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Python Minigames

20 Questions you own this product

This free project is part of the liveProject series Python Minigames
prerequisites
Python basics • pandas basics • Jupyter Notebook basics
skills learned
data processing • user input • randomness • data filtering • CRUD operations • modularizing code • debugging
Jaya Moore
1 week · 6-8 hours per week · INTERMEDIATE
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This free project is part of the liveProject series Python Minigames explore series
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In this liveProject, you’ll use Python to create a command-line version of the classic guessing game 20 Questions. In your version of the game, the computer will have up to twenty chances to guess what animal the player is thinking of. You’ll use Jupyter notebooks to code your program and define functions that build a knowledge base in real time. Then, you’ll test and debug your code by playing against the computer.

project author

Jaya Moore
Jaya Moore is a developer enablement professional with a specialization in developer education. She has extensive experience serving organizations across the world as a technical writer, web developer, and data scientist. She has been learning and writing about Python for over six years.

prerequisites

This liveProject is for intermediate-level Python practitioners who are comfortable with the basics of manipulating strings, operating on data structures (such as lists and dictionaries), defining functions, and debugging code. To begin this liveProject, you will need to be familiar with the following:


TOOLS
  • Basic Python
  • Basic pandas
TECHNIQUES
  • Operating on strings, files, data structures
  • Storing and accessing data in lists and dictionaries
  • Control flow and conditional logic
  • Installing and importing Python modules
  • Running a Python script from the command line

you will learn

In this liveProject, you’ll build and manage a dataset that is dynamically generated during gameplay with the end-user. The skills you’ll learn throughout this project will be directly applicable to your job as a software developer, analyst or data scientist.


  • Using pandas to create and manage a dataset
  • Operating on DataFrames
  • Getting and sanitizing user input
  • Implementing randomness and conditional logic
  • Modularizing your code
  • Running your code as a command-line script

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
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