2. Agenda#
Agenda#
Sync Changes from GitHub and a Brief Overview of Git Concepts: We’ll go over how to sync changes from GitHub and a brief overview of Git concepts.
Install Necessary Python Packages. If you haven’t done so already, make sure to run the following command in your terminal to install the necessary packages for this course:
pip install -r requirements.txtWhile going through the following notebooks, be sure to demo the features of using the Python and Jupyter extensions within VS Code.
Overview: https://code.visualstudio.com/docs/datascience/overview
Variable explorer and data viewer: https://code.visualstudio.com/docs/datascience/jupyter-notebooks#_variable-explorer-and-data-viewer
Custom notebook diffing: https://code.visualstudio.com/docs/datascience/jupyter-notebooks#_custom-notebook-diffing
Overview of the PyData Stack: We’ll go over the various libraries that we’ll be using in this course. This includes NumPy, SciPy, Pandas, Matplotlib, and Seaborn.
Optional review of using
interactin Jupyter Notebooks. We’re not going to cover it, but those that are interested can learn more about how to use it here.Python by Example: We’ll go through some examples of Python basics: basic control-flow, functions, and classes.
Start Homework 2 Together: We’ll start working on Homework 1. This homework will be due before the next class. It will not be graded, but it will be a good way to get started with the material.
Individual Help with Setup. Save 30-45 minutes at the end to help students individually with their setup.
Homework#
Please complete the following:
Homework 2: We’ll start working on Homework 1. This homework will be due before the next class. It will not be graded, but it will be a good way to get started with the material.
Please read the following:
Introduction to NumPy
Introduction to Matplotlib
Compare Matplotlib to other plotting libraries: ./src/comparing_plotting_libraries.ipynb
Introduction to SciPy
Additional Reading#
After class, consider reading some of the following on your own: