add method to plot multiple results next to each other

lib/xgta.py

@@ -105,36 +105,62 @@ class Xgta:
             ])
         )
         
-        return self.Result(q, search_term)
+        return self.Result(self, q, search_term)
 
+
+    def plot_frequency_of(self, results=[], plot=[], shared_xaxes=True, shared_yaxes=True):
+        if plot:
+            absolut = [st for st in plot if not st.startswith('percent')]
+            percent = [st for st in plot if st.startswith('percent')]
+    
+            n_rows = 2 if len(absolut) > 0 and len(percent) > 0 else 1
+    
+            subplot_titles = []
+            
+            for i in results:
+                for y in range(n_rows):
+                    subplot_titles.append(i.search_term)
+    
+            print(subplot_titles)
     
+            
+            fig = make_subplots(
+                rows=n_rows*len(results),
+                cols=1, 
+                shared_xaxes=shared_xaxes, 
+                shared_yaxes=shared_yaxes, 
+                vertical_spacing=0.07,
+                subplot_titles=subplot_titles,
+            )
+    
+            for nth_result, result in enumerate(results):
+    
+                for i in px.line(result.df, x="postdate", y=absolut).data:
+                    fig.append_trace(i, row=nth_result*n_rows+1, col=1)
+                
+                for i in px.line(result.df, x="postdate", y=percent).data:
+                    fig.append_trace(i, row=nth_result*n_rows+n_rows, col=1)
+                    
+            if len(results) == 1:
+                fig.update_layout(title_text=results[0].search_term)
+                
+            fig.update_layout(height=len(results)*500, hovermode='x unified')
+            fig.update_traces(
+                mode="lines",
+                hovertemplate = "%{y}"),
+            fig.show()
+
     class Result:
         
-        def __init__(self, df, search_term):
+        def __init__(self, outer_instance, df, search_term):
             self.df = df
             self.search_term = search_term
+            self.outer_instance = outer_instance
 
         
-        def plot_frequency_of(self, plot=[]):
+        def plot_frequency_of(self, plot=[], shared_xaxes=True, shared_yaxes=False):
             if plot:
-    
-                absolut = [st for st in plot if not st.startswith('percent')]
-                percent = [st for st in plot if st.startswith('percent')]
-        
-                n_rows = 2 if len(absolut) > 0 and len(percent) > 0 else 1
-                fig = make_subplots(rows=n_rows, cols=1, shared_xaxes=True,vertical_spacing=0.02)
-        
-                for i in px.line(self.df, x="postdate", y=absolut).data:
-                    fig.append_trace(i, row=1, col=1)
-                
-                for i in px.line(self.df, x="postdate", y=percent).data:
-                    fig.append_trace(i, row=n_rows, col=1)
-                
-                fig.update_layout(title_text=self.search_term, height=600, hovermode='x unified')
-                fig.update_traces(
-                    mode="lines",
-                    hovertemplate = "%{y}"),
-                fig.show()
+                self.outer_instance.plot_frequency_of([self], plot=plot, shared_xaxes=shared_xaxes, shared_yaxes=shared_yaxes)
             else:
                 print("""
 Uncomment columns of interest: