[{'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:def convertSymbolsToInt(train, maxSymbolsForEachColumns=10,nameOfColumnsToKeepNoTouch=[],nameOfColumnsToDrop=[],hashtable={}):\n""" converts no number data into integer.\nArgs:\ntrain (df): main data frame.\nmaxSymbolsForEachColumns (int) : If columns have a number of unique values learger than  the columns are not converted.\nnameOfColumnsToKeepNoTouch (list) : column-names-list to keep original data.\nnameOfColumnsToDrop (list): list of columns whish is removed from datatable.\nhashtable (dict): hashtable to convert symbols to integer numbers. this hash is pdated if data has symbols that is not listed in the hashtable.\nReturns:\n(df, dict) : a tapple (pd.DataFrame and hashtable{})\n"""\n_hashtable={}\nfor name in train.columns:\nif name in set(hashtable.keys()):\n_hashtable[name]=hashtable[name]\nelse:\n_hashtable[name]={}\nif name in set(nameOfColumnsToKeepNoTouch):\ncontinue\nif name in set(nameOfColumnsToDrop):\ntrain=train.drop(name,axis=1)\ncontinue\nif str.isnumeric(str(train[name][0])) and str.isnumeric(str(train[name][2])):\ncontinue\nif train[name].head(maxSymbolsForEachColumns).unique().shape[0]==maxSymbolsForEachColumns:\ncontinue\nuniqSymbol=train[name].dropna().unique()\nuniqSymbol.sort()\nnumberOfSymbols=uniqSymbol.shape[0]\nif numberOfSymbols >= maxSymbolsForEachColumns:\ncontinue\nfor __symbol in set(uniqSymbol):\nif _hashtable[name]=={}:\n_hashtable[name][0]=__symbol\ncontinue\nif __symbol not in set(_hashtable[name].values()):\nmaxKeyNum=max(_hashtable[name].keys())\n_hashtable[name][maxKeyNum+1]=__symbol\ntrain[name]=train[name].replace(to_replace=_hashtable[name].values(),value=_hashtable[name].keys())\ntrain[name]=train[name]\nreturn (train, _hashtable)'}, {'role': 'assistant', 'content': "['data_preprocessing']"}]