NumPy (Numerical Python) is the foundation of all scientific Python. It makes working with large arrays of numbers incredibly fast.

Python lists are flexible but slow. NumPy arrays are:
• 100–1000x faster for math operations
• Can do math on the whole array at once
• Used by scipy, matplotlib, pandas — everything NMA uses

import numpy as np  # always import numpy as np

# Create an array of 1000 time steps (0 to 999 ms)
t = np.arange(0, 1000)  # [0, 1, 2, ..., 999]

# Create an array of 100 neurons, all at rest (-70 mV)
V = np.full(100, -70.0)  # [-70. -70. -70. ... -70.]

print(t.shape)   # (1000,) — 1000 elements
print(V.shape)   # (100,)  — 100 elements

NMA fact: Every tutorial starts with 'import numpy as np'. You'll type this thousands of times.