Installing NetworkX #

Python has become the go-to programming language for data science projects due to its extensive ecosystem of third-party packages that facilitate tasks from data collection to visualisation. However, for those new to network analysis, knowing where to begin can be a bit overwhelming.

This guide is the first in a series that will introduce you to the fundamentals of analysing networks with Python. In this post, we will cover the installation of two key packages: NetworkX and Pandas.

Why NetworkX and Pandas? #

Both NetworkX and Pandas are highly regarded packages for network analysis in Python. Their popularity stems not only from their powerful features but also from the robust community that surrounds them. A strong community means ample resources, tutorials, and forums where you can seek help or find answers to common problems.

Here’s a brief overview of why these packages are essential for network analysis:

NetworkX #

• Comprehensive: Offers a wide range of tools and built-in algorithms for network analysis.
• Performance: Capable of handling large graphs and analysing them efficiently in real time.
• Ease-of-use: The package is well-structured, making it simple to locate the tools and functions you need.

Pandas #

• Modelling tabular data: Ideal for handling network edge lists and related tabular data.
• Import from external sources: Allows for easy importing of data from URLs or external files.
• Exchangeable data types: Flexible in terms of data manipulation and supports exporting to various formats.

Installation #

Installing these packages is straightforward, and you can choose between two primary methods: using pip or conda.

Installing with pip #

If you are working with a standard Python environment, you can install the packages using pip, Python’s package manager.

To install Pandas:

$ pip install pandas

To install NetworkX:

$ pip install networkx

Installing with Anaconda #

For users who prefer working in virtual environments, I highly recommend using Anaconda. It offers a comprehensive suite of tools specifically geared towards data analysis. Anaconda comes with Pandas pre-installed.

Once you’ve set up your virtual environment in Anaconda, it’s a good idea to install the SciPy package, which includes Pandas and other useful tools for scientific computing.

$ conda install scipy

Now, to install NetworkX:

$ conda install networkx

Conclusion #

The process of installing the necessary packages for network analysis is quite simple, whether you are using pip or conda. While this guide has focused on the most common installation methods, there are other ways to set up these packages depending on your specific environment or requirements.

In the next guide, we will begin by creating some basic graphs, taking the first step into network analysis with Python.

Next: Getting Started