| Description |
1 online resource. |
| Series |
Pocket primer
|
|
Pocket primer.
|
| Summary |
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available. FEATURES: Includes a concise introduction to Python 3 and linear algebra; Provides a thorough introduction to data visualization and regular expressions; Covers NumPy, Pandas, R, and SQL; Introduces probability and statistical concepts; Features numerous code samples throughout; Companion files with source code and figures. |
| Contents |
1: Working with Data. -- 2: Introduction to Probability and Statistics. -- 3: Linear Algebra Concepts. -- 4: Introduction to Python. -- 5: Introduction to NumPy. -- 6: Introduction to Pandas. -- 7: Introduction to R. -- 8: Regular Expressions. -- 9: SQL and NoSQL. -- 10: Data Visualization. -- Index. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Databases.
|
|
Information retrieval.
|
|
Python (Computer program language)
|
|
information retrieval. |
|
Databases |
|
Information retrieval |
|
Python (Computer program language) |
| Other Form: |
Print version: Campesato, Oswald. Data science fundamentals. Dulles : Mercury Learning & Information, 2021 9781683927334 (OCoLC)1263811116 |
| ISBN |
9781683927310 (electronic bk.) |
|
1683927311 (electronic bk.) |
|
1683927338 |
|
9781683927334 |
|
