reelabooración de las gráficas de detalle de visitas

ahora hay una gráfica que muestra la cobertura de las variables que se
registran en las visitas.

dinamyc.py

@@ -2,12 +2,16 @@ import pandas as pd
 from dash import Dash, Input, Output, dcc, html
 from dash import Dash, Input, Output, dcc, html
 import plotly.graph_objects as go
 import plotly.graph_objects as go
 import plotly.express as px
 import plotly.express as px
+import requests
+import numpy as np
 
 
+url = 'https://nutricion.c3.unam.mx/nd/'
 data_o = (
 data_o = (
     pd.read_csv("inventario.csv")
     pd.read_csv("inventario.csv")
 )
 )
 
 
-
+data_o["paciente"] = data_o["paciente"].astype("str") + "_p"
+data_o["Secuenciaciones"] = 0
 Visitas_e = 4
 Visitas_e = 4
 Etapas_e = 3
 Etapas_e = 3
 Comidas_E1_e = 42
 Comidas_E1_e = 42
@@ -258,26 +262,6 @@ app.layout = html.Div(
                                     ),
                                     ),
                                 ], className="wrapper"
                                 ], className="wrapper"
                             ),
                             ),
-                            html.Div(
-                                children=[
-                                    html.Div(children="Medida", className="menu-title"),
-                                    dcc.Dropdown(
-                                        id="pruebasVisita",
-                                        options=[
-                                            {"label":"Antropometría", "value":"antrop-mets"},
-                                            {"label":"Qumíca Sanguinea", "value":"quimica-S"},
-                                            {"label":"C.Corporal", "value":"comp-corp"},
-                                            {"label":"Fisiológicos", "value":"physiological"},
-                                            {"label":"C. Tolerancia", "value":"tolerancia"},                                                                                                    
-                                        ],
-                                        value='antrop-mets',
-                                        clearable=False,
-                                        searchable=False,
-                                        className="dropdown",
-                                    ), 
-                                ], className="wrapper", 
-                            ),
-                    
                         ], style={"display":"flex", "flexDirection": "row"},
                         ], style={"display":"flex", "flexDirection": "row"},
                     ),
                     ),
             
             
@@ -301,7 +285,6 @@ app.layout = html.Div(
                                 {"label":"1", "value":1},
                                 {"label":"1", "value":1},
                                 {"label":"2", "value":2},
                                 {"label":"2", "value":2},
                                 {"label":"3", "value":3},
                                 {"label":"3", "value":3},
-                                {"label":"No-Clas.", "value":4},
                                 {"label":"Total", "value":5},                 
                                 {"label":"Total", "value":5},                 
                             ],
                             ],
                             value=1,
                             value=1,
@@ -335,11 +318,10 @@ app.layout = html.Div(
     Input("etapaDet", "value"),
     Input("etapaDet", "value"),
     Input("visitaSel", "value"),
     Input("visitaSel", "value"),
     Input("visitaPruebas", "value"),
     Input("visitaPruebas", "value"),
-    Input("pruebasVisita", "value"),        
     Input("mesurableEt", "value"),            
     Input("mesurableEt", "value"),            
 
 
 )
 )
-def update_charts(etapaSel,min_comidas, min_glucosa, medidaDet, etapaDet, visitaSel, visitaPruebas, pruebasVisita, mesurableEt):
+def update_charts(etapaSel,min_comidas, min_glucosa, medidaDet, etapaDet, visitaSel, visitaPruebas, mesurableEt):
     contados ={}
     contados ={}
     total_data = len(data.index)
     total_data = len(data.index)
     gauges = {
     gauges = {
@@ -527,18 +509,24 @@ def update_charts(etapaSel,min_comidas, min_glucosa, medidaDet, etapaDet, visita
         gauge = gauges,
         gauge = gauges,
     ))    
     ))    
 
 
-    visitaCad = pruebasVisita + str(visitaPruebas)
+    url_visitas = url + "/visits/" + str(visitaPruebas) + "/patients-data/"
+    t1 = requests.get(url_visitas).json()["patient_data"]
+    df = pd.json_normalize(t1)
+    df.drop(["tolerance_curve_measure","id","name","finished_periods","include_in_analysis","patient_visit_id", "visit_date","sample"], inplace=True, axis=1)
+    l1 = [ { cf["controlled_food"]: cf["increment_auc"] for cf in tolerance["tolerance_curve_measure"] } for tolerance in t1 ] 
+    df.rename(columns= lambda x: x.split(".")[1] if "." in x else x, inplace=True)
+    df1 = pd.concat([df, pd.DataFrame(l1)], axis=1)
+#    df1 = df
+    cuentas = 100 *  df1.replace("",np.nan).count() / len(df1)
+    
     detalle_pruebas = {
     detalle_pruebas = {
         "data": [
         "data": [
             {
             {
-                "x": data["paciente"],
-                "y": data[visitaCad],
+                "x": cuentas.index,
+                "y": cuentas,
                 "type": "bar",
                 "type": "bar",
             }
             }
         ],
         ],
-        "layout": {
-            "title": {"text": pruebasVisita + " " +   str(visitaPruebas)}
-        }
     }
     }