Update app.py

app.py

@@ -206,24 +206,23 @@ end = start + train_split
 
 if ("0" == "mycustom"):
 	x_train = train_data[[i for i in range(7)]].values
-if ("0" != "mycustom"):
-	x_train = train_data[[i for i in range(len(myfields))]].values
-
-if ("0" == "mycustom"):
 	y_train = features.iloc[start:end][[1]]
 if ("0" != "mycustom"):
+	x_train = train_data[[i for i in range(len(myfields))]].values
 	y_train = features.iloc[start:end][[0]]
 
 sequence_length = int(past / step)
 x_end = len(val_data) - past - future
 
 label_start = train_split + past + future
+st.write(label_start)
 
 if ("0" == "mycustom"):
 	x_val = val_data.iloc[:x_end][[i for i in range(7)]].values
+	y_val = features.iloc[label_start:][[1]]
 if ("0" != "mycustom"):
 	x_val = val_data.iloc[:x_end][[i for i in range(len(myfields))]].values
-y_val = features.iloc[label_start:][[1]]
+	y_val = features.iloc[label_start:][[0]]
 
 dataset_val = keras.preprocessing.timeseries_dataset_from_array(
     x_val,
@@ -273,3 +272,4 @@ fig = plot()
 st.pyplot(fig)
 
 # %%
+