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NotFittedError                            Traceback (most recent call last)
Input In [199], in <cell line: 57>()
     54 label_encoder = LabelEncoder()
     56 # Fit the label encoder to the encoded column and transform it back to the original form
---> 57 decoded_column = label_encoder.inverse_transform(df['unique_top_5_person_who_resolved'])
     59 # Display the updated dataframe
     60 print(df.head())

File /Analytics/venv/CAPEANALYTICS/lib/python3.8/site-packages/sklearn/preprocessing/_label.py:288, in LabelEncoder.inverse_transform(self, y)
    276 def inverse_transform(self, y):
    277     """Transform labels back to original encoding.
    278 
    279     Parameters
   (...)
    286     y : numpy array of shape [n_samples]
    287     """
--> 288     check_is_fitted(self)
    289     y = column_or_1d(y, warn=True)
    290     # inverse transform of empty array is empty array

File /Analytics/venv/CAPEANALYTICS/lib/python3.8/site-packages/sklearn/utils/validation.py:967, in check_is_fitted(estimator, attributes, msg, all_or_any)
    963     attrs = [v for v in vars(estimator)
    964              if v.endswith("_") and not v.startswith("__")]
    966 if not attrs:
--> 967     raise NotFittedError(msg % {'name': type(estimator).__name__})

NotFittedError: This LabelEncoder instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.