Updated On : Jul-23,2020 Tags numpy, basics
NumPy - IO with NumPy Part 20

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.

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

In [3]:
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.


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Dolly Solanki  Dolly Solanki