Data preparation involved the creation of time series longitudinal, 1 day level count data of the following attributes: . I All visits are recorded with OFFENSE DATE attributes. << Move this to introduction >> 

Exploratory data analysis

Exploratory data analysis involved (a)  generating descriptive statistics of the dataset. (b) Time series visualisation of the observed variable across the full dataset. (c) A simple X-Y plot of locations (the independent variable, ordered from high to low) against the count of visits attributable to the location.  I also performed simple ratio analysis of the service volume information, by the locations that were attributed to 10 or more calls per day. 

Model discovery and fitting

I attempted to find the appropriate stochastic model iteratively fitting the service volume data to the distribution and observing result of the ChiSquare test.
I then attempted to fit the data against a polynomial and reported the result.

Longitudinal analysis

I performed longitudinal data analysis, yearwise, with a focus on locations. I selected the top “high needs” locations that were common in each of the ten years. 

Visualisation

I then geocoded the locations, by (unique) street addresses and plotted the result geospatially. 

Section

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