ADM-HW2: The Best Books of All Time

In this project, we conducted an exploratory data analysis on a dataset containing information about books and their authors. The objective was to extract valuable insights from the data and explore genres, authors, publication dates, ratings, and more.

Project Structure

• main.ipynb: This Jupyter notebook contains all the answers to the research questions (RQs) and the two Bonus Points.

• main.html: This is the HTML version of the main.ipynb notebook.

• functions.py: This Python script provides all the user-defined functions used in the main.ipynb notebook.

AWSQ Folder

This folder contains the response to the Amazon Web Service Question (AWSQ).

• AWSQ.py: This Python script generates the report and measures the time to generate it.

• report.txt: This text file contains the report, including the config of the EC2 instance, the commands used, and the running time of the script on the local system and EC2 instance.

CLQ Folder

This folder contains the response to the Command Line Question (CLQ).

• CLQ_Q2.txt: This text file contains the report for question 2.

• commandline_LLM.sh: The shell script implemented by the LLM.

• commandline_original.sh: The shell script implemented by us.

• SS.png: This image file contains a screenshot of the output.

AQ.ipynb

This Jupyter notebook contains the response to the Algorithmic Question (AQ). It contains a Python function that implements an algorithm to follow the boss's instructions and report the answers to type 3 instructions.

Authors

• @Ambar Chatterjee
• @Susanna Bravi
• @Stefano Rinaldi
• @Arash Bakhshaee Babaroud