In this tutorial, we'll introduce different methods for installing Pandas and Python on Linux. Then, we'll briefly compare the methods. Finally, we'll show how to manage multiple Python/Pandas versions on Linux.
As a prerequisite to each method, we need
- minimal ternimal knowledge
- non-root user with sudo privileges
The instructions described below have been tested on Linux Mint 19 and 20.
2. Install Python on Linux / Ubuntu
Python is a widely-used general-purpose, powerful, mature and high-level programming language. It is easy to learn and has a huge community. Python is one of the most liked and wanted languages according to: stackoverflow - Python is the most wanted language for its fifth-year
Most Linux systems have pre-installed Python on their machine. You can check your Linux by simple command:
python --version python3 --version
Python 2.7.17 Python 3.6.9
In 2021 Python 3 is the only one which needs to be used - Python 2 was deprecated.
2.1. Install Python by apt-get
Most of the Linux distros offer Python packages which can be installed simply by:
sudo apt-get install python3.8
Confirm the disk space prompt and wait for the installation
To search for other Python packages and versions you can use:
apt-cache search python3
or filtering the results:
apt-cache search python3 | grep Interactive:
python3.6-venv - Interactive high-level object-oriented language (pyvenv binary, version 3.6) python3.7 - Interactive high-level object-oriented language (version 3.7) python3.7-venv - Interactive high-level object-oriented language (pyvenv binary, version 3.7)
2.2. Download and install latest Python from python.org
If we want to use the latest and greatest version of Python, often manual installation is the way to go. This means downloading the package from the Python site.
Once the selected version is downloaded for example:
Python-3.10.1.tar.xz you can extract it by:
tar -xf Python-3.10.1.tar.xz
Next you need to open the extracted folder:
Start the configuration by:
Finally install Python by:
sudo make altinstall
Important note: In order to prevent damage on your Linux system use `altinstall` instead of `install`.
2.3. Verify the installation
Finally the installation can be verified by next commands:
which python3.8 result:
2.4. Create a virtual environment (optional)
Python offers a powerful package system
venv which helps separate different Python packages. In simple words, you can create several virtual environments in multiple Pandas versions:
- pandas 1.3.4
- pandas 1.0.0
To create new virtual environment called
- create folder for your virtual environments ( or select existing one)
- Run command:
python3.8 -m venv pandas1
- activate the environment by:
cd pandas1 source bin/activate
Once environment is activated you will see change in the terminal:
(pandas1) $ deactivate
The command above deactivates the environment.
3. Install Pandas on Linux
3.1. Install Pandas by Pypi
Next step is to install Pandas. The most popular way of installing Pandas is by running:
pip install pandas
You can find more information for Pandas on: pandas - pypi.org.
3.2. Install Pandas by Anaconda
If you like to use alternative installation methods you can check the official docs: Installation.
For example Pandas is part of Anaconda - so if you install Anaconda on your system you will get Pandas:
download the Anaconda installer for Linux
Verify data integrity with SHA-256. (optional but highly RECOMMENDED step)
follow the instructions or check for more details: Installing Anaconda on Linux
3.3. Verify Pandas installation
Finally you can test Pandas installation by running next commands:
pip freeze | grep pandas
result will be:
To summarize, in this article, we've seen examples of installing Python and Pandas from a PPA and manually. We've briefly explained these installation methods.
And finally, we've seen how to manage multiple Python/Pandas installations on Ubuntu systems with different package versions.