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Today I wrote and published my first Medium article ‘Crime On the Rise?’. Give it a read and share your thoughts.

Here are a few highlights:

Crime happens across the globe and it fosters various consequences that may impact home prices or other neighborhood characteristics. Using Python and Jupyter Notebooks I seek to analyze California criminal records to gain further insight.

In summary, crime in Los Angeles throughout this time frame does not indicate any type of gender or ethnic biases. Both men and women fall victim to criminal behavior equally across their respective age groups. The most frequent type of crime is ‘Battery – Simple Assault’. The most commonly used weapon across crimes is ‘Strong-arm (hands, fist, feet, or bodily force). Although criminal behavior seemed to see its peak in Los Angeles in 2011, the crime rate has been increasing since (at least up to 2015).

I practiced:

  • Pandas data wrangling and crosstabs
  • Matplotlib, Seaborn, and Pandas plotting
  • Geographical plotting using Basemap

The entire notebook, including code and comments, can be found here My Colab Notebook.

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