NumPy — Array Slicing

Key attributes

import numpy as np

arr = np.array([[1, 2, 3], [4, 5, 6]])

print(f"Shape: {arr.shape}")      # (2, 3)
print(f"Size: {arr.size}")        # 6
print(f"Ndim: {arr.ndim}")        # 2
print(f"Dtype: {arr.dtype}")      # int64
print(f"Itemsize: {arr.itemsize}") # 8 bytes

reshape

arr = np.array([1, 2, 3, 4, 5, 6])
reshaped = arr.reshape(2, 3)
print(reshaped)

flatten

arr_2d = np.array([[1, 2], [3, 4]])
flat = arr_2d.flatten()
print(flat)  # [1, 2, 3, 4]

T (transpose)

arr = np.array([[1, 2], [3, 4]])
print(arr.T)

dtype

arr = np.array([1, 2, 3], dtype=np.float32)
print(arr.dtype)  # float32

Mini Practice

1. Check shape and size
2. Reshape arrays
3. Transpose matrices
4. Work with dtypes

Up Next

Continue with Indexing - Accessing elements.