[{'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:country_stat=pd.read_csv('../input/countryinfo/covid19countryinfo.csv')\ncountry_stat = country_stat[country_stat['region'].isnull()] \n\ndef add_country_stat(old_df,country_stat):\n    df=old_df.copy()\n    df=df.merge(country_stat[['country','pop','medianage','sex65plus','lung','smokers','density']],left_on=['Country_Region'],right_on=['country'],how='left')\n    df.drop(columns=['country'],inplace=True)\n    \n    df['pop']=df['pop'].fillna(1000)\n    df['pop']=df['pop'].apply(lambda x: int(str(x).replace(',', '')))\n    #df['gdp2019']=df['gdp2019'].fillna(0)\n    #df['gdp2019']=df['gdp2019'].apply(lambda x: int(str(x).replace(',', '')))\n    #df['gdp2019']=df['gdp2019']/df['pop']\n    \n    \n    df['density']=df['density'].fillna(0)\n    df['medianage']=df['medianage'].fillna(0)\n    #df['sexratio']=df['sexratio'].fillna(1)\n    df['sex65plus']=df['sex65plus'].fillna(1)\n    df['lung']=df['lung'].fillna(24)\n    df['smokers']=df['smokers'].fillna(24)\n    #df['lung']=df['lung']*df['pop']\n    \n    return df\n    \n\ntrain=add_country_stat(train,country_stat)"}, {'role': 'assistant', 'content': 'load_data'}]