Suggestions for books about scientific computing using Python

In summary, the conversation is about a person looking for suggestions on books or other learning materials that will help them improve their skills using Python for scientific computing. They are comfortable with Python programming but not an expert, and are specifically looking for a book that includes Python routines. They mention owning a copy of Numerical Recipes but prefer a book with Python code. One suggestion is Computational Physics with Python, which returns 815,000 results in a Google search.
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GoldenBear
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Looking for suggestions on books (or other learning material) that will help me improve my skills using Python for scientific computing. I am comfortable with Python programming (syntax, conditional statements, loops, etc.), and use it for data analysis in my undergraduate experimental physics courses, but I am not an expert.

I own a copy of Numerical Recipes which is written using C++ (which I haven’t learned yet) and from what I understand the material is transferable to other languages, but I would prefer a book that has Python routines in it as I am comfortable with the syntax and believe seeing the material being applied using Python code would make learning the material easier. Any suggestions are greatly appreciated!
 
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1. What is scientific computing and how is it related to Python?

Scientific computing is the use of computers to solve complex scientific problems. It involves using algorithms, mathematical models, and programming languages to analyze and interpret scientific data. Python is a popular programming language for scientific computing because of its ease of use, powerful libraries, and ability to handle large amounts of data.

2. What are some recommended books for learning scientific computing with Python?

Some highly recommended books for learning scientific computing with Python include "Python for Data Analysis" by Wes McKinney, "Think Python: How to Think Like a Computer Scientist" by Allen B. Downey, and "Python for Scientists and Engineers" by Shane J. Grigsby. These books cover a range of topics from data analysis to scientific programming and are suitable for beginners as well as experienced programmers.

3. Are there any free online resources for learning scientific computing with Python?

Yes, there are many free online resources available for learning scientific computing with Python. Some popular ones include the official Python documentation, tutorials on websites like Real Python and DataCamp, and YouTube channels such as Sentdex and Corey Schafer that offer free video tutorials on scientific computing with Python.

4. How important is it to have a background in mathematics for learning scientific computing with Python?

Having a good understanding of mathematics is important for learning scientific computing with Python. Many scientific problems involve complex mathematical concepts and having a solid foundation in mathematics can help with understanding and implementing algorithms and models in Python. However, there are also resources available to help beginners with little or no background in mathematics to learn scientific computing with Python.

5. Are there any specific applications of scientific computing with Python?

Yes, there are many applications of scientific computing with Python in various fields such as physics, biology, chemistry, and data science. Some examples include data analysis and visualization, simulation of physical systems, machine learning, and image processing. Python's versatility and extensive libraries make it a powerful tool for various scientific applications.

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