Loading scikit-learn's MNIST Hand-Written Dataset

h1ros

Jun 22, 2019, 2:52:16 AM

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Goal¶

This post aims to introduce how to load MNIST (hand-written digit image) dataset using scikit-learn

Refernce

Scikit-learn Tutorial - introduction

Library¶

In [11]:

from sklearn.datasets import load_digits
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

Load Dataset¶

In [2]:

mnist = load_digits()

In [3]:

type(mnist)

Out[3]:

sklearn.utils.Bunch

In [4]:

mnist.keys()

Out[4]:

dict_keys(['data', 'target', 'target_names', 'images', 'DESCR'])

Data¶

In [5]:

pd.DataFrame(mnist.data).head()

Out[5]:

	2	3	4	5	9	...	54	58	59	60	61	62
0	5.0	13.0	9.0	1.0	0.0	...	0.0	6.0	13.0	10.0	0.0	0.0
1	0.0	12.0	13.0	5.0	0.0	...	0.0	0.0	11.0	16.0	10.0	0.0
2	0.0	4.0	15.0	12.0	0.0	...	5.0	0.0	3.0	11.0	16.0	9.0
3	7.0	15.0	13.0	1.0	8.0	...	9.0	7.0	13.0	13.0	9.0	0.0
4	0.0	1.0	11.0	0.0	0.0	...	0.0	0.0	2.0	16.0	4.0	0.0

5 rows × 64 columns

Target¶

In [6]:

pd.DataFrame(mnist.target).head()

Out[6]:

	0
0	0
1	1
2	2
3	3
4	4

Images¶

This dataset comprises of 8 x 8 images.

In [13]:

plt.imshow(mnist.images[0]);

In [27]:

fig, axes = plt.subplots(2, 10, figsize=(16, 6))
for i in range(20):
    axes[i//10, i %10].imshow(mnist.images[i], cmap='gray');
    axes[i//10, i %10].axis('off')
    axes[i//10, i %10].set_title(f"target: {mnist.target[i]}")
    
plt.tight_layout()