diff --git a/modules/contrail/util.py b/modules/contrail/util.py
index eab33f3dffb5bf3096786bacdd97df17cf9d76fb..c898e77954efb24e3cd864018f0cef418bdab296 100644
--- a/modules/contrail/util.py
+++ b/modules/contrail/util.py
@@ -116,15 +116,15 @@ def extract(mask_image, image_ts, clavrx_path):
             # tmp = horz_shear_3d.sel(Pressure=press, method='nearest')
             # tmp = tmp.sel(Longitude=lon, Latitude=lat, method='nearest')
 
-            levels_dict[press_bins[key]].append((press_level, press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
+            levels_dict[press_level].append((press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
             all_list.append((press_level, press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
 
     # Create pandas DataFrame for each list of tuples in voxel_dict
     voxel_dict_df = {}
     for k, v in levels_dict.items():
-        print(k, len(v))
+        print('pressure level, number of contrail points: ', k, len(v))
         df = pd.DataFrame(v,
-                          columns=["pressure_level", "pressure", "lat", "lon", "temperature", "relative_humidity",
+                          columns=["pressure", "lat", "lon", "temperature", "relative_humidity",
                                    "horz_shear_deform", "static_stability", "horz_wind_speed", "vert_wind_shear"])
         voxel_dict_df[k] = df