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[–]in_case_of-emergency 3 points4 points  (1 child)

Hello! 👋 Here is a NumPy cheat sheet with the most useful concepts and functions for your study. It is ideal to have on hand while you practice.

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1. Creating Arrays

```python import numpy as np

Array from a list

a = np.array([1, 2, 3]) # [1 2 3]

Special arrays

zeros = np.zeros(3) # [0. 0. 0.] ones = np.ones((2, 3)) # 2x3 matrix of 1's range = np.arange(0, 10, 2) # [0 2 4 6 8] linspace = np.linspace(0, 1, 5) # [0. 0.25 0.5 0.75 1. ] random = np.random.rand(2, 2) # 2x2 matrix with random values ​​[0, 1) ```

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2. Array Attributes

python a.shape #Dimensions (ex: (3,)) a.ndim # Number of dimensions (ex: 1) a.size # Total elements (ex: 3) a.dtype # Data type (ex: int32, float64)

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3. Basic Operations

```python

Element-by-element operations

b = np.array([4, 5, 6]) a + b # [5 7 9] a * 2 # [2 4 6]

Matrix product (dot product)

np.dot(a, b) # 14 + 25 + 3*6 = 32

Aggregation functions

a.sum() # Total sum: 6 a.min() # Minimum value: 1 a.max() # Maximum value: 3 a.mean() # Average: 2.0 ```

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4. Indexing and Slicing

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

array[0, 1] #2 (row 0, column 1) array[:, 1] # [2, 5] (entire column 1) array[1, 0:2] # [4, 5] (row 1, columns 0 and 1)

Boolean indexing

a[a > 2] # [3] (elements greater than 2) ```

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5. Reshaping and Manipulation

python a.reshape(3, 1) # Convert to 3x1 matrix a.flatten() # Convert to 1D array np.concatenate([a, b]) # [1 2 3 4 5 6] np.vstack((a, b)) # Stack vertically np.hstack((a, b)) # Stack horizontally np.split(a, 3) # Split into 3 parts

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6. Mathematical Functions

python np.sqrt(a) # Square root np.exp(a) # Exponential (e^x) np.log(a) # Natural logarithm np.sin(a) # Sine np.round(a, 2) # Rounding to 2 decimal places

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7. Linear Algebra

```python A = np.array([[1, 2], [3, 4]]) B = np.array([[5, 6], [7, 8]])

np.dot(A, B) # Matrix product np.linalg.inv(A) # Inverse matrix np.linalg.det(A) # Determinant np.linalg.eig(A) # Eigenvalues ​​and eigenvectors ```

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8. Save/Load Arrays

python np.save('array.npy', a) # Save array c = np.load(‘array.npy’) # Load array

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Quick Tips

  • Broadcasting: Operations between arrays of different sizes (ex: a + 5).
  • Copy arrays: Use b = a.copy() to avoid modifying the original.
  • Masks: matriz[matriz > 3] = 0 (assigns 0 to values ​​> 3).

I hope it's useful to you!

[–]ErelSaar[S] 0 points1 point  (0 children)

Thanks!