how to change line color in a sympy plot within jupyter
Explore related questions graphing-functions python See similar questions with these tags.
How can I find which function corresponds to a set of data points?
Here is a Python Jupyter script for that purpose. If you can restrict yourself to polynomials, NumPy (a Python math library) will offer an easy solution: import numpy as np from numpy.polynomial …
Finding number of edges given vertices and degree sequence?
Feb 15, 2017 · See Handshaking Lemma and the degree sum formula (naming of these varies among authors).
python - Euler-Lagrange formalism with SymPy - Mathematics …
Nov 27, 2018 · Explore related questions euler-lagrange-equation python See similar questions with these tags.
Are there four whole numbers $a$, $b$, $m$, and $n$, where $a$, …
Dec 3, 2025 · I’m currently looking into differences of powers. I found that 3^2-2^3 is 1, 3^3-5^2 is 2, 2^7-5^3 is 3, etc. My python code didn’t find a solution for 6. In fact, 6 was the only number …
Does there exist a number such that the first 16 numbers of its …
Dec 1, 2025 · There seems to be an ambiguity with your use of "digits" and "numbers". In the title you say "the first 16 digits of its collatz sequence", do you actually mean "the first 16 …
Confusion about atan vs atan2 - Mathematics Stack Exchange
Feb 29, 2024 · Explore related questions limits trigonometry computational-mathematics python sagemath See similar questions with these tags.
Why is the FFT output divided by the data length?
Apr 26, 2024 · I am working with FFT using NumPy in Python, and I noticed that it's common to divide the output of the np.fft.fft function by the length of the data array. Here's a simplified …
Where to start learning about topological data analysis?
I know nothing about data analysis, but, in addition to general topology that you probably took, you would need some basic algebraic topology as well (simplicial complexes, homology, …
Machine Learning: Good book for learning Probability and …
0 Python for Probability, Statistics, and Machine Learning is focused on an intuitive grasp of these topics. Most of the book is available on github as IPython/Jupyter notebooks