Key Error: None of [Int64Index…] dtype='int64] are in the columns

Question

I\'m trying to shuffle my indices using the np.random.shuffle() method, but I keep getting an error that I don\'t understand. I\'d appreciate it if someone could help me puz

Answer 1

You created your scaled_inputs_all DataFrame using loc function, so it most likely contains no consecutive indices.

On the other hand, you created shuffled_indices as a shuffle from just a range of consecutive numbers.

Remember that scaled_inputs_all[shuffled_indices] gets rows of scaled_inputs_all which have index values equal to elements of shuffled_indices.

Maybe you should write:

scaled_inputs_all.iloc[shuffled_indices]

Note that iloc provides integer-location based indexing, regardless of index values, i.e. just what you need.

Answer 2

Got the same error:

KeyError: "None of [Int64Index([26], dtype='int64')] are in the [index]"

Solved by Saving the dataframe to a local file and open it,

like below:

df.to_csv('Step1.csv',index=False)
df = pd.read_csv('Step1.csv')

Answer 3

I had this problem too. I solved it by changing the data frame and series to array.

try the follwing codeline:

scaled_inputs_all.iloc[shuffled_indices].values 

Answer 4

This below error occured while deleting the row with index based on the column value condition:

return self._engine.get_loc(key) File "pandas/_libs/index.pyx", line 107, in pandas._libs.index.IndexEngine.get_loc File "pandas/_libs/index.pyx", line 131, in pandas._libs.index.IndexEngine.get_loc File "pandas/_libs/hashtable_class_helper.pxi", line 992, in pandas._libs.hashtable.Int64HashTable.get_item File "pandas/_libs/hashtable_class_helper.pxi", line 998, in pandas._libs.hashtable.Int64HashTable.get_item KeyError: 226

During handling of the above exception, another exception occurred:

Traceback (most recent call last):

To resolve this make a list of index and delete the rows at once as below:

df.drop(index=list1,labels=None, axis=0, inplace=True,columns=None, level=None, errors='raise')

Answer 5

might have someone also get the same error in working with KFOLD in machine learning.

And the solution for this is as below:

Click here to watch solutinon

You need to use iloc:

 X_train, X_test = X.iloc[train_index], X.iloc[test_index]

 y_train, y_test = y.iloc[train_index], y.iloc[test_index]