezaccess.libraries.psu.edu/login?url=https://www.taylorfrancis.com/books/9781003438397">https://ezaccess.libraries.psu.edu/login?url=https://www.taylorfrancis.com/books/9781003438397</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |