Multiple people shot at UNLV; suspect dead
Shooting at University of Nevada, Las Vegas Campus Leaves Multiple People Injured
Tragedy struck the University of Nevada, Las Vegas campus on Wednesday afternoon when several individuals were shot, according to local law enforcement officials. The suspect responsible for the incident has been confirmed deceased, but their identity remains unknown.
Las Vegas Metropolitan Police Sheriff Kevin McMahill stated that the motive behind the shooting is currently unclear. “No more threat to the community. The suspect is deceased. Right now, we know there are three victims, but the extent of their injuries is still unknown,” he said. “We will keep you updated as we gather more information.”
The incident sparked a swift and massive response from law enforcement, as captured in various videos shared online.
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URGENT: From Sheriff Kevin McMahill: “No more threat to the community. The suspect is deceased. Right now, we know there are 3 victims, but the extent of their injuries is still unknown. That number could change. We will update you when we know more.” https://t.co/Y3jT9VcNFz
— LVMPD (@LVMPD) December 6, 2023
This is a developing news story; refresh the page for updates.
What are some key features of Pandas when it comes to data cleaning?
Pandas is a powerful data manipulation library in Python. It provides data structures and functions to efficiently manipulate and analyze structured data. Some of the key features of Pandas include:
1. DataFrame: The main data structure in Pandas, which is a two-dimensional table of data with columns and rows. It allows you to easily manipulate and analyze data.
2. Data Cleaning: Pandas provides functions for handling missing data, removing duplicates, and transforming data into the desired format.
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4. Data Visualization: Pandas has integration with other libraries such as Matplotlib and Seaborn, allowing you to create various visualizations to explore and present your data.
5. Time Series Analysis: Pandas has built-in support for working with time series data, including the ability to easily manipulate and analyze data with dates and times.
Overall, Pandas is a versatile library that makes it easier to work with and analyze data in Python.
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