I was learning to do classification with the MNIST dataset. And I got an error which 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
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 .