diff --git a/Examples/Basic/tutorial1.py b/Examples/Basic/tutorial1.py
index 7ea254f96..8e183d0a7 100644
--- a/Examples/Basic/tutorial1.py
+++ b/Examples/Basic/tutorial1.py
@@ -51,6 +51,12 @@ def main():
     ldf_data = c_dataobj.get_data(ldt_timestamps, ls_symbols, ls_keys)
     d_data = dict(zip(ls_keys, ldf_data))
 
+    # Filling the data for NAN
+    for s_key in ls_keys:
+        d_data[s_key] = d_data[s_key].fillna(method='ffill')
+        d_data[s_key] = d_data[s_key].fillna(method='bfill')
+        d_data[s_key] = d_data[s_key].fillna(1.0)
+
     # Getting the numpy ndarray of close prices.
     na_price = d_data['close'].values
 
diff --git a/Examples/Basic/tutorial3.py b/Examples/Basic/tutorial3.py
index 12d08f20f..422fce947 100644
--- a/Examples/Basic/tutorial3.py
+++ b/Examples/Basic/tutorial3.py
@@ -77,6 +77,7 @@ def main():
     # Filling the data.
     df_rets = df_rets.fillna(method='ffill')
     df_rets = df_rets.fillna(method='bfill')
+    df_rets = df_rets.fillna(1.0)
 
     # Numpy matrix of filled data values
     na_rets = df_rets.values
diff --git a/Examples/Basic/tutorial5.py b/Examples/Basic/tutorial5.py
index 877ae20b2..50bec0827 100644
--- a/Examples/Basic/tutorial5.py
+++ b/Examples/Basic/tutorial5.py
@@ -46,6 +46,9 @@ def main():
 
     # Reading just the close prices
     df_close = c_dataobj.get_data(ldt_timestamps, ls_symbols, "close")
+    df_close = df_close.fillna(method='ffill')
+    df_close = df_close.fillna(method='bfill')
+    df_close = df_close.fillna(1.0)
 
     # Creating the allocation dataframe
     # We offset the time for the simulator to have atleast one