This project focuses on exploring and analyzing a dataset of episodes from the American version of the popular TV show "The Office". The project aims to understand how the popularity and quality of the series varied over time by examining different characteristics of each episode, including ratings, viewership, guest stars, and more.
The dataset used in this project, which was downloaded from Kaggle, contains information on 201 episodes over nine seasons. The information provided for each episode includes its canonical episode number, the season in which it appeared, its title and description, the average IMDB rating, the number of votes, the number of US viewers in millions, the duration in minutes, the airdate, the guest stars in the episode (if any), the director of the episode, the writers of the episode, a True/False column for whether the episode contained guest stars, and the ratings scaled from 0 (worst-reviewed) to 1 (best-reviewed).
By analyzing this dataset, we can gain insights into how different factors impacted the popularity and quality of the show. For example, we may discover that episodes with guest stars tended to have higher viewership or ratings, or that certain directors or writers were associated with particularly successful or popular episodes. Overall, this project provides an interesting and in-depth analysis of one of the most popular and beloved TV shows of all time.