To participate fully in our programs, it is very helpful to have some skill using the primary Python data analysis tools, which include Python, the Pandas data analysis library, and Jupyter Notebook. This guide summarizes links to training, and some of our own notebooks for honing your Pandas skills.
These Jupyter notebooks are hosted in Google Colaboarator, a free Jupyter notebook environment. They will teach you core Pandas skills, and include short interactive tests at the end.
- Python and Pandas Demo. An overview of Python and Pandas and an introduction to Colab.
- Basic Pandas Analysis Tutorial and Test. If your are stuck, there is also a Solved version of the notebook.
- Restructuring Tables Tutorial and Test, and the Solutions.
- Advanced Indexing Tutorial and Test, and the Solutions.
Online Python and Data Analysis Training
If you need more comprehensive training, there are many excellent online courses that cover Python and the Python data analysis environment.
Code-based training is organized as short written tutorials followed by an interactive session where you write and execute code and get immediate feedback.
- Data Camp. A Code based environment with a good combination of lessons and projects.
- Dataquest. A code based course, with specific tracks for data analysis and data scientists.
- Codecademy. A code based course
[ Of these three, I I recommend either Data Camp or Dataquest ]
Lecture based training consists primarily of videos, and you are responsible for setting up your own Python environment to practice the lessons.
- Udemy Python Series. Video lecture course
- Kahn Academy, Coursera, and many Others
Jupyter and CoLab
Jupyter is the most popular environment for doing data analysis with Python, but we will mostly be using CoLab, a variant of Jupyter created by Google.