Learning Numpy - Simple Tutorial For Beginners - NumPy - I/O with NumPy Part 20

The ndarray objects can be saved to and loaded from the disk files. The IO functions available are −

• load() and save() functions handle /numPy binary files (with npy extension)

• loadtxt() and savetxt() functions handle normal text files

NumPy introduces a simple file format for ndarray objects. This .npy file stores data, shape, dtype and other information required to reconstruct the ndarray in a disk file such that the array is correctly retrieved even if the file is on another machine with different architecture.

numpy.save()

The numpy.save() file stores the input array in a disk file with npy extension.

import numpy as np
a = np.array([1,2,3,4,5])
np.save('outfile',a)

import numpy as np
b = np.load('outfile.npy')
print (b)

[1 2 3 4 5]

The save() and load() functions accept an additional Boolean parameter allow_pickles. A pickle in Python is used to serialize and de-serialize objects before saving to or reading from a disk file.

savetxt()

The storage and retrieval of array data in simple text file format is done with savetxt() and loadtxt() functions.

import numpy as np

a = np.array([1,2,3,4,5])
np.savetxt('out.txt',a)
b = np.loadtxt('out.txt')
print (b)

[1. 2. 3. 4. 5.]

Note: The savetxt() and loadtxt() functions accept additional optional parameters such as header, footer, and delimiter.

Refernces

• Learning Numpy - Array From Existing Data Part 6
• Learning Numpy - Array Creation Routines Part 5
• Learning Numpy - Array Attributes Part 4
• Learning Numpy - Data Types Part 3