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Hands-On Data Analysis with NumPy and pandas: Implement Python packages from data manipulation to processing
82% of respondents would recommend this to a friend
XAF 30998
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By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.
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What Stands Out
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| Publisher | Packt Publishing |
| Publication date | June 29, 2018 |
| Language | English |
| Print length | 168 pages |
| ISBN-10 | 1789530792 |
| ISBN-13 | 978-1789530797 |
| Item Weight | 10.5 ounces (297.68 grams) |
| Dimensions | 7.5 x 0.38 x 9.25 inches (19.1 x 1 x 23.5 cm) |
Who Should Buy?
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Data Analysts
Ideal for data analysts looking to enhance their skills in data manipulation and analysis using Python libraries.
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Beginners in Python
Great for beginners who want to learn data analysis with hands-on examples in Python, specifically using NumPy and Pandas.
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Machine Learning Enthusiasts
Beneficial for those interested in applying data analysis techniques to improve machine learning models and data preprocessing.
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Advanced Users
Experienced data scientists may find the content too basic and not challenging enough for their advanced needs.
KWATANCEN ABUN
Hands-On Data Analysis with NumPy and pandas: Implement Python packages from data manipulation to processing
Tambayoyi & Amsoshi Abokin Ciniki
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Tambaya:
Do I need prior experience in data analysis to use this book?
Amsa: No, this book is designed for those with no previous experience in data analysis. -
Tambaya:
What Python packages will I learn about?
Amsa: You will learn about the NumPy and pandas packages, essential for data analysis. -
Tambaya:
Is this book suitable for beginners?
Amsa: Yes, it's specifically tailored for beginner Python developers starting in data analysis.
Data Modeling & Design Editorial Review
Customer Reviews & Ratings
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XAF 30998
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Fasaloli & Fa'idoji
- Learn to set up a Python data analysis environment.
- Master the powerful NumPy package for advanced mathematical functions.
- Discover how to create and manipulate data arrays efficiently.
- Explore the pandas extension for effective data mining and subsetting.
- Understand hierarchical indexing and data plotting techniques.
- Ideal for Python developers venturing into data analysis without prior experience.
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