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47178583
Data Science for Marketing Analytics: A practical guide to forming a killer marketing strategy through data analysis with Python, 2nd Edition
89% of respondents would recommend this to a friend
Nº de artículo:
47178583
CLP 59244
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What Stands Out
Practical Approach
This edition emphasizes hands-on techniques, allowing readers to apply data analysis using Python directly to formulate effective marketing strategies.
Updated Content
Incorporating the latest trends and tools in data science, this edition provides insights that help marketers stay ahead in the competitive landscape.
Beginner Friendly
The book is designed for those new to data science, making complex concepts accessible and actionable for marketers looking to enhance their analytical skills.
Detalles de producto
| Publisher | Packt Publishing |
| Publication date | September 7, 2021 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 636 pages |
| ISBN-10 | 1800560478 |
| ISBN-13 | 978-1800560475 |
| Item Weight | 2.37 pounds (1.08 kg) |
| Dimensions | 7.5 x 1.44 x 9.25 inches (19.1 x 3.7 x 23.5 cm) |
Who Should Buy?
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Marketing Professionals
Ideal for marketers looking to enhance their strategies and utilize data analysis for effective decision-making.
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Data Analysts
Great for data analysts wanting to apply their technical skills to marketing analytics and strategy development.
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Business Students
Suitable for business students focusing on marketing, providing practical insights into data-driven strategy formulation.
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Complete Beginners
Not suitable for individuals with no prior knowledge of data analysis or programming concepts in Python.
DESCRIPCIÓN DEL PRODUCTO
Data Science for Marketing Analytics: A practical guide to forming a killer marketing strategy through data analysis with Python, 2nd Edition
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Python Editorial Review
The book on business analysis using Pandas in Python has received mixed reviews from customers. While some users praise its intuitive and easy-to-understand principles, labeling it as one of the best Python books they've read, others have found it lacking in depth when it comes to specific topics such as marketing or customer analytics. One user, in particular, mentioned that the book mainly Consists of simple tasks without providing much insight or in-depth analysis into the field. Overall, the book seems to be a good starting point for those looking to learn about business analysis using Pandas in Python, but it may not be comprehensive enough for those seeking a deeper dive into marketing or customer analytics. **
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ventajas
- Intuitive and easy-to-understand principles
- Great introduction to Pandas in Python for business analysis
Contras
- Lacks depth in specific topics like marketing or customer analytics
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CLP 59244
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