diff --git a/pandas/03.04-Missing-Values.ipynb b/pandas/03.04-Missing-Values.ipynb
index 4febcb5..146a864 100644
--- a/pandas/03.04-Missing-Values.ipynb
+++ b/pandas/03.04-Missing-Values.ipynb
@@ -467,7 +467,8 @@
     "## Operating on Null Values\n",
     "\n",
     "As we have seen, Pandas treats ``None`` and ``NaN`` as essentially interchangeable for indicating missing or null values.\n",
-    "To facilitate this convention, there are several useful methods for detecting, removing, and replacing null values in Pandas data structures.\n",
+    "To facilitate this convention, there are several useful methods for detecting, removing, and replacing null values in Pandas data structures. Also some of the times if we drop the data  \n",
+    "Then it could create skewness among data so we use filling techniques like using mean, median values to fill out the data which will create a normal distribution behaviour among data. :\n",
     "They are:\n",
     "\n",
     "- ``isnull()``: Generate a boolean mask indicating missing values\n",