Python Fundamentals for Data Analytics Dr Chandrika M, Dr Pavithra B Shetty
- Autorzy:
- Dr Chandrika M, Dr Pavithra B Shetty
- Wydawnictwo:
- BPB Publications
- Ocena:
- Stron:
- 276
- Dostępne formaty:
-
ePubMobi
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Python Fundamentals for Data Analytics
Description
Python is a simple, easy-to-learn, and one of the top programming languages across the globe. As a result of advancements in AI, data mining, and numerical computing fields, Python has become a popular programming language catering to various stakeholders. It is a powerful tool for working with a variety of data. This book provides the basics of Python and an introduction to data analytics.
This book offers a complete introduction to Python programming, covering everything from the basics to the advanced topics. It starts by explaining core concepts like syntax and the Python interpreter, then dives into data structures, control flow, functions, and modules. You will also learn about data analysis and visualization with popular libraries like NumPy, Pandas, Matplotlib, and Seaborn. It wraps up with practical case studies, showing how to apply Python in real-world scenarios effectively.
The book serves as a step-by-step guide to performing data analysis. Its content is designed so that even a novice can learn and perform data analysis and visualization simply by following the instructions in the book. Key Features
The book covers a wide range of topics, from Python fundamentals to advanced data analysis techniques.
It includes practical exercises and real-world case studies to illustrate the applications of Python for data analysis.
The book explains complex concepts in a clear and understandable manner. What you will learn
Understand the basics of programming languages and the role of the Python interpreter.
Read about different data structures like lists, sets, tuples, and dictionaries, and understand their applications.
Learn how to work with files in Python, including reading, writing, and appending data.
Discover how to use NumPy and Pandas for efficient data manipulation and analysis.
Learn how to create informative visualizations using Matplotlib and Seaborn. Who this book is for
This book is designed for students studying UG or PG courses in the computer science and applications domain. Learning Python is a simple way to begin the journey of data analytics. One of the in-demand domains in the job market, and research is data analytics. This book will be helpful for students interested in this domain. Table of Contents
1. Programming Languages and Python Interpreter
2. Python Fundamentals
3. Project Jupyter and JupyterLab Environment
4. Collection Types
5. Conditional Branching
6. Iterating Constructs
7. Functions and Methods
8. Modules
9. File Operations
10. Working with Data
11. Data Visualization
12. Case Studies
Appendix I: Abbreviations
Python is a simple, easy-to-learn, and one of the top programming languages across the globe. As a result of advancements in AI, data mining, and numerical computing fields, Python has become a popular programming language catering to various stakeholders. It is a powerful tool for working with a variety of data. This book provides the basics of Python and an introduction to data analytics.
This book offers a complete introduction to Python programming, covering everything from the basics to the advanced topics. It starts by explaining core concepts like syntax and the Python interpreter, then dives into data structures, control flow, functions, and modules. You will also learn about data analysis and visualization with popular libraries like NumPy, Pandas, Matplotlib, and Seaborn. It wraps up with practical case studies, showing how to apply Python in real-world scenarios effectively.
The book serves as a step-by-step guide to performing data analysis. Its content is designed so that even a novice can learn and perform data analysis and visualization simply by following the instructions in the book. Key Features
The book covers a wide range of topics, from Python fundamentals to advanced data analysis techniques.
It includes practical exercises and real-world case studies to illustrate the applications of Python for data analysis.
The book explains complex concepts in a clear and understandable manner. What you will learn
Understand the basics of programming languages and the role of the Python interpreter.
Read about different data structures like lists, sets, tuples, and dictionaries, and understand their applications.
Learn how to work with files in Python, including reading, writing, and appending data.
Discover how to use NumPy and Pandas for efficient data manipulation and analysis.
Learn how to create informative visualizations using Matplotlib and Seaborn. Who this book is for
This book is designed for students studying UG or PG courses in the computer science and applications domain. Learning Python is a simple way to begin the journey of data analytics. One of the in-demand domains in the job market, and research is data analytics. This book will be helpful for students interested in this domain. Table of Contents
1. Programming Languages and Python Interpreter
2. Python Fundamentals
3. Project Jupyter and JupyterLab Environment
4. Collection Types
5. Conditional Branching
6. Iterating Constructs
7. Functions and Methods
8. Modules
9. File Operations
10. Working with Data
11. Data Visualization
12. Case Studies
Appendix I: Abbreviations
Szczegóły książki
- ISBN Ebooka:
- 978-93-658-9231-4, 9789365892314
- Data wydania ebooka :
-
2024-12-18
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