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LAB | Python Data structures

Learning Goals

This exercise allows you to practice and apply the concepts and techniques taught in class.

Upon completion of this exercise, you will be able to:

  • Use different data structures such as lists, dictionaries, sets and tuples, to store and manipulate data.
  • Access and modify data stored in data structures using indexing, slicing, or built-in methods.


Prerequisites

Before this starting this lab, you should have learnt about:
  • Basic Python syntax

  • Variables

  • Data types, operators and structures



Introduction

Welcome to your first data analytics bootcamp lab! In this lab, you will have the opportunity to dive into one of the fundamental building blocks of Python programming: data structures.

As you may already know, data structures are collections of values that can be used to organize and manipulate data more efficiently, such as lists, dictionaries, sets, and tuples.

Understanding data structures is essential to working with data in any programming language. It is a common practice to modify or manipulate data structures when performing various operations, such as filtering data, performing calculations, or extracting specific data elements.

Through a series of lab exercises, you will have the opportunity to apply the concepts and techniques learned in class and gain a solid understanding of data structures.


Happy coding! ❤️

Requirements

  • Fork this repo
  • Clone it to your machine

Getting Started

Complete the challenges in the notebook. Follow the instructions and add your code and explanations as necessary.

Submission

  • Upon completion, run the following commands:
git add .
git commit -m "Solved lab"
git push origin master
  • Paste the link of your lab in Student Portal.

FAQs