I. Introduction
1.1 Overview and purpose
The aim and scope of this data analysis is to investigate the escalating expenses
associated with crimes during storm events, as well as the specific types of crimes that transpire
during these occurrences. By analyzing this data, we can improve our ability to anticipate the
locations where future waves of storm-related crimes are likely to occur. This, in turn, will
enable the police department to allocate its resources more effectively and promptly to the
impacted areas.
1.2 Define why you need data analysis.
The police department requires this data analysis to enhance their ability to anticipate the
location of the next surge in crime during a storm event. Additionally, we will investigate the
reasons behind the increasing costs of these crimes. By accurately predicting where the next
wave of crimes will occur during a storm event, we can determine the necessary allocation of
resources to the affected areas and calculate the associated expenses. This analysis will aid in
determining the cost-effectiveness of allocating resources to deter crime versus waiting until
after the storm.
II. Data Preparations
2.1 Name data sources
The data sources that will be used are the crime data for the city of Miami from Jan. 1,
2017, to Dec 1, 2019.
2.2 Filter through unnecessary data
The types of crimes that are committed are irrelevant to the amount of loss experienced
by the victims.
2.3 Define your parameters.
The parameters for this data analysis are storms with crimes, storms without crimes, and
the amount of loss experienced by the victims.
2.4 Identify measurement priorities.
Measurement priorities are storms with crimes, storms without crimes, amount of loss
experienced by the victims, location of crimes that occurred during storms and the location of
crimes without storms.
2.5 Ensure collected data fits the need.
