🔢 NumPy

# pip install numpy
import numpy as np

# From list
arr = np.array([1, 2, 3, 4, 5])
print(arr)  # [1 2 3 4 5]

# 2D array (matrix)
matrix = np.array([[1, 2, 3], [4, 5, 6]])
print(matrix.shape)  # (2, 3)

# Special arrays
zeros = np.zeros((3, 3))      # 3x3 array of zeros
ones = np.ones((2, 4))        # 2x4 array of ones
identity = np.eye(3)          # 3x3 identity matrix
random = np.random.rand(3, 3) # 3x3 random values [0,1)

# Range arrays
arange = np.arange(0, 10, 2)  # [0, 2, 4, 6, 8]
linspace = np.linspace(0, 1, 5)  # 5 evenly spaced values

# Element-wise operations
arr = np.array([1, 2, 3, 4])
print(arr + 10)    # [11 12 13 14]
print(arr * 2)     # [2 4 6 8]
print(arr ** 2)    # [1 4 9 16]

# Array arithmetic
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
print(a + b)       # [5 7 9]
print(a * b)       # [4 10 18]

# Aggregation functions
arr = np.array([1, 2, 3, 4, 5])
print(arr.sum())   # 15
print(arr.mean())  # 3.0
print(arr.std())   # 1.414...
print(arr.max())   # 5
print(arr.min())   # 1

# Matrix operations
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
print(A @ B)       # Matrix multiplication
print(A.T)         # Transpose

arr = np.array([10, 20, 30, 40, 50])

# Indexing
print(arr[0])      # 10
print(arr[-1])     # 50

# Slicing
print(arr[1:4])    # [20 30 40]
print(arr[:3])     # [10 20 30]

# Boolean indexing
print(arr[arr > 25])  # [30 40 50]

# 2D indexing
matrix = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print(matrix[0, 1])    # 2
print(matrix[:, 1])    # [2 5 8] (column)
print(matrix[1, :])    # [4 5 6] (row)