Skip to content

luc-codes/project382_lists

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Frida Kahlo Retrospective Off-Platform Project

Overview

This project was created as part of a Python programming exercise focused on working with lists, tuples, the zip() function, and the range() function.

The scenario is based on creating an audio tour for a retrospective exhibition of the work of Mexican artist Frida Kahlo. The goal is to organize a collection of paintings by pairing each painting with its creation date and assigning each artwork a unique audio tour identification number.

The final output is a master list containing:

  • The audio tour number
  • The painting title
  • The year the painting was created

Project Objectives

The program demonstrates how to:

  • Create and manipulate Python lists
  • Combine related lists using zip()
  • Convert zipped objects into lists
  • Add new elements using .append()
  • Determine the number of items in a list using len()
  • Generate sequential identifiers using range()
  • Create a final structured dataset

Technologies Used

  • Python 3

No external libraries or dependencies are required.


Project Structure

PROJECT382_LISTS |_data |_notebooks | |_explore.ipynb |_src | |_project382_lists.py |venv |.gitignore |_README.md |_requirements.txt


Dataset

The project uses a collection of artwork records representing paintings included in a museum audio tour.

Each artwork record contains:

  • Artwork title
  • Year of creation
  • Audio tour identifier

The data is organized programmatically using Python lists and tuples, then transformed into a structured master list for the tour system.

How to Run

Make sure Python 3 is installed.

Run: project382_lists.py

Technologies

  • Python 3

Author

Created as a Python practice project following the Codecademy syllabus of 'Data and Programming Foundations for AI Skill Path'.

About

Frida Kahlo artworks catalogue (Python practice project following the Codecademy syllabus of 'Data and Programming Foundations for AI Skill Path')

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors