Why does using X[0] in MNIST classifier code give me an error?

Question

I was learning to do classification with the MNIST dataset. And I got an error with I am not able to figure out, I have done a lot of google searches and I am not able to do anything, maybe you are an expert and can help me. Here is the code--

>>> from sklearn.datasets import fetch_openml
>>> mnist = fetch_openml('mnist_784', version=1)
>>> mnist.keys()

output: dict_keys(['data', 'target', 'frame', 'categories', 'feature_names', 'target_names', 'DESCR', 'details', 'url'])

>>> X, y = mnist["data"], mnist["target"]
>>> X.shape

output:(70000, 784)

>>> y.shape

output:(70000)

>>> X[0]

output:KeyError                                  Traceback (most recent call last)
c:\users\khush\appdata\local\programs\python\python39\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2897             try:
-> 2898                 return self._engine.get_loc(casted_key)
   2899             except KeyError as err:

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 0

The above exception was the direct cause of the following exception:

KeyError                                  Traceback (most recent call last)
<ipython-input-10-19c40ecbd036> in <module>
----> 1 X[0]

c:\users\khush\appdata\local\programs\python\python39\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   2904             if self.columns.nlevels > 1:
   2905                 return self._getitem_multilevel(key)
-> 2906             indexer = self.columns.get_loc(key)
   2907             if is_integer(indexer):
   2908                 indexer = [indexer]

c:\users\khush\appdata\local\programs\python\python39\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2898                 return self._engine.get_loc(casted_key)
   2899             except KeyError as err:
-> 2900                 raise KeyError(key) from err
   2901 
   2902         if tolerance is not None:

KeyError: 0

Please answer, there can be a silly mistake because I am a beggineer in ML. It would be really helpful if you gave me some hint also.

Answer 1

The API of fetch_openml changed between versions. In earlier versions, it returns a numpy.ndarray array. Since 0.24.0 (December 2020), as_frame argument of fetch_openml is set to auto (instead of False as default option earlier) which gives you a pandas.DataFrame for the MNIST data. You can force the data read as a numpy.ndarray by setting as_frame = False. See fetch_openml reference .

Answer 2

I was also facing the same problem.

• scikit-learn: 0.24.0
• matplotlib: 3.3.3
• Python: 3.9.1

I used to below code to resolve the issue.

import matplotlib as mpl
import matplotlib.pyplot as plt


# instead of some_digit = X[0]
some_digit = X.to_numpy()[0]
some_digit_image = some_digit.reshape(28,28)

plt.imshow(some_digit_image,cmap="binary")
plt.axis("off")
plt.show()

Answer 3

You don't need to downgrade you scikit-learn library, if you follow the code below:

from sklearn.datasets import fetch_openml
mnist = fetch_openml('mnist_784', version= 1, as_frame= False)
mnist.keys()