[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:from sklearn.preprocessing import OneHotEncoder, LabelEncoder\n\nfor p in categorial_features:\n    X_int = LabelEncoder().fit_transform(df_store[p].values.astype(str)).reshape(-1,1)\n    ohe_feat = OneHotEncoder(sparse=False).fit_transform(X_int)\n    tmp = pd.DataFrame(ohe_feat, columns=['{0}='.format(p) + str(i) for i in df_store[p].unique()], \n                       index=df_store.index,\n                       dtype=int)\n    df_store = pd.concat([df_store, tmp], axis=1)\n    df_store = df_store.drop(p, axis=1)"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]