A Python Data Analyst’s Toolkit:... by Rajagopalan, Gayathr Paperback / softback
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Product Details
| ISBN | 1484263987 |
| EAN | 9781484263983 |
| Release Title | A Python Data Analystu2019s Toolkit: Learn Python and Python-based... |
| Artist | Rajagopalan, Gayathri |
| Brand | N/A |
| Colour | N/A |
| Book Title | A Python Data Analystu2019s Toolkit: Learn Python and Python-based... |
| Subject Area | Mathematics, Computers |
| Publication Name | Python Data Analyst's Toolkit : Learn Python and Python-Based Libraries with Applications in Data Analysis and Statistics |
| Publisher | Apress L. P. |
| Item Length | 10 in (25.4 cm) |
| Subject | Probability & Statistics / General, General, Databases / General, Programming Languages / Python |
| Publication Year | 2020 |
| Type | Textbook |
| Format | Trade Paperback |
| Language | English |
| Author | Gayathri Rajagopalan |
| Item Weight | 28 Oz (793.8 grams) |
| Item Width | 7 in (17.8 cm) |
| Number of Pages | Xx, 399 Pages |
| Country of Origin | India |
| What is in the box | A Python Data Analyst&rsquo... For more details, please check description/product details |
Who Should Buy?
-
Beginner Analysts
Ideal for those new to data analysis, providing foundational Python skills and practical applications in data handling.
-
Data Science Students
Perfect for university students studying data science, offering insights into Python tools and techniques relevant to coursework.
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Professionals Upskilling
Great for working professionals looking to enhance their data analytics skills and productivity through Python programming.
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Advanced Analysts
Not suitable for experienced data analysts who may seek more advanced or specialized topics beyond basic Python techniques.
Product Description
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n/a Editorial Review
A Python Data Analyst’s Toolkit: Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics by Gayathri Rajagopalan is a comprehensive resource designed for those eager to delve into data analysis using Python. This textbook covers essential topics in mathematics and programming, making it suitable for learners in the fields of probability and statistics. With 399 pages of detailed content, the book is structured to gradually build your skills in Python and its libraries, allowing for practical applications in data tasks. The engaging writing style and thorough explanations make it ideal for both beginners and intermediates. Questions like what you can achieve using Python for data analysis can easily be answered as you navigate through the toolkit presented within.
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Pros
- Comprehensive coverage of data analysis techniques
- Practical applications using Python libraries
- Suitable for both beginners and intermediates
- Engaging writing style for easy understanding
- Structured learning path through 399 pages
Cons
- Could benefit from more visual aids or diagrams
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