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Ultimate Python Libraries for Data Analysis and Visualization: Leverage Pandas, NumPy, Matplotlib, Seaborn, Julius AI and No-Code Tools for Data ...
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COP 224258
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Unlock the full potential of Python for extracting insights from data using Pandas, NumPy, Matplotlib, Seaborn, and Julius AI.
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- Test your Data Analysis skills to its fullest using Python and other no-code toolsBook DescriptionUltimate Python Libraries for Data Analysis and Visualization is your comprehensive guide to mastering the intricacies of data analysis and visualization using Python. This book serves as your roadmap to unlocking the full potential of Python for extracting insights from data using Pandas, NumPy, Matplotlib, Seaborn, and Julius AI. Starting with the fundamentals of data acquisition, you'll learn essential techniques for gathering and preparing data for analysis. From there, you’ll dive into exploratory data analysis, uncovering patterns and relationships hidden within your datasets.Through step-by-step tutorials, you'll gain proficiency in statistical analysis, time series forecasting, and signal processing, equipping you with the tools to extract actionable insights from any dataset. What sets this book apart is its emphasis on real-world applications. With a series of hands-on projects, you’ll apply your newfound skills to analyze diverse datasets spanning industries such as finance, healthcare, e-commerce, and more.By the end of the book, you'll have the confidence and expertise to tackle any data analysis challenge with Python. To aid your journey, the book includes a handy Python cheat sheet in the appendix, serving as a quick reference guide for common functions and syntax.Table of Contents1. Introduction to Data Analysis and Data Visualization using Python2. Data Acquisition3. Data Cleaning and Preparation4. Exploratory Data Analysis5. Statistical Analysis6. Time Series Analysis and Forecasting7. Signal Processing8. Analyzing Real-World Data Sets using PythonAPPENDIX A Python Cheat SheetIndex
| Publisher | Orange Education Pvt Ltd |
| Publication date | 4 April 2024 |
| Language | English |
| Print length | 267 pages |
| ISBN-10 | 8197081913 |
| ISBN-13 | 978-8197081910 |
| Item weight | 463 g |
| Dimensions | 19.05 x 1.55 x 23.5 cm |
| Book 2 of 2 | Data Analyst (Python) — Expert Micro Path |
Who Should Buy?
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Data Analysts
Ideal for data analysts needing comprehensive tools for manipulating datasets and generating insightful visualizations.
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Data Science Students
Perfect for students learning data science who want practical guidance on applying popular Python libraries.
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No-Code Enthusiasts
Great for users interested in data analysis without coding experience, offering no-code tools and clear instructions.
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Absolute Beginners
Not suitable for complete beginners to programming who lack foundational knowledge of Python and libraries.
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Data Mining Editorial Review
Ultimate Python Libraries For Data Analysis And Visualization Leverage Pandas, NumPy, Matplotlib, Seaborn, Julius AI And No-Code Tools For Data ... Data Analyst Python Expert Micro Path is an essential read for aspiring data analysts. This 267-page book delves into powerful libraries like Pandas and NumPy, providing practical insights that can enhance both data analysis and visualization skills. Ideal for those venturing into the data field, it offers a comprehensive learning path. The clear language and well-structured content cater to both beginners and experienced professionals. Readers have appreciated its engaging layout and the step-by-step guidance that makes complex topics more digestible. Overall, it serves as a valuable resource for mastering data tools.
Customer Reviews & Ratings
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5 estrella
74%
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4 estrella
8%
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3 estrella
12%
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2 estrella
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1 estrella
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ventajas
- Thorough guide to data libraries
- Easy to understand for beginners
- Practical insights into data visualization
- Well-structured content for learning
- Engaging layout enhances user experience
Contras
- May require prior knowledge of Python basics
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COP 224258
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características y beneficios
- Master data analysis and visualization with Python.
- Comprehensive guide covering popular libraries like Pandas and NumPy.
- Step-by-step tutorials for statistical analysis and time series forecasting.
- Hands-on projects for analyzing real-world datasets across various industries.
- Includes a Python cheat sheet for quick reference.
- Gain confidence to tackle any data analysis challenge.
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