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#364: Symbolic Math with Python using SymPy

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Manage episode 327818969 series 2497444
Content provided by Talk Python To Me Podcast and Michael Kennedy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Talk Python To Me Podcast and Michael Kennedy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
We're all familiar with the data science tools like numpy, pandas, and others. These are numerical tools working with floating point numbers, often to represent real-world systems. But what if you exactly specify the equations, symbolically like many of us did back in Calculus and Differential Equations courses? With SymPy, you can do exactly that. Create equations, integrate, differentiate, and solve them. Then you can convert those solutions into Python (or even C++ and Fortran code). We're here with two of the core maintainer: Ondřej Čertík and Aaron Meurer to learn all about SymPy. Full episode page over at https://talkpython.fm/episodes/show/364/symbolic-math-with-python-using-sympy
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636 episodes

Artwork
iconShare
 
Manage episode 327818969 series 2497444
Content provided by Talk Python To Me Podcast and Michael Kennedy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Talk Python To Me Podcast and Michael Kennedy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
We're all familiar with the data science tools like numpy, pandas, and others. These are numerical tools working with floating point numbers, often to represent real-world systems. But what if you exactly specify the equations, symbolically like many of us did back in Calculus and Differential Equations courses? With SymPy, you can do exactly that. Create equations, integrate, differentiate, and solve them. Then you can convert those solutions into Python (or even C++ and Fortran code). We're here with two of the core maintainer: Ondřej Čertík and Aaron Meurer to learn all about SymPy. Full episode page over at https://talkpython.fm/episodes/show/364/symbolic-math-with-python-using-sympy
  continue reading

636 episodes

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