2023-02-24

# How to Save Numpy Array to File?

## Save/Load single array

To save a NumPy array to a file, you can use the `np.save`

function. The `np.save`

function can save a NumPy array to a binary file with a `.npy`

extension.

```
import numpy as np
# Create a NumPy array
my_array = np.array([1, 2, 3, 4, 5])
# Save the array to a file
np.save('my_array.npy', my_array)
```

To load the saved array back into memory, you can use the `np.load`

function:

```
# Load the saved array from the file
loaded_array = np.load('my_array.npy')
# Print the loaded array
print(loaded_array)
```

Note:you can also save multiple arrays to a single file using`np.savez`

, which creates a compressed archive of the arrays with a`.npz`

extension.

## Save/Load multiple arrays

```
import numpy as np
# Create some example data
X = np.array([[1, 2, 3], [4, 5, 6]])
y = np.array([0, 1])
# Save the arrays to a file
np.savez('my_data.npz', X=X, y=y)
# Load the arrays from the file
loaded_data = np.load('my_data.npz')
X_loaded = loaded_data['X']
y_loaded = loaded_data['y']
# Print the loaded arrays
print('X:', X_loaded)
print('y:', y_loaded)
```

Tags:
numpy
dataset
machine-learning