Data Visualization in Python

This workshop provides an introduction to effective data visualization in Python. The training focuses on three plotting packages: Matplotlib, Seaborn and Plotly. Examples may include simple static 1D plots, 2D contour maps, heat maps, violin plots, and box plots. The session may also touch on more advanced interactive plots.

Learning objectives: Attendees will be exposed to different plotting packages in Python, along with how to integrate them with NumPy and Pandas. After the session, participants will know the basic mechanics of how to generate publication-quality plots using Python.

Session format: Presentation, demo and hands-on

Knowledge prerequisites: Participants should have reasonable facility with the Python programming language, including a basic familiarity with NumPy arrays and Pandas data frames. No previous experience with Python plotting tools is required.

Hardware/software prerequisites: Participants have two options: (1) Come with your own installation of Anaconda Python 3 distribution on your laptop. This will provide Jupyter notebooks, NumPy, Pandas and Matplotlib. (2) Create an account on Adroit at least a few hours before the workshop (https://forms.rc.princeton.edu/registration/?q=adroit) and use the MyAdroit web interface for the workshop. Directions for using the MyAdroit interface are here:
https://researchcomputing.princeton.edu/jupyter

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Co-hosted with: GradFUTURES

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