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Artikal br.:
62606761
Python for Data Analysis: Data Wrangling with Pandas, Numpy, and Jupyter, (Paperback)
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Artikal br.:
62606761
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Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python.
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What Stands Out
Comprehensive Guide
This book offers an in-depth exploration of data analysis techniques using Python, making it ideal for beginners and professionals looking to enhance their skills.
Practical Examples
With hands-on tutorials that utilize Pandas, Numpy, and Jupyter, readers gain practical experience, facilitating easier application of concepts in real-world data scenarios.
User-Friendly Approach
The clear and structured layout empowers readers without requiring extensive prior knowledge, ensuring they can effectively learn and apply data wrangling skills.
Detalji o proizvodu
- Updated handbook for manipulating, processing, and crunching datasets in Python
- Includes practical case studies to solve data analysis problems effectively
- Covers the latest versions of pandas, NumPy, and Jupyter
- Written by Wes McKinney, the creator of the Python pandas project
- Ideal for analysts new to Python and Python programmers new to data science
- Provides data files and related material on GitHub for practical application
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | September, 2022 |
| Pages | 579 |
| Reading level | General |
| Subgenre | Data Science |
| Series title | No Series |
| Edition | 3rd Edition |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Editor | Fu-Chan Wei |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 9.10 x 1.20 x 6.90 in (23.1 x 3 x 17.5 cm) |
| Assembled product weight | 2.07 lb (940 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Data Analysts
Ideal for professionals looking to enhance their data manipulation skills with practical examples and exercises.
-
Students
Perfect for university students studying data science or analytics seeking foundational knowledge in Python libraries.
-
Self-learners
Great for individuals eager to learn data analysis independently, offering hands-on tutorials and comprehensive explanations.
-
Complete Beginners
Not suitable for those without prior programming knowledge, as some foundational concepts may be challenging.
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Karakteristike i prednosti
- Updated for Python 3.10 and pandas 1.4
- Packed with practical case studies
- Ideal for analysts new to Python and for Python programmers new to data science
- Learn basic and advanced features in NumPy
- Create informative visualizations with matplotlib
- Solve real-world data analysis problems with thorough, detailed examples
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