/python-prep

Our python prep content

Primary LanguageJupyter NotebookOtherNOASSERTION

The Erdős Institute

Python Prep Content

Last Updated March 26, 2023

This repository will contain all of our python prep content. Those individuals wishing to complete our Data Science Boot Camp will need to understand all of the content covered in this repository.

Repository Content

Lectures

These lectures will present python coding through a series of jupyter notebooks. Lectures have corresponding videos which can be found here, https://www.erdosinstitute.org/programs/asynchronous/python-prep. Each lecture notebook will have two versions:

  1. An empty version that you can fill in and play around with as desired,
  2. A "Complete" version that was filled in while recording the lecture video.

Lectures Order

You should complete the lectures in the following order:

  1. Introduction
  2. My First jupyter notebook
  3. Basic Data Types
  4. Strings
  5. More Complicated Data Types
  6. Shallow and Deep Copies
  7. Conditionals and Loops
  8. Writing Functions
  9. Reading and Writing to File
  10. Importing a Module or Package
  11. Basic numpy
  12. Basic pandas
  13. Basic Plotting
  14. Data File Types
  15. Troubleshooting Errors
  16. Next Steps
  17. Classes and Objects in Python (Optional)
  18. Parquet Files (Optional)
  19. ydata-profiling (Optional)

Practice Problems

This folder contains jupyter notebooks full of practice problems. Unless otherwise stated, each lecture notebook has a corresponding practice problem notebook for you to test your skills after completing the lecture. You should strive to reach a competency with the content so that you are able to complete these notebooks relatively quickly.

Practice Problems Order

You should complete the practice problem notebooks in the following order:

  1. Start Here!
  2. jupyter notebooks
  3. Data Structures Conditionals and Loops
  4. Shallow and Deep Copies
  5. Functions
  6. Writing to File and Importing a Package
  7. numpy
  8. pandas
  9. Plotting
  10. Data File Types
  11. Troubleshooting Errors
  12. Classes and Objects in Python (Optional)
  13. Parquet Files (Optional)
  14. ydata-profiling (Optional)

Skill Assessments

This folder contains a few notebooks that can serve as skill assessments. You should treat these notebooks like quizzes, meaning you should try to not refer back to the lectures or practice problems when completing them. Each notebook will have a set of solutions posted with them as well. These notebooks can be finished in any order.

Start Here!

A starting point explaining the skill assessment notebooks.

Skill Assessment 1

Focuses more on base python like loops, list comprehensions, writing functions, etc.

Skill Assessment 2

Focuses more on data analysis packages like pandas, numpy, and matplotlib.

Skill Assessment 3

A blend of base python and data analysis packages.

Data

The data folder contains the data used in the various jupyter notebooks in the repository.


Copyright Info

This repository was written for the Erdős Institute Cőde Data Science Boot Camp by Matthew Osborne, Ph. D., 2023.

Any potential redistributors must seek and receive permission from Matthew Tyler Osborne, Ph.D. prior to redistribution. Redistribution of the material contained in this repository is conditional on acknowledgement of Matthew Tyler Osborne, Ph.D.'s original authorship and sponsorship of the Erdős Institute. (see License.md)