[{'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:box_pts = time_window_s*fps+1\ndef box_plot_data(reaction_data, is_reversal):\nif is_reversal:\nreaction_str = \'Fraction of worms going backwards\'\ntitle_str = \'REVERSALS\'\nelse:\nreaction_str = \'Fraction of worms going forward\'\ntitle_str = \'FORWARDS\'\nresults = []\nfor exp, dat in reaction_data.items():\nfor key, (light_on, reaction_frac) in dat.items():\nbox = np.ones(box_pts)/box_pts\nlight_on_v = np.convolve(light_on, box, mode=\'same\')\ngood_off = light_on_v==0\ngood_on = light_on_v>.99\nresults.append((exp, key[0], \'ON\', np.nanmean(reaction_frac[good_on])))\nresults.append((exp, key[0], \'OFF\', np.nanmean(reaction_frac[good_off])))\nresults = pd.DataFrame(results, columns=[\'Experiment\', \'Strain\', \'Light\', reaction_str])\nsns.set(font_scale=1.3)\ng = sns.FacetGrid(results, col="Strain", row=\'Experiment\', size=5, aspect=1)\ng = g.map(sns.boxplot, "Light", reaction_str)\ng = g.map(sns.stripplot, "Light", reaction_str, color="r")\nplt.subplots_adjust(top=0.9)\ng.fig.suptitle(title_str)\nreturn results\nresults_reversal = box_plot_data(reversals_data, is_reversal=True)\nresults_forward = box_plot_data(forwards_data, is_reversal=False)'}, {'role': 'assistant', 'content': "['data_exploration']"}]