[{'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:# StateHoliday\n\n# StateHoliday column has values 0 & "0", So, we need to merge values with 0 to "0"\nrossmann_df["StateHoliday"].loc[rossmann_df["StateHoliday"] == 0] = "0"\n# test_df["StateHoliday"].loc[test_df["StateHoliday"] == 0] = "0"\n\n# Plot\nsns.countplot(x=\'StateHoliday\', data=rossmann_df)\n\n# Before\nfig, (axis1,axis2) = plt.subplots(1,2,figsize=(15,4))\n\nsns.barplot(x=\'StateHoliday\', y=\'Sales\', data=rossmann_df, ax=axis1)\n\nmask = (rossmann_df["StateHoliday"] != "0") & (rossmann_df["Sales"] > 0)\nsns.barplot(x=\'StateHoliday\', y=\'Sales\', data=rossmann_df[mask], ax=axis2)\''}, {'role': 'assistant', 'content': "['result_visualization']"}]