https://github.com/mr-chang95/sf_data_visualization

In this personal project, I am interested in examining all of the active businesses in the San Francisco Bay Area while performing some simple data visualizations, mainly on categorical variables.
https://github.com/mr-chang95/sf_data_visualization

business data-analysis data-visualization jupyter-notebook pandas python san-francisco

Last synced: 4 days ago
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In this personal project, I am interested in examining all of the active businesses in the San Francisco Bay Area while performing some simple data visualizations, mainly on categorical variables.

• Host: GitHub
• URL: https://github.com/mr-chang95/sf_data_visualization
• Owner: Mr-Chang95
• Created: 2022-01-11T04:38:13.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-02-07T20:27:03.000Z (almost 3 years ago)
• Last Synced: 2024-11-28T04:14:28.577Z (2 months ago)
• Topics: business, data-analysis, data-visualization, jupyter-notebook, pandas, python, san-francisco
• Language: Jupyter Notebook
• Homepage:
• Size: 23.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# San Francisco Business Data Analysis And Visualization

## by Daniel Chang

## Project Description

For this project, I am interested in analyzing businesses that have physical locations in the Bay Area. Mainly, those located in San Francisco. I am going to put a lot of focus on the industries of these businesses. For somewhere like SF, my initial thought was that the most popular industry would be financial services. I will then examine the locations of these businesses and industries. Perhaps, each area has a higher concentration of a particular industry than another. 

## Dataset

This dataset contains 28,3369 loans with 32 variables for each business, including 'City', 'Source Zipcode', 'Location Start Date','Location End Date', 'NAICS Code Description', 'Neighborhoods - Analysis Boundaries'.

## Summary of Findings

During my project, I found that the most popular industry in SF/Bay Area is real estate, rental & leasing services, then the professional, scientific and technical services. The most popular zip code is 94110, while the most popular boundary is the Financial District/South Beach. In most zip codes and boundaries, the real estate, rental & leasing industry is the most dominant. We also found that the most businesses (active) opened their location in the 1990s.  

## Licensing, Authors, Acknowledgements

I would like to give special thanks to the San Francisco government for making this dataset free on their [website](https://data.sfgov.org/widgets/g8m3-pdis).