https://github.com/namratha2301/starbucks_global_presence

Exploring the global presence of Starbucks.
https://github.com/namratha2301/starbucks_global_presence

business-analysis data-analysis data-science data-visualization matplotlib pandas pycountry

Last synced: about 2 months ago
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Exploring the global presence of Starbucks.

• Host: GitHub
• URL: https://github.com/namratha2301/starbucks_global_presence
• Owner: Namratha2301
• Created: 2024-11-03T19:46:32.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-11-03T19:51:31.000Z (3 months ago)
• Last Synced: 2024-11-03T20:28:19.537Z (3 months ago)
• Topics: business-analysis, data-analysis, data-science, data-visualization, matplotlib, pandas, pycountry
• Language: Jupyter Notebook
• Homepage: https://medium.com/@namrathameedinti/exploring-the-global-presence-of-starbucks-333fd54f8255
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Starbucks Global Presence Analysis

## Overview

This project explores the global presence of Starbucks by analyzing its store locations worldwide. It includes visualizations that highlight the distribution of stores by country, state, city, and ownership type, providing insights into Starbucks' expansion strategies and market presence.

![Untitled design-2](https://github.com/user-attachments/assets/0dd3d036-5f0c-489d-9f56-a934990d68ff)

## Table of Contents

- [Data Source](#data-source)

- [Technologies Used](#technologies-used)

- [Data Analysis](#data-analysis)

- [Visualizations](#visualizations)

- [Observations](#observations)

- [Conclusion](#conclusion)

## Data Source

The dataset used for this analysis is obtained from the Starbucks Store Locator data available on [GitHub](https://github.com/chrismeller/Starbucks-Store-Locator).

## Technologies Used

- Python

- Pandas

- Plotly Express

- Pycountry

- Matplotlib

## Data Analysis

The analysis involves the following steps:

1. Loading the Starbucks dataset.

2. Grouping the data by country, state, city, and ownership type.

3. Creating various visualizations to represent the data insights.

## Visualizations

The following visualizations are included in this project:

1. **Choropleth Map**: Displays the number of Starbucks stores worldwide by country.

   

2. **Bar Chart**: Shows the top 10 countries with the most Starbucks stores.

   

3. **Bar Chart**: Displays the top 10 states in the U.S. with the most Starbucks stores.

   

4. **Treemap**: Represents the top 10 cities with the most Starbucks stores.

   

5. **Pie Chart**: Illustrates the distribution of Starbucks stores by ownership type.

   

6. **Statistics Overview**: Provides a summary of total stores, countries, and cities.

## Observations

- The United States holds more than 50% of Starbucks locations.

- The top 10 countries account for nearly 85% of all stores.

- India, despite its large population and growing economy, does not rank among the top 10.

- Non-U.S. cities like Shanghai have a significant number of stores, with Shanghai surpassing New York City.

- Approximately 47% of stores are company-owned, with only about 2% being franchises, and around 15% operating under joint ventures.

## Conclusion

Starbucks has significantly shaped the global coffee culture since its founding in 1971. With a strong presence in the U.S. and strategic expansion into international markets, Starbucks continues to be a leader in the coffee industry. Its unique ownership structure and innovative partnerships, particularly in Asia, underscore its adaptability and commitment to growth.

## Acknowledgments

- Data source: [Starbucks Store Locator data (GitHub: chrismeller)](https://github.com/chrismeller/Starbucks-Store-Locator)