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Item #:
80102539
python for data analisys: python for data analysis: the python crash course comprehensive the programming from the ground up to python (Paperback)
Item #:
80102539
XAF 17226
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What Stands Out
Comprehensive Guide
This book offers a thorough introduction to Python, guiding readers from basic programming concepts to advanced data analysis techniques, making it ideal for beginners and those looking to deepen their knowledge.
Practical Applications
Focuses on hands-on examples and real-world applications, allowing readers to apply Python skills directly to data analysis tasks, enhancing learning through practical experience and projects.
User-Friendly Format
Designed with clarity in mind, the paperback format ensures easy navigation through concepts and examples, benefiting visual learners who prefer a tangible resource over digital formats.
Product Details
- Python for Data Analysis will explore many areas of Python and how different functions work and how it all correlates to python. We will also supply you with many examples by using graphs and charts.In chapter 1 we begin by giving you an overview of the different Python libraries. We also give a brief description; explain why they are popular, and what their functions are.In chapter 2 we discuss the Panda library and give a rundown of its basics and why it is one of the more popular libraries and most commonly used today.In chapter 3 we dive into the retrieving, processing, and storing of the data that is utilized in Python.Chapter 4 explores data visualizations and the use of charts and graphs to assist in visualizing the data that is generated through Python.With chapter 5 you will become familiar with working with the databases that Python supports. A few examples of these include SQL, API, and SQLite.Chapter 6 will cover predictive analytics and machine learning. It will describe the way machine learning and predictive analytics plays a role in Python and how Python can help to advance machine learning.Finally, in chapter 7, we see Python's involvement with time series and signal processing. You will have several graphs available that allows you to see the data at work.As the chapters will show you, Python for Data Analysis is a great way to get a huge amount of information in a hurry. It is beautifully detailed, and gives you a nice amount of visuals that help you to understand the information that is presented in the chapter. So no matter if you are just beginning in Python or need to learn it in a hurry, Python for Data Analysis is sure to provide you with what you need.
| 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.
-
Data Enthusiasts
Perfect for data enthusiasts interested in exploring data manipulation, visualization, and analysis using Python libraries.
-
Students & Learners
Beneficial for students studying data science or computer science who need a comprehensive introduction to Python.
-
Advanced Users
Not suitable for experienced Python developers seeking advanced techniques or specialized data analysis methodologies.
-
Professionals in Fields
May not meet the needs of professionals looking for in-depth data strategies or industry-specific applications.
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Non-Technical Individuals
Not recommended for those with no programming background, as it might be too technical and complex to grasp.
Product Description
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Customer Questions & Answers
-
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.
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XAF 17226
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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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