forma de contar los renglones de cada indicador

en vez del método count() cambiamos a la longitud del index. así,
podemos asignar un DF vacío si así es conveniente.

dinamyc.py

@@ -195,7 +195,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
 
     comidas_data = data.query("Selectedfoods >= @min_comida")
     multi.add_trace(go.Indicator(
-        value = 100 * comidas_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(comidas_data.index) / Total_pacientes,
         domain = {'x': [0.25, 1], 'y': [0.90, 1]},
         title = {'text': "Comidas"},
         mode = modes,
@@ -205,7 +205,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
 
     glucosa_data = data.query("Days_glucose >= @min_glucosa") 
     multi.add_trace(go.Indicator(
-        value = 100 * glucosa_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(glucosa_data.index) / Total_pacientes,
         domain = {'x': [0.25, 1], 'y': [0.8, 0.9]},
         title = {'text': "Glucómetro"},
         mode = modes,
@@ -224,7 +224,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
  
     
     multi.add_trace(go.Indicator(
-        value = 100 * medibles_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(medibles_data.index) / Total_pacientes,
         domain = {'x': [0.25, 1], 'y': [0.7, 0.8]},
         title = {'text': "AUCs"},
         mode = modes,
@@ -234,7 +234,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
 
     relojes_data = data.query("ConPasos > 0") 
     multi.add_trace(go.Indicator(
-        value = 100 * relojes_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(relojes_data.index) / Total_pacientes,
         domain = {'x': [0.25, 1], 'y': [0.6, 0.7]},
         title = {'text': "Reloj"},
         mode = modes,
@@ -244,7 +244,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
     
     microbiota_data = data.query("MT >= @min_microbiota") 
     multi.add_trace(go.Indicator(
-        value = 100 * microbiota_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(microbiota_data.index) / Total_pacientes,
 #        value = min_microbiota,
         domain = {'x': [0.25, 1], 'y': [0.5, 0.6]},
         title = {'text': "Microbiota"},
@@ -255,7 +255,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
 
     fismet_data = data.query("FISMET >= @min_fismet") 
     multi.add_trace(go.Indicator(
-        value = 100 * fismet_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(fismet_data.index) / Total_pacientes,
 #        value = min_microbiota,
         domain = {'x': [0.25, 1], 'y': [0.4, 0.5]},
         title = {'text': "Fisiomet"},
@@ -266,7 +266,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
 
     qs_data = data.query("QS >= @min_qs") 
     multi.add_trace(go.Indicator(
-        value = 100 * qs_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(qs_data.index) / Total_pacientes,
 #        value = min_microbiota,
         domain = {'x': [0.25, 1], 'y': [0.3, 0.4]},
         title = {'text': "QS"},
@@ -278,7 +278,7 @@ def update_charts(etapaSel,min_comida, min_glucosa, min_aucs, min_microbiota, mi
     
     visitas_data = data.query("Nvisitas >= @min_visitas") 
     multi.add_trace(go.Indicator(
-        value = 100 * visitas_data["medibles"].count() / Total_pacientes,
+        value = 100 * len(visitas_data.index) / Total_pacientes,
         domain = {'x': [0.25, 1], 'y':[0.1, 0.2]},
         title = {'text': "Visitas"},
         mode = modes,