I analyzed 1 million NYC car crashes (2017–2022) in Power BI — the borough fatality data is not what you'd expect [OC] Statistics

What This Visualization Shows

This data visualization displays "I analyzed 1 million NYC car crashes (2017–2022) in Power BI — the borough fatality data is not what you'd expect [OC]" and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on OC: Built this in Power BI using 1 million NYC

collision records from Datdotgov (2017–2022)

Key findings that surprised me:

\- Staten Island has the HIGHEST fatality rate

at 0.49% — nearly double Manhattan's 0.33%

despite having the fewest total crashes

\- Belt Parkway is the most dangerous street —

14,649 collisions and 36 deaths

\- Midday 10am–3pm has MORE crashes than rush

hour — completely counterintuitive

\- Backhoe loaders and tow trucks: 100% fatality

rate on every collision

\- Driver inattention is #1 cause across all

5 boroughs without exception

Tools used: Power BI Desktop, Power Query, DAX

Data source: DataDOTgov (publicly available)

Happy to answer any questions about the

methodology or how the measures were built., which allows us to understand complex relationships and insights within the data through visual storytelling.

Deep Dive into the Topic

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Data Analysis and Insights

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