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+# Pandas DataFrame
+
+The Pandas DataFrame is a two-dimensional, size-mutable, and possibly heterogeneous tabular data format with labelled axes. A data frame is a two-dimensional data structure in which the data can be organised in rows and columns. Pandas DataFrames are comprised of three main components: data, rows, and columns.
+
+In the real world, Pandas DataFrames are formed by importing datasets from existing storage, which can be a Excel file, a SQL database or CSV file. Pandas DataFrames may be constructed from lists, dictionaries, or lists of dictionaries, etc.
+
+
+Features of Pandas `DataFrame`:
+
+- **Size mutable**: DataFrames are mutable in size, meaning that new rows and columns can be added or removed as needed.
+- **Labeled axes**: DataFrames have labeled axes, which makes it easy to keep track of the data.
+- **Arithmetic operations**: DataFrames support arithmetic operations on rows and columns.
+- **High performance**: DataFrames are highly performant, making them ideal for working with large datasets.
+
+
+### Installation of libraries
+
+`pip install pandas` <br/>
+`pip install xlrd`
+
+- **Note**: The `xlrd` library is used for Excel operations.
+
+Example for reading data from an Excel File:
+
+```python
+import pandas as pd
+
+l = pd.read_excel('example.xlsx')
+d = pd.DataFrame(l)
+print(d)
+```
+Output:
+```python
+    Name  Age
+0   John   12
+```
+
+
+Example for Inserting Data into Excel File:
+
+```python
+import pandas as pd
+
+l = pd.read_excel('file_name.xlsx')
+d = {'Name': ['Bob', 'John'], 'Age': [12, 28]}
+d = pd.DataFrame(d)
+L = pd.concat([l, d], ignore_index = True)
+L.to_excel('file_name.xlsx', index = False)
+print(L)
+```
+
+Output:
+```python
+    Name  Age
+0   Bob   12
+1   John  28
+```
+
+### Usage of Pandas DataFrame:
+
+- Can be used to store and analyze financial data, such as stock prices, trading data, and economic data.
+- Can be used to store and analyze sensor data, such as data from temperature sensors, motion sensors, and GPS sensors.
+- Can be used to store and analyze log data, such as web server logs, application logs, and system logs
diff --git a/contrib/pandas/index.md b/contrib/pandas/index.md
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 # List of sections
 
 - [Pandas Series Vs NumPy ndarray](pandas_series_vs_numpy_ndarray.md)
+- [Excel using Pandas DataFrame](excel_with_pandas.md)