[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:tmp = df[((times.hour <= 9) & (times.hour >= 7))]\ncr_counts = tmp.loc[:, ["loc", "count"]].groupby(["loc"]).sum()["count"]\ndf_run = tmp.loc[:, ["time", "loc", "count"]].groupby(["time","loc"])\ntmp2 = pd.DataFrame(df_run.sum()["count"], columns = [\'count\'])\ntmp2.reset_index(inplace=True)\ntmp2 = tmp2.pivot(index="loc", columns = "time", values = \'count\')\nplt.figure(figsize=(15,10))\nvals = df.groupby(["loc"])["count"].sum().sort_values(ascending=False)[0:5]\ntmp2[tmp2.index.isin(vals.index)].plot(kind="barh", stacked = True)\nplt.legend(loc=\'center left\', bbox_to_anchor=(1.0, 0.5))\nplt.show()'}, {'role': 'assistant', 'content': 'data_exploration'}]