Update test_dataset.py

test_dataset.py

@@ -81,7 +81,6 @@ class HealthStatisticsDataset(datasets.GeneratorBasedBuilder):
 
     @staticmethod
     def preprocess_data(data):
-        # 이 함수는 이미 전처리된 데이터를 사용하도록 수정되었습니다.
         data = data[['YearStart', 'LocationAbbr', 'LocationDesc', 'Geolocation', 'Topic', 'Question', 'Data_Value_Type', 'Data_Value', 'Data_Value_Alt', 
                      'Low_Confidence_Limit', 'High_Confidence_Limit', 'Break_Out_Category', 'Break_Out']]
         def convert_to_tuple(geo_str):
@@ -91,6 +90,8 @@ class HealthStatisticsDataset(datasets.GeneratorBasedBuilder):
                 return (lon, lat)
             else:
                 return geo_str
+
+        pd.options.mode.chained_assignment = None
       
         data['Geolocation'] = data['Geolocation'].apply(convert_to_tuple)
         disease_columns = [
@@ -131,6 +132,8 @@ class HealthStatisticsDataset(datasets.GeneratorBasedBuilder):
         data['Data_Value_Type'] = data['Data_Value_Type'].apply(lambda x: 1 if x == 'Age-Standardized' else 0)
         data.rename(columns={'Question':'Disease_Type', 'YearStart':'Year', 'Break_Out':'Break_Out_Details'}, inplace=True)
         data['Break_Out_Type'] = data['Break_Out_Type'].replace('Overall', 0)
+
+        pd.options.mode.chained_assignment = 'warn'
       
         lt2000 = pd.read_csv("https://docs.google.com/uc?export=download&id=1ktRNl7jg0Z83rkymD9gcsGLdVqVaFtd-&confirm=t")
         lt2000 = lt2000[(lt2000['race_name'] == 'Total') & (lt2000['age_name'] == '<1 year')]