Understanding features (October, 23 -Monday)

Today, to gain deeper insights into the dataset, I calculated frequency counts for categorical variables, including “threat_type,” “armed_with,” “was_mental_illness_related,” and “flee status.”

Here are my key observations:

  1. Regarding the “threat_type” category, it is evident that “shoot” and “threat” represent the most prevalent threat types, whereas “point,” “attack,” and “move” are comparatively less common.
  2. When examining whether victims were armed or not, it is apparent that “gun” and “knife” emerge as the predominant weapons used in these incidents. Additionally, a significant number of cases involve unarmed victims.
  3. With respect to flee status, Most cases do not involve fleeing (“not”).
  4. An analysis of the “was_mental_illness_related” category reveals that the majority of cases, approximately 79%, do not report any indication of mental illness (“False”). However, a substantial portion, around 20%, does report mental illness (“True”).

These observations might be useful in decision-making, resource allocation, and the development of policies in the relevant fields.

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