Python
Installing Python Packages
This section is only relevant if you are running Python on your own computer. If you are running Python within a Jupyter notebook on a webserver or a computer account which has already been configured for your use (such as
https://jove.smith.edu for Smith College physics) , this section can be skipped.
Installing Python
Our focus in this article is on the use of Python to expedite the analysis of your experimental data and not, for example, the specifics of various Python distributions and their relative merits for computational physics in terms of speed, accuracy, and memory requirements.
We therefore recommend that if you need to install a Python distribution for scientific data analysis in physics on your own computer, you choose an installer that will automatically install
Python, interactive Python (
iPython) and
Jupyter notebooks, scientific python development environments (editing, testing, debugging) such as
Spyder or
Canopy, and essential
Scientific Python packages (such as
numpy,
matplotlib and
scipy) in a single step, rather than building this from scratch. This provides ease of installation, ease of use, and a comprehensive curated set of preinstalled and easily added packages.