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.
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.
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.
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