Update app.py

app.py

@@ -9,19 +9,19 @@ import os
 
 
 def predictAirPassengers(df, split):
-    ts= pd.read_csv('AirPassengers.csv')
+    ts= pd.read_csv('DemandaQuito.csv')
     df2 =ts.copy()
     ttSplit=split/100
     ts['Month']=pd.to_datetime(ts['Month'])
-    ts.rename(columns={'#Passengers':'Passengers'},inplace=True)
+    ts.rename(columns={'#Valor':'Valor'},inplace=True)
     ts=ts.set_index(['Month'])
     ts['months'] = [x.month for x in ts.index]
     ts['years'] = [x.year for x in ts.index]
     ts.reset_index(drop=True, inplace=True)
 
     # Split Data
-    X=ts.drop("Passengers",axis=1)
-    Y= ts["Passengers"]
+    X=ts.drop("Valor",axis=1)
+    Y= ts["Valor"]
     X_train=X[:int (len(Y)*ttSplit)] 
     X_test=X[int(len(Y)*ttSplit):]
     Y_train=Y[:int (len(Y)*ttSplit)] 
@@ -32,11 +32,11 @@ def predictAirPassengers(df, split):
     rf.fit(X_train, Y_train)
     
     df1=df2.set_index(['Month'])
-    df1.rename(columns={'#Passengers':'Passengers'},inplace=True)
+    df1.rename(columns={'#Valor':'Valor'},inplace=True)
     train=df1.Passengers[:int (len(ts.Passengers)*ttSplit)]
     test=df1.Passengers[int(len(ts.Passengers)*ttSplit):]
     preds=rf.predict(X_test).astype(int) 
-    predictions=pd.DataFrame(preds,columns=['Passengers'])
+    predictions=pd.DataFrame(preds,columns=['Valor'])
     predictions.index=test.index
     predictions.reset_index(inplace=True)
     predictions['Month']=pd.to_datetime(predictions['Month'])
@@ -44,12 +44,12 @@ def predictAirPassengers(df, split):
     
     #combine all into one table
     ts_df=df.copy()
-    ts_df.rename(columns={'#Passengers':'Passengers'},inplace=True)
+    ts_df.rename(columns={'#Valor':'Valor'},inplace=True)
     train= ts_df[:int (len(ts_df)*ttSplit)]
     test= ts_df[int(len(ts_df)*ttSplit):] 
 
     df2['Month']=pd.to_datetime(df2['Month'])
-    df2.rename(columns={'#Passengers':'Passengers'},inplace=True)
+    df2.rename(columns={'#Valor':'Valor'},inplace=True)
     df3= predictions
     df2['origin']='ground truth'
     df3['origin']='prediction'
@@ -64,12 +64,12 @@ demo = gr.Interface(
         gr.Slider(1, 100, value=75, step=1, label="Train test split percentage"),
     ],
     outputs= [
-       gr.LinePlot(x='Month', y='Passengers', color='origin')
+       gr.LinePlot(x='Month', y='Valor', color='origin')
        #gr.Timeseries(x='Month')
 
     ],
     examples=[
-        [os.path.join(os.path.abspath(''), "AirPassengers_dt.csv"), 75],
+        [os.path.join(os.path.abspath(''), "DemandaQuito_dt.csv"), 75],
     ]
 )