pandas: powerful Python data analysis toolkit, Release 1.4.3
1.4.1 Installation
The easiest way to install pandas is to install it as part of the Anaconda distribution, a cross platform distribution for
data analysis and scientific computing. This is the recommended installation method for most users.
Instructions for installing from source, PyPI, ActivePython, various Linux distributions, or a development version are
also provided.
Python version support
Officially Python 3.8, 3.9 and 3.10.
Installing pandas
Installing with Anaconda
Installing pandas and the rest of the NumPy and SciPy stack can be a little difficult for inexperienced users.
The simplest way to install not only pandas, but Python and the most popular packages that make up the SciPy stack
(IPython, NumPy, Matplotlib, .. .) is with Anaconda, a cross-platform (Linux, macOS, Windows) Python distribution
for data analytics and scientific computing.
After running the installer, the user will have access to pandas and the rest of the SciPy stack without needing to install
anything else, and without needing to wait for any software to be compiled.
Installation instructions for Anaconda can be found here.
A full list of the packages available as part of the Anaconda distribution can be found here.
Another advantage to installing Anaconda is that you don’t need admin rights to install it. Anaconda can install in the
user’s home directory, which makes it trivial to delete Anaconda if you decide (just delete that folder).
Installing with Miniconda
The previous section outlined how to get pandas installed as part of the Anaconda distribution. However this approach
means you will install well over one hundred packages and involves downloading the installer which is a few hundred
megabytes in size.
If you want to have more control on which packages, or have a limited internet bandwidth, then installing pandas with
Miniconda may be a better solution.
Conda is the package manager that the Anaconda distribution is built upon. It is a package manager that is both cross-
platform and language agnostic (it can play a similar role to a pip and virtualenv combination).
Miniconda allows you to create a minimal self contained Python installation, and then use the Conda command to
install additional packages.
First you will need Conda to be installed and downloading and running the Miniconda will do this for you. The installer
can be found here
The next step is to create a new conda environment. A conda environment is like a virtualenv that allows you to specify
a specific version of Python and set of libraries. Run the following commands from a terminal window:
conda create -n name_of_my_env python
This will create a minimal environment with only Python installed in it. To put your self inside this environment run:
6 Chapter 1. Getting started