Role: Data visualization
Tools used: Python Jupyter Notebook
Libraries used: Pandas Matplotlib Seaborn
Purpose:
We wanted to analyze the severity of crime in different areas of San Diego, so we created various line, bar, and heat plots to analyze it. Our hypothesis was that there would be more serious crime in downtown, compared to in rural areas of San Diego.
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Back to projectsAs part of this group project, I helped with the data visualization, like creating bar charts, and grouping the violent and non-violent crime.
Specifically, to get an idea of our dataset, I first made a chart to find out how many different types of crime there were, and how many of each.
Then, I organized it by agency of the crime, and how many crimes there were in each.
In total, from the dataset, there were 11 agencies and 14 different types of crime. Additionally, because we were using two different datasets with different crimes, we decided to generalize it into violent crime and property crime, and I made a chart showing the final cleaned up result:
I also made a bar chart to display the tabled result of how many violent crimes and property crimes there were in each of the 11 agencies.
