python for data analisys: python for data analysis: the python crash course comprehensive the programming from the ground up to python Paperback
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Python for Data Analysis is a great way to get a huge amount of information in a hurry
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What Stands Out
Product Details
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | October, 2020 |
| Pages | 220 |
| Edition | Standard Edition |
| Publisher | Frank |
| Original languages | English |
| Language | English |
| Assembled product height | 1.5 in (3.8 cm) |
| Assembled product weight | 0.66 lb (300 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Beginner Programmers
Ideal for beginners wanting to learn Python basics and data analysis concepts from scratch with structured guidance.
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Data Enthusiasts
Perfect for data enthusiasts interested in exploring data manipulation, visualization, and analysis using Python libraries.
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Students & Learners
Beneficial for students studying data science or computer science who need a comprehensive introduction to Python.
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Advanced Users
Not suitable for experienced Python developers seeking advanced techniques or specialized data analysis methodologies.
Product Description
python for data analisys: python for data analysis: the python crash course comprehensive the programming from the ground up to python Paperback
Customer Questions & Answers
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Question:
Is this book suitable for beginners?
Answer: Yes, the book is suitable for beginners as well as those who need to learn Python quickly. -
Question:
What topics does the book cover?
Answer: The book covers Python libraries, data retrieval and processing, data visualizations, working with databases, predictive analytics, machine learning, and time series and signal processing. -
Question:
Are there visual examples in the book?
Answer: Yes, the book includes many examples using graphs and charts to help visualize the data.
Jason Cannon All Books Editorial Review
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BMD 30
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Features & Benefits
- Comprehensive guide to Python for data analysis
- Explores different Python libraries and their functions
- Discusses data retrieval, processing, and storage
- Covers data visualizations and working with databases
- Includes chapters on predictive analytics and machine learning
- Involves time series and signal processing
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