Introduction to Jupyter Notebooks

Title: Introduction to Jupyter Notebooks
Author: Elizabeth DuPre & Ross Markello
Materials needed: A Miniconda installation
Time to Complete: One Hour
Workshop Slides

Summary/Context/Objectives:

  1. Learn about conda, a package manager for organizing and installing software packages and dependencies
  2. Learn about Jupyter Notebooks, an open-source tool for data visualization, analysis, and description
  3. Use conda to install all the necessary software to run a Jupyter Notebook
  4. Create and use a Python and R Jupyter notebook

Steps to Complete:

  1. Understand what conda is and how to install it
  2. Create a new conda environment and install all the necessary packages to use Jupyter notebooks
  3. Open the Jupyter notebook launch page in your browser
  4. Create a new (Python) Jupyter notebook
  5. Learn about Markdown, a plain-text formatting language that can be used in-line with Jupyter notebooks to provide descriptive text
  6. Show how Jupyter notebooks allow for seamless integration between languages like R and Python (using rpy2)
  7. Learn about the various languages that can be used natively in a Jupyter notebook (i.e., Python, R, LaTeX, Markdown, bash/shell, HTML)
  8. Create a new (R) Jupyter notebook
  9. Explore the differences between the Python + R Jupyter notebooks

Glossary:
conda: a package manager system
markdown: a plain-text formatting language
jupyter: an open-source Python library providing tools to create and use notebooks
pandas: an open-source Python library providing data structures similar to R’s built-in data frames
rpy2: an open-source Python library providing seamless integration between R and Python
seaborn: an open-source Python library providing useful data visualization tools

Additional Resources