diff --git a/contrib/pandas/Pandas_Series_Vs_NumPy_ndarray.md b/contrib/pandas/Pandas_Series_Vs_NumPy_ndarray.md
index d493136..e739766 100644
--- a/contrib/pandas/Pandas_Series_Vs_NumPy_ndarray.md
+++ b/contrib/pandas/Pandas_Series_Vs_NumPy_ndarray.md
@@ -6,7 +6,7 @@ Both NumPy ndarray and Pandas Series are essential tools for data manipulation i
 
 ## NumPy ndarray
 
-NumPy is short form for Numerical Python, provides a powerful array object called `ndarray`, which is the backbone of many scientific and mathematical Python libraries. ndarray is also called n-dimensional array. Indexing in ndarray is integer based indexing. 
+NumPy is short form for Numerical Python, provides a powerful array object called `ndarray`, It is very important for many scientific and mathematical Python libraries. ndarray is also called n-dimensional array. Indexing in ndarray is integer based indexing (like arr[0], arr[3], etc.).
 
 Features of NumPy `ndarray`:
 
@@ -31,11 +31,11 @@ Output:
 - When you need to perform mathematical operations on numerical data.
 - When you’re working with multi-dimensional data.
 - When computational efficiency is important.
-- When you need to store data of same data type.  `
+- When you need to store data of same data type.
 
 ## Pandas Series
 
-Pandas is a Python library used for data manipulation and analysis, introduces the `Series` data structure, which is designed for handling labeled one-dimensional data efficiently.
+Pandas is a Python library used for data manipulation and analysis, introduces the `Series` data structure, which is designed for handling labeled one-dimensional data efficiently. Indexing in Pandas Series is Label-based. It effectively handles heterogeneous data.
 
 Features of Pandas `Series`:
 
@@ -43,7 +43,7 @@ Features of Pandas `Series`:
 
 - **Heterogeneous Data**: Unlike NumPy arrays, Pandas Series can hold data of different types (integers, floats, strings, etc.) within the same object.
 
-- **Data Alignment**: One of the powerful features of Pandas Series is its ability to automatically align data based on label. This makes handling and manipulating data much more intuitive and less error-prone.
+- **Data Alignment**: One of the powerful features of Pandas Series is its ability to automatically align data based on label.
 
 Example of creating a Pandas Series: