added 6 more filters

utils.py

@@ -750,7 +750,12 @@ class QualtricsSurvey(QualtricsPlotsMixin):
         self.filter_consumer:list = None
         self.filter_ethnicity:list = None
         self.filter_income:list = None
-
+        self.filter_business_owner:list = None      # QID4
+        self.filter_employment_status:list = None   # QID13
+        self.filter_personal_products:list = None   # QID14
+        self.filter_ai_user:list = None             # QID22
+        self.filter_investable_assets:list = None   # QID16
+        self.filter_industry:list = None            # QID17
         
     
     
@@ -838,6 +843,12 @@ class QualtricsSurvey(QualtricsPlotsMixin):
         self.options_consumer = sorted(df['Consumer'].drop_nulls().unique().to_list()) if 'Consumer' in df.columns else []
         self.options_ethnicity = sorted(df['QID3'].drop_nulls().unique().to_list()) if 'QID3' in df.columns else []
         self.options_income = sorted(df['QID15'].drop_nulls().unique().to_list()) if 'QID15' in df.columns else []
+        self.options_business_owner = sorted(df['QID4'].drop_nulls().unique().to_list()) if 'QID4' in df.columns else []
+        self.options_employment_status = sorted(df['QID13'].drop_nulls().unique().to_list()) if 'QID13' in df.columns else []
+        self.options_personal_products = sorted(df['QID14'].drop_nulls().unique().to_list()) if 'QID14' in df.columns else []
+        self.options_ai_user = sorted(df['QID22'].drop_nulls().unique().to_list()) if 'QID22' in df.columns else []
+        self.options_investable_assets = sorted(df['QID16'].drop_nulls().unique().to_list()) if 'QID16' in df.columns else []
+        self.options_industry = sorted(df['QID17'].drop_nulls().unique().to_list()) if 'QID17' in df.columns else []
         
         return df.lazy()
     
@@ -854,15 +865,21 @@ class QualtricsSurvey(QualtricsPlotsMixin):
         
         return q.select(QIDs).rename(rename_dict)
 
-    def filter_data(self, q: pl.LazyFrame, age:list=None, gender:list=None, consumer:list=None, ethnicity:list=None, income:list=None) -> pl.LazyFrame:
+    def filter_data(self, q: pl.LazyFrame, age:list=None, gender:list=None, consumer:list=None, ethnicity:list=None, income:list=None, business_owner:list=None, employment_status:list=None, personal_products:list=None, ai_user:list=None, investable_assets:list=None, industry:list=None) -> pl.LazyFrame:
         """Filter data based on provided parameters
         
         Possible parameters:
-        - age: list of age groups to include
-        - gender: list
-        - consumer: list
-        - ethnicity: list
-        - income: list
+        - age: list of age groups to include (QID1)
+        - gender: list (QID2)
+        - consumer: list (Consumer)
+        - ethnicity: list (QID3)
+        - income: list (QID15)
+        - business_owner: list (QID4)
+        - employment_status: list (QID13)
+        - personal_products: list (QID14)
+        - ai_user: list (QID22)
+        - investable_assets: list (QID16)
+        - industry: list (QID17)
         
         Also saves the result to self.data_filtered.
         """
@@ -888,7 +905,29 @@ class QualtricsSurvey(QualtricsPlotsMixin):
         if income is not None:
             q = q.filter(pl.col('QID15').is_in(income))
         
-        self
+        self.filter_business_owner = business_owner
+        if business_owner is not None:
+            q = q.filter(pl.col('QID4').is_in(business_owner))
+        
+        self.filter_employment_status = employment_status
+        if employment_status is not None:
+            q = q.filter(pl.col('QID13').is_in(employment_status))
+        
+        self.filter_personal_products = personal_products
+        if personal_products is not None:
+            q = q.filter(pl.col('QID14').is_in(personal_products))
+        
+        self.filter_ai_user = ai_user
+        if ai_user is not None:
+            q = q.filter(pl.col('QID22').is_in(ai_user))
+        
+        self.filter_investable_assets = investable_assets
+        if investable_assets is not None:
+            q = q.filter(pl.col('QID16').is_in(investable_assets))
+        
+        self.filter_industry = industry
+        if industry is not None:
+            q = q.filter(pl.col('QID17').is_in(industry))
         
         self.data_filtered = q
         return self.data_filtered