Assignment 2 – Data Processing using Python and Pandas: Task description: In this assignment,

Assignment 2 – Data Processing using Python and Pandas:

Task description:

In this assignment, you will create a Jupyter notebook and use Python and Pandas to analyse and visualize a real engineering data set.

Use of generative Artificial Intelligence (AI)

The use of generative AI tools such as ChatGPT, including programming/coding assistants such as CoPilot, is strictly forbidden for all assessment tasks in EGB103 and will be considered as an act of major academic misconduct.

Unit Learning Outcomes assessed:

• ULO 1: Create your software – you will learn a programming language and how to design and implement simple algorithms.
• ULO 2: Manipulate engineering data flexibly and efficiently by creating your scripts and simple programs to handle the specific tasks.
• ULO 4: Ensure software is correct, clear, and maintainable by applying introductory-level software development principles and processes.
  Tasks:
• Use markdown to document any checks on the data to ensure that the data is clean. Hint:
• Running consistency checks is good practice before working with data sets.
• Read the clean CSV file into a Pandas data frame
• Determine the car with the maximum Engine Size and print the Make, Model and Year of that car
• Determine the average car price of all cars in the dataset
• Add a column that shows the price per Horsepower of each car
• Show a bar chart with the 10 fastest cars in order using the 0-60mph value as criteria
• Plot a histogram of engine sizes in the dataset, binning to full liters
• Show the relation of Engine size vs Torque in a scatterplot
• Make a table of all cars where the model starts with the letter ‘A’
• Plot the torque of each electric car in ascending order

All data processing should be done using the Pandas library. Everything required for this assignment is covered in the lectures and/or practical exercises (aside from where hints are provided to use specific Pandas functions), so there should be no need to use Python or Pandas features outside of what has been covered in class. Note, you will get Zero marks if you use some other programming language, library or system such as R, MATLAB or Excel.