The following blog series will let you know about the one of the powerful library of Python i.e. Pandas. Particularly, the blog will make understand about the usage, installation and different data structures of Pandas.


Pandas is one of the powerful library of Python which act as a data manipulation and analysis tool. It is primarily used in Data Science and Machine Learning. It provides a lot of powerful features and I will cover all of those one by one in upcoming blogs. Before going further let us understand, how you could install the Pandas Library in your Machine(Personal Computer).

Installation using PIP

pip(Python install Packages) is basically a package management system which is used to install and manage software packages written in Python. In order to install any package in Python using pip, you just need to enter following command and the command will automatically install the desired package.

pip install package-name

if you wish to install pandas library then just simply enter pip install pandas in your Linux terminal and pandas gets installed automatically as shown below.

How to Verify ?

In order to verify that pandas has been installed or not, you have to perform some simple steps which are described below:

  1. Open your Linux Terminal

  2. Enter python on terminal and it will put you inside the Python shell as shown below.

  3. Type import pandas and Press Enter

  4. After hitting the Enter, if pandas has not been installed in your machine then you would simply get an import error but if you have been prompt to enter the next statement then it means that the pandas has been successfully installed in your machine.

  5. You could also verify by just printing the current date time using pandas as shown below.

Data Structures of Pandas

Pandas mainly include following three Data Structures

  1. Series

  • Series is one dimensional data structure just like an Array.

  • It contains homogeneous data and once you have created a Series then you are not allowed to change the size of it. Hence it is size immutable.

  • You are allowed to change the values inside the Series. Thus it is value mutable.



  1. DataFrame

  • DataFrame is two-dimensional data structure just like your an structured database table which contains rows and columns.

  • It contains the heterogeneous data and you are allowed to change the size of dataframe after creation. Thus it is size mutable.

  • DataFrames are value mutable too.

  • DataFrame can also be defined as the container of Series data structures.

        Data Frame

  1. Panel

  • Panel is three-dimensional data structure which contains the heterogeneous data structure.

  • Panel is also size and value mutable.

  • Panel can also be defined as the container of Data Frames.

Note: Among all three data structures of pandas, Series and DataFrames are widely used.

Hopefully, you got an overview of Pandas Library. The journey has just started and it gonna be more interesting because in upcoming blogs we will go through each and every data structure one by one in detail i.e. how to create them, use their valuable features etc. Please feel free to share your valuable feedback and ask any kind of questions.

Thank you for Reading



About the author

Dixit Khurana