challengeQuestions

Challenge questions for GWC participants. Jupyter notebook file content follows DataCamp's Introduction to Python for Data Science and Intermediate Python for Data Science. Challenge questions made by Stephanie Thiede, Rucheng Diao, Zena Lapp, Brooke Wolford, and Marlena Duda of the University of Michigan. Solutions to select challenge questions.

Instructions for use:

Via Terminal

1. Download .ipynb file to your computer
2. Identify the path to your file (e.g. /GWC/Desktop/test.ipynb)
3. Open the Terminal application
4. Type the command below and press enter

jupyter notebook <path/to/file.ipynb>

5. The file should open in a web browser

Via the Web

1. Download the .ipynb file to your computer
2. Go to jupyter.org
3. Click the orange button “try it on your browser”
4. Click the upload button and upload the .ipynb (you have to click upload button when it turns blue)
5. Click on file name in the list of files and your notebook will open

Introduction to Python for Data Science Challenge Questions

Basics and Lists

1. Basics_and_Lists_Challenge_Question_1.ipynb: practice declaring variables, accessing items in a list and printing messages to the screen by creating your own Mad Lib
2. Basics_and_Lists_Challenge_Question_2.ipynb: practice accessing items in a list, type casting, and simple mathematical calculations by calculating how the price of a car depreciates over time
3. Basics_and_Lists_Challenge_Question_3.ipynb: practice declaring variables, accessing items in a list and printing messages to the screen by spelling your name with a list of lists
4. Basics_and_Lists_Challenge_Question_4.ipynb: practice selecting and subetting a list, and changing elements in a list by preparing a meal prep menu. Preview functions and packages by using matplotlib to visualize results

Functions and Packages and NumPy

1. Functions+Methods+Packages+Numpy_ChallengeProblem.ipynb: understand why numpy arrays are fast and efficient and practice using functions, methods, and packages

Intermediate Python for Data Science Challenge Questions

Matplotlib

1. matplotlib_challenge_problems.ipynb: practice using matplotlib to visualize college degrees awarded in different fields

Dictionaries and Pandas

Coming soon

Putting it all together

1. example_script_CQ.py: practice with user defined functions, data types, scripting

#open a terminal window and cd to directory with this file
#open this file in a text editor
emacs -nw example_script_CQ.py

#using keyboard arrows to navigate around and make changes, answer challenge questions
#to test the script
python example_script_CQ.py