Materials Informatics Research Engagement for Undergraduates 2021: An introduction to programming and data science with Python

This collection of Jupyter notebooks provides an introduction to Jupyter Notebook, programming with Python, and data science techniques with the Python libraries pandas and matplotlib. These materials were originally developed for inclusion in a collection of asynchronous learning modules created as part of a Materials Informatics Research Engagement for Undergraduates project.

Running these interactive notebooks

Run online

This is a Binder-ready repository. Click the launch binder button above or follow this Binder link to open this repository in an online Jupyter server and run these interactive notebooks without having to set up a local environment or download these materials. Note that it may take one minute or more to launch the environment. When the environment is loaded, click on any of the files with the .ipynb extension to open that notebook in the interactive editor.

Run on a local machine

These interactive notebooks can be copied to your local machine and run using Jupyter Notebook. Follow these steps to run on a local machine:

1. Copy the files. Clone this repository, or download a zip file containing the repository contents, using the green Code button at the top of the repository page.

2. Start a Jupyter server. You will need Anaconda installed on your machine, we recommend installing Anaconda using the appropriate Anaconda Graphical Installer for your operating system. If you have recently installed Anaconda you should also have Anaconda Navigator installed (Anaconda Navigator is a desktop graphical user interface that allows you to launch Jupyter Notebook, and other applications, and manage environments). We recommend opening Anaconda Navigator and launching Jupyter Notebook through that interface.

3. Navigate to the folder where the repository files were copied. After launching Jupyter Notebook a browser window should open with the Jupyter explorer interface. Use this interface to navigate to the folder in which you copied the repository files.

4. Open a notebook. Click on any of the files with the .ipynb extension to open that notebook in the interactive editor.

Notebook content

Workshop 1: Introduction to Jupyter and Python

This notebook introduces the Jupyter Notebook interface and covers fundamental concepts of programming in the Python programming language.

Workshop 2: Getting started with pandas

This notebook provides an introduction to the pandas library, including methods for reading, exploring, and writing various data formats such as tab-delimited files, Excel files, and JSON files.

Workshop 3: Cleaning, manipulating, and exploring data with pandas

This notebook covers common methods for cleaning and preparing datasets for analyses with pandas such as filtering, aggregation, and joins and introduces basic exploratory analysis methods using pandas and Python visualization libraries.

Credits

These materials were developed by Claire Cahoon and Walt Gurley in the Data & Visualization Services Department at the NC State University Libraries.