Pandas in Python is a package that is written for data analysis and manipulation. Pandas offer various operations and data structures to perform numerical data manipulations and time series. Pandas is an open-source library that is built over Numpy libraries. Pandas library is known for its high productivity and high performance. Pandas are popular because it makes importing and analyzing data much easier. Pandas programs can be written on any plain text editor like notepad, notepad++, or anything of that sort and saved with a .py extension.
To begin with, writing Pandas Codes and performing various intriguing and useful operations, one must have Python installed on their System.
What if Python already exists? Let’s check
To check if your device is pre-installed with Python or not, just go to the Command line(search for cmd in the Run dialog( + R). Now run the following command:
python --version
If Python is already installed, it will generate a message with the Python version available else install Python, for installing please visit: How to Install Python on Windows or Linux and PIP.
Python version
How to Install or Download Python Pandas
Pandas can be installed in multiple ways on Windows, Linux and MacOS. Various different ways are listed below:
Install Pandas on Windows
Python Pandas can be installed on Windows in two ways:
- Using pip
- Using Anaconda
Install Pandas using pip
PIP is a package management system used to install and manage software packages/libraries written in Python. These files are stored in a large “online repository” termed as Python Package Index (PyPI).
Install Python Pandas using Command Prompt
Pandas can be installed using PIP by use of the following command in Command Prompt.
pip install pandas
Install Pandas using Anaconda
Anaconda is open-source software that contains Jupyter, spyder, etc that is used for large data processing, Data Analytics, and heavy scientific computing. If your system is not pre-equipped with Anaconda Navigator, you can learn how to install Anaconda Navigator on Windows or Linux.
Install and Run Pandas from Anaconda Navigator
Step 1: Search for Anaconda Navigator in Start Menu and open it.
Step 2: Click on the Environment tab and then click on the Create button to create a new Pandas Environment.
Creating Environment
Step 3: Give a name to your Environment, e.g. Pandas, and then choose a Python and its version to run in the environment. Now click on the Create button to create Pandas Environment.
Naming the environment and selecting version
Step 4: Now click on the Pandas Environment created to activate it.
Activate the environment
Step 5: In the list above package names, select All to filter all the packages.
Getting all the packages
Step 6: Now in the Search Bar, look for ‘Pandas‘. Select the Pandas package for Installation.
Selecting the package to install
Step 7: Now Right Click on the checkbox given before the name of the package and then go to ‘Mark for specific version installation‘. Now select the version that you want to install.
Selecting the version for installation
Step 8: Click on the Apply button to install the Pandas Package.
Step 9: Finish the Installation process by clicking on the Apply button.
Step 10: Now to open the Pandas Environment, click on the Green Arrow on the right of the package name and select the Console with which you want to begin your Pandas programming.
Pandas Terminal Window:
Pandas Terminal
Install Pandas on Linux
Install Pandas on Linux, just type the following command in the Terminal Window and press Enter. Linux will automatically download and install the packages and files required to run Pandas Environment in Python:
pip3 install pandas
Install Pandas on Mac OS
Install Pandas on MacOS, type the following command in the Terminal, and make sure that python is already installed in your system.
pip install pandas
Importing Pandas
Now, that we have installed pandas on the system. Let’s see how we can import it to make use of it.
For this, go to a Jupyter Notebook or open a Python file, and write the following code:
import pandas as pd
Here, pd is referred to as an alias to the Pandas, which will help us in optimizing the code.
