[{'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:crime['Year'] = pd.DatetimeIndex(crime['Incident Date']).year     # Adding a column for the year of the crime\nfig, ax = plt.subplots()                                          # Creating a figure\ncrime['Category'].value_counts().head(12).plot(ax=ax,             # Plotting the top 12 offenses by category (bar chart)\nkind='barh',\nlegend=False,\ncolor='blue',\nalpha=0.5,\nfigsize=(12,6))\nax.set_xlabel('Number of Offenses', fontsize=14)                  # Label the x-axis\nax.set_title('Top 12 Offenses in Detroit',                        # Title the graph\nfontsize=16, fontweight='bold')\nplt.show()\nfig, ax = plt.subplots()                                          # Creating a figure\ncrime['Year'].value_counts().plot(ax=ax,                          # Plotting the number of crimes per year (line graph)\nlegend=False,\ncolor='blue',\nalpha=0.5,\nfigsize=(12,6))\nax.set_ylabel('Number of Offenses', fontsize=14)                  # Label the y-axis\nax.set_title('Number of Crimes By Year',                          # Title the graph\nfontsize=16,\nfontweight='bold')\nax.ticklabel_format(useOffset=False)                              # Make sure the years show on the x-axis\nplt.show()"}, {'role': 'assistant', 'content': 'data_exploration'}]