In this project I initially analyzed Star Wars movie using a separate dataset, unfortunately I lost the original file, however the results and visualizations I had gotten are still available on my LinkedIn post :

https://www.linkedin.com/posts/ethanpds_in-this-small-project-i-explored-the-global-activity-7324659638837067777-4Bsq?utm_source=share&utm_medium=member_desktop&rcm=ACoAAE4g_bYBwsz_B0R2x0tgc1aGQRZB0jU235M

I filtered the dataset for Star Wars titles and recreated key visualizations, to have a clear comparison of box office performance across the franchise. This project demonstrates my skills in data cleaning, filtering and effective visualization with pandas and matplotlib .

Goal of this analysis

<aside> 🗨️

In celebration of May the 4th earlier this year also known as Star Wars Day, I conducted on analysis of global box office performance amongst the Star Wars film franchise. As a life long Star Wars fan I intend to combine my personal passion with data management and story telling.

The goal of this analysis is to

1. Investigate whether Star Wars performs better in the U.S. (domestically) or in the international market, we re comparing the two by comparing adjusted and unadjusted gross revenues.
2. Ranking Star Wars movies in terms of global box office success to arrange movies in ascending order in terms of box office success.
3. Use clear engaging horizontal bar charts to visualize revenue comparisons across films and regions, ensuring that it can be visualized by both coders and non-coders. </aside>

Deliverables

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Deliverables:

• Sharing Format:
  • Comprehensive report with key findings and recommendations did on Notions
  • Google collab with functional codes and visualized findings.

🔍 Analysis Components

• A Python-based Google Colab notebook exploring the relationship amongst the Star Wars franchise.
• Bar chart visualizations to clearly visualize the box office earnings amongst the Star Wars movies to be able to clearly understand the differences in international gross and domestic gross.

🛠️ Tools Used

• pandas for data cleaning, filtering, and exploratory analysis
• matplotlib to plot and visualize the bar chart
• Google Colab for an efficient workflow

📤 Output & Sharing Format

• A shareable Google Colab notebook containing code, charts, and insights
• Report done using Notion </aside>

Questions to be answered

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🔹 1. Domestic vs. International Popularity

• Do Star Wars films earn more revenue domestically (U.S.) or internationally?
• Does inflation-adjusted data change the perceived popularity by region?

🔹 2. Highest-Grossing Star Wars Film

• Which Star Wars movie ranks as the top earner based on unadjusted gross?
• What role does release year play in determining total box office success?

🔹 3. Visualizing the Results

• What is the most effective way to compare gross revenues across films (e.g., horizontal bar charts)?
• Do visual trends reveal shifts in the franchise’s popularity over time? </aside>

What data do I have?

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Star Wars Box Office Dataset

• Source:

  Top Movies 2020 dataset published via GitHub, originally compiled from historical box office records.

• Data Description:

  The dataset includes a list of major films with the following key attributes:

  • Title – the name of the film
  • Gross – unadjusted box office earnings
  • Gross (Adjusted) – earnings adjusted for inflation
  • Year – release year of the film

• Limitations with the Data:

  • Not every Star Wars film is included — the dataset may exclude titles released after 2020 or less prominent entries.
  • Does not distinguish between domestic and international revenue — values are total gross only.
  • Adjusted gross calculations may vary depending on methodology (e.g., inflation index used).
  • No breakdown by region, ticket sales, or runtime — analysis is limited to revenue totals and titles only. </aside>

Data Preparation & Filtering

import pandas as pd

csvFile = '<https://raw.githubusercontent.com/csbfx/advpy122-data/master/top_movies_2020.csv>'
movies = pd.read_csv(csvFile)

# Filter for Star Wars movies only
star_wars_df = movies[movies['Title'].str.contains('Star Wars', case=False, na=False)]
print(star_wars_df)