Table 1. Some useful Python libraries for numerical and scientific computing.

Module name	Description	Link
Pandas	For data analysis; supports objects like dataframes	https://pandas.pydata.org/
NumPy	For scientific computing; supports matrices and arrays	https://numpy.org/
SymPy	For symbolic maths; can also convert Python code into math notation	https://www.sympy.org/en/index.html
matplotlib	Produces publication-quality plots/graphs	https://matplotlib.org/
scikit-learn	A machine learning algorithm library	https://scikit-learn.org/stable/