fixed No timeseries chosen to plot.. bug

app.py

@@ -213,9 +213,6 @@ def display_filtered_forecast(file, preset_filename, selected_names, forecast_le
             df = load_table(preset_filename)
             file_name = preset_filename
 
-        if df.shape[1]>2048:
-            df = df.iloc[:,-2048:]
-            gr.Info("Maximum of 2048 steps per timeseries (row) is allowed, hence last 2048 kept. ℹ️", duration=5)
 
 
         # 3) Determine whether first column is names or numeric
@@ -224,9 +221,15 @@ def display_filtered_forecast(file, preset_filename, selected_names, forecast_le
             and df.iloc[:, 0].dtype == object
             and not df.iloc[:, 0].str.isnumeric().all()
         ):
+            if df.shape[1]>2048:
+                df = pd.concat([ df.iloc[:, [0]], df.iloc[:, -2048:] ], axis=1)
+                gr.Info("Maximum of 2048 steps per timeseries (row) is allowed, hence last 2048 kept. ℹ️", duration=5)
             all_names = df.iloc[:, 0].tolist()
             data_only = df.iloc[:, 1:].astype(float)
         else:
+            if df.shape[1]>2048:
+                df = df.iloc[:, -2048:]
+                gr.Info("Maximum of 2048 steps per timeseries (row) is allowed, hence last 2048 kept. ℹ️", duration=5)
             all_names = [f"Series {i}" for i in range(len(df))]
             data_only = df.astype(float)
 
@@ -497,4 +500,3 @@ gradio app.py
 ssh -L 7860:localhost:7860 nikita_blago@oracle-gpu-controller -t \
    ssh -L 7860:localhost:7860 compute-permanent-node-83 
 '''
-

data/air_passangers copy.csv

@@ -0,0 +1,2 @@
+index,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141
+air_passangers,132.0,129.0,121.0,135.0,148.0,148.0,136.0,119.0,104.0,118.0,115.0,126.0,141.0,135.0,125.0,149.0,170.0,170.0,158.0,133.0,114.0,140.0,145.0,150.0,178.0,163.0,172.0,178.0,199.0,199.0,184.0,162.0,146.0,166.0,171.0,180.0,193.0,181.0,183.0,218.0,230.0,242.0,209.0,191.0,172.0,194.0,196.0,196.0,236.0,235.0,229.0,243.0,264.0,272.0,237.0,211.0,180.0,201.0,204.0,188.0,235.0,227.0,234.0,264.0,302.0,293.0,259.0,229.0,203.0,229.0,242.0,233.0,267.0,269.0,270.0,315.0,364.0,347.0,312.0,274.0,237.0,278.0,284.0,277.0,317.0,313.0,318.0,374.0,413.0,405.0,355.0,306.0,271.0,306.0,315.0,301.0,356.0,348.0,355.0,422.0,465.0,467.0,404.0,347.0,305.0,336.0,340.0,318.0,362.0,348.0,363.0,435.0,491.0,505.0,404.0,359.0,310.0,337.0,360.0,342.0,406.0,396.0,420.0,472.0,548.0,559.0,463.0,407.0,362.0,405.0,417.0,391.0,419.0,461.0,472.0,535.0,622.0,606.0,508.0,461.0,390.0,432.0