sklearn.datasets.load_digits

sklearn.datasets.load_digits(n_class=10)[source]

Load and return the digits dataset (classification).

Each datapoint is a 8x8 image of a digit.

Classes 10
Samples per class ~180
Samples total 1797
Dimensionality 64
Features integers 0-16
Parameters:

n_class : integer, between 0 and 10, optional (default=10)

The number of classes to return.

Returns:

data : Bunch

Dictionary-like object, the interesting attributes are: ‘data’, the data to learn, ‘images’, the images corresponding to each sample, ‘target’, the classification labels for each sample, ‘target_names’, the meaning of the labels, and ‘DESCR’, the full description of the dataset.

Examples

To load the data and visualize the images:

>>> from sklearn.datasets import load_digits
>>> digits = load_digits()
>>> print(digits.data.shape)
(1797, 64)
>>> import pylab as pl 
>>> pl.gray() 
>>> pl.matshow(digits.images[0]) 
>>> pl.show()