Setting a column in a dataframe to new values

from sklearn import preprocessing

def labelencoder(dataframe) : 
  label_encoder = preprocessing.LabelEncoder() 
  dataframe= label_encoder.fit_transform(dataframe)
  
  return dataframe

new_df['label'] = labelencoder(new_df['label'])

I am getting the following warning for the above code:

SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

new_df['label'] = labelencoder(new_df['label'])

The code is working fine, it just shows this warning each time. Is there a solution?

I tried something like:

new_df.loc[:, 'label'] = labelencoder(new_df['label'])

But it didn't work, It still shows the warning

source https://stackoverflow.com/questions/76134989/setting-a-column-in-a-dataframe-to-new-values

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