afinamos los titulos en ejes de algunas figuras

estadisticas.py

@@ -16,15 +16,18 @@ server = flask.Flask(__name__)
 
 def datavis(datos):
     medidas = ["imc", "age", "glucose", "hba1c", "ct", "hdl"]    
-    fig = make_subplots(rows=2, cols=3, shared_xaxes=True, vertical_spacing=0.1,
-                        subplot_titles=medidas)
+    fig = make_subplots(rows=2, cols=3, vertical_spacing=0.25)
     lcol = 1
     lrow = 1
+    seq = 1
     for medida in medidas:
         fig.add_trace(
             go.Scatter(x=datos["id"], y=datos[medida], name=medida,mode="markers"),
             row=lrow, col=lcol
         )
+        fig['layout']['xaxis' + str(seq)]['title']='Patient ID'
+        fig['layout']['yaxis' + str(seq)]['title']=medida     
+        seq = seq + 1
         lrow = lrow + (lcol // 3)
         lcol = lcol + 1 if lcol < 3 else 1
     fig.update_layout(showlegend = False)
@@ -32,17 +35,20 @@ def datavis(datos):
 
 def popdist(datos):
     medidas = ["imc", "age", "glucose", "hba1c", "ct", "hdl"]
-    # removemos outliers
-    fig = make_subplots(rows=2, cols=3, shared_yaxes=True, subplot_titles=medidas)
+    # remoemos outliers
+    fig = make_subplots(rows=2, cols=3, vertical_spacing = 0.25 )
     lcol = 1
     lrow = 1
-
+    seq = 1
     for medida in medidas:
         datosfil = datos[np.abs(stats.zscore(datos[medida], nan_policy='omit')) < 3]
         fig.add_trace(
             go.Histogram(x=datosfil[medida], name=medida),
             row=lrow, col=lcol
         )
+        fig['layout']['xaxis' + str(seq)]['title']=medida     
+        seq = seq + 1
+        
         lrow = lrow + (lcol // 3)
         lcol = lcol + 1 if lcol < 3 else 1
 
@@ -56,44 +62,50 @@ def popdist(datos):
 def popcorr(datos):
     medidas = [ "glucose", "hba1c", "ct", "hdl", "insuline"]
     # removemos outliers
-    fig = make_subplots(rows=2, cols=3, shared_yaxes=False, subplot_titles=medidas)
+    fig = make_subplots(rows=2, cols=3, shared_yaxes=False, vertical_spacing=0.25)
     lcol = 1
     lrow = 1
-
+    seq = 1
     for medida in medidas:
         datosfil = datos[np.abs(stats.zscore(datos[medida], nan_policy='omit')) < 3]
         fig.add_trace(
             go.Scatter(x=datosfil["imc"], y=datosfil[medida], name=medida, mode="markers"),
             row=lrow, col=lcol
         )
+        fig['layout']['xaxis' + str(seq)]['title']='IMC'
+        fig['layout']['yaxis' + str(seq)]['title']=medida        
         lrow = lrow + (lcol // 3)
         lcol = lcol + 1 if lcol < 3 else 1
+        seq = seq + 1
 
     fig.update_layout(
         bargap=0.05, # gap between bars of adjacent location coordinates
         bargroupgap=0.05, # gap between bars of the same location coordinates
         showlegend = False
     )
+
     return fig
 
 
 
 def imc_cat(datos):
     medidas = [ "glucose", "hba1c", "ct", "hdl", "insuline"]
-    grupos = ["LW","NW","OW","O-CI","O-CII","O-CIII"]
-    datos["imc_cat"] = pd.cut(datos["imc"], bins=[0,18,25,30,35,40,100], labels=grupos)
-    fig = make_subplots(rows=2, cols=3, shared_yaxes=False, subplot_titles=medidas)
+    grupos = ["LW","NW","OW","O-CI","O-CII"]
+    datos["imc_cat"] = pd.cut(datos["imc"], bins=[0,18,25,30,35,40], labels=grupos)
+    fig = make_subplots(rows=2, cols=3, shared_yaxes=False, vertical_spacing=0.25)
     lcol = 1
     lrow = 1
-
+    seq = 1
     for medida in medidas:
         datosfil = datos.groupby("imc_cat")[medida].mean()
         fig.add_trace(
             go.Scatter(x=grupos, y=datosfil, name=medida),
             row=lrow, col=lcol
         )
+        fig['layout']['yaxis' + str(seq)]['title']=medida                
         lrow = lrow + (lcol // 3)
         lcol = lcol + 1 if lcol < 3 else 1
+        seq = seq + 1
 
     fig.update_layout(
         showlegend = False