[{'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:import nltk\ntexttest1 = nltk.Text(tok1)\ntexttest2 = nltk.Text(tok2)\ntexttest3 = nltk.Text(tok3)\ntexttest4 = nltk.Text(tok4)\ntexttest5 = nltk.Text(tok5)\nfreqdistemail1 = texttest1.vocab()\nfreqdistemail2 = texttest2.vocab()\nfreqdistemail3 = texttest3.vocab()\nfreqdistemail4 = texttest4.vocab()\nfreqdistemail5 = texttest5.vocab()\nfromtodf = pd.DataFrame()\nfromtodf_from = []\nfromtodf_to = []\nemail_count = []\nfor i in range(len(from_list['email'])):\nfromtodf_from.append(from_list['email'][i])\nfromtodf_to = [freqdistemail1.most_common()[1][0],freqdistemail2.most_common()[1][0],freqdistemail3.most_common()[1][0],freqdistemail4.most_common()[1][0],\nfreqdistemail5.most_common()[1][0]]\nemail_count = [freqdistemail1.most_common()[1][1],freqdistemail2.most_common()[1][1],freqdistemail3.most_common()[1][1],freqdistemail4.most_common()[1][1],\nfreqdistemail5.most_common()[1][1]]\nfromtodf['From'] = fromtodf_from\nfromtodf['To'] = fromtodf_to\nfromtodf['Email Count'] = email_count\nfromtodf"}, {'role': 'assistant', 'content': "['data_exploration']"}]