filtrado de outliers para relacion de ppgr/mediciones

estadisticas.py

@@ -59,21 +59,20 @@ def correlaciones(datos, controlado):
     lrow = 1
     lrow = 1
     lcol = 1
     lcol = 1
     for metrica in metricas:
     for metrica in metricas:
+        datosfil = datos_sorted[np.abs(stats.zscore(datos_sorted[metrica], nan_policy='omit')) < 3]     
+
         figura.add_trace(
         figura.add_trace(
-            go.Scatter(x=datos_sorted.index, y=datos_sorted[metrica], name=metrica, mode='markers'),
+            go.Scatter(x=datosfil.index, y=datosfil[metrica], name=metrica, mode='markers'),
             row=lrow, col=lcol
             row=lrow, col=lcol
         )
         )
         figura.add_trace(
         figura.add_trace(
-            go.Scatter(x=datos_sorted.index, y=datos_sorted[metrica].rolling(5).mean(), name="PM(5)"),
+            go.Scatter(x=datosfil.index, y=datosfil[metrica].rolling(5).mean(), name="PM(5)"),
             row=lrow, col=lcol
             row=lrow, col=lcol
         )
         )
         corr = datos_sorted[[metrica]].corrwith(datos_sorted[controlado]).values[0]
         corr = datos_sorted[[metrica]].corrwith(datos_sorted[controlado]).values[0]
         figura.add_annotation(row=lrow, col=lcol, text="R = " + "{:.2f}".format(corr))
         figura.add_annotation(row=lrow, col=lcol, text="R = " + "{:.2f}".format(corr))
         lcol = lcol + 1 if lcol < 2 else 1
         lcol = lcol + 1 if lcol < 2 else 1
         lrow = lrow + (lcol % 2)
         lrow = lrow + (lcol % 2)
-    figura.update_layout(yaxis1= dict(range=[15,45]))    
-    figura.update_layout(yaxis3= dict(range=[80,120]))
-    figura.update_layout(yaxis4= dict(range=[4,7]))
     figura.update_layout(showlegend=False)
     figura.update_layout(showlegend=False)
 
 
     return figura
     return figura