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Quantitative analyses can have a significant impact on initiating change within one's community. When analyzed responsibly, data can provide evidence to understand difficult social issues correctly. In this project, you will leverage publicly available data to interpret crime patterns within the city of San Francisco. The dataset used in this project is [hosted on Kaggle](https://www.kaggle.com/san-francisco/sf-police-calls-for-service-and-incidents) and updated daily. Note - some of the original column names are altered for adherence to a standard naming scheme.
- 1The power of data science
- 2First poke and prod
- 3Mutating join
- 4Inspect frequency trends
- 5Correlation between trends
- 6Filtering joins
- 7True crime
- 8Grand theft auto
- 9Density map
PhD Student at University of California, San Francisco
Will Connell is a Pharmaceutical Sciences and Pharmacogenomics doctorate student at UCSF. He is a hobbyist in all things data science and advocates for project-based learning and peer-to-peer mentorship.
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Lloyds Banking Group
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