diff --git a/src/data/mat_to_csv.py b/src/data/mat_to_csv.py
index d4dbbe2..0033ea9 100644
--- a/src/data/mat_to_csv.py
+++ b/src/data/mat_to_csv.py
@@ -7,6 +7,7 @@ from datetime import datetime, timedelta
 
 import pandas as pd
 from mat4py import loadmat
+import numpy as np
 
 logging.config.fileConfig('./src/logging.conf', disable_existing_loggers=False)
 logger = logging.getLogger(__name__)
@@ -152,6 +153,25 @@ def parse_profiles(profiles_mat):
     df = pd.DataFrame(rows)
     return df
 
+def remove_zeros(df_profiles):
+    """
+    When parsing the pre/post storm profiles, the end of some profiles have constant values of zero. Let's change
+    these to NaNs for consistancy. Didn't use pandas fillnan because 0 may still be a valid value.
+    :param df:
+    :return:
+    """
+
+    df_profiles = df_profiles.sort_index()
+    groups = df_profiles.groupby(level=['site_id','profile_type'])
+    for key, _ in groups:
+        logger.debug('Removing zeros from {} profile at {}'.format(key[1], key[0]))
+        idx_site = (df_profiles.index.get_level_values('site_id') == key[0]) & \
+                   (df_profiles.index.get_level_values('profile_type') == key[1])
+        df_profile = df_profiles[idx_site]
+        x_last_ele = df_profile[df_profile.z!=0].index.get_level_values('x')[-1]
+        df_profiles.loc[idx_site & (df_profiles.index.get_level_values('x')>x_last_ele), 'z'] = np.nan
+
+    return df_profiles
 
 def matlab_datenum_to_datetime(matlab_datenum):
     # https://stackoverflow.com/a/13965852
@@ -228,6 +248,9 @@ def main():
     df_tides.set_index(['site_id', 'datetime'], inplace=True)
     df_sites.set_index(['site_id'], inplace=True)
 
+    logger.info('Nanning profile zero elevations')
+    df_profiles = remove_zeros(df_profiles)
+
     logger.info('Outputting .csv files')
     df_profiles.to_csv('./data/interim/profiles.csv')
     df_tides.to_csv('./data/interim/tides.csv')