Author Archives: MantasCode

The Spread of ShotSpotter in Chicago 2017 – 2022

ShotSpotter is gunshot detection technology that uses sophisticated acoustic sensors to detect, locate and alert law enforcement agencies and security personnel about illegal gunfire incidents in real-time. ShotSpotter uses acoustic sensors that are strategically placed in an array of approximately 20 sensors per square mile. These sensors are connected wirelessly to ShotSpotter’s centralized, cloud-based application to reliably detect and accurately triangulate gunshots.

Data is from https://data.cityofchicago.org/Public-Safety/Violence-Reduction-Shotspotter-Alerts/3h7q-7mdb. CARTO was used to create animated map of ShotSpotter alerts.

   

Chicago ShotSpotter coverage as of 7/17/2022

Chicago Victims of Homicides and Non-Fatal Shootings 2010 – 2022

A look into Chicago’s individual-level homicide and non-fatal shooting victimizations. The dataset was published on the Chicago Data Portal and comes from the Chicago Police Department (CPD). Accessed 7/4/2022. Click on larger visualizations for full size. Carto and Google Charts were used.

12 years of shootings..

Victims by race..

Daily Counts

Aggregates by Month, Day of Week, and Hour of Day. 2010 – 2022..
Summer months accrue the most shootings. Suns out guns out.

Most shootings happen over the weekends.

Night time is the most popular time for a shooting.

Age Group..

Race..

Type..

Community..

Iowa’s Liquor Sale Maps and Visualizations 2020

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A look into Iowa’s liquor sales for the last 2.5 years. Time spans from January 2018 through June 2020. The data can be found at data.iowa.gov. Click on images below to enlarge.

Distinct Coordinate by Volume Sold (Liters)

Pandemic Upswing

Top Bottle Sold by Distinct Location

Top Bottle

Top Category Per Distinct Location

C# Console Application was used to parse, aggregate, and output the data into desired structure for Google Charts and Carto. The script below can be used as a reference if you would like to investigate Iowa’s liquor sale data yourself. Note that this particular script will only output the data source of the last map in this post (Top Category Per Distinct Location sized by Bottles Sold).

using CsvHelper;
using System;
using System.Collections.Generic;
using System.Globalization;
using System.IO;
using System.Linq;
using System.Text;
using System.Text.RegularExpressions;
using System.Threading.Tasks;
 
namespace IowaSpirits2018plus
{
    class Program
    {
        static void Main(string[] args)
        {
            Console.WriteLine("Iowa Spirits..");
            Console.BufferHeight = 4000;
            Dictionary<string, Dictionary<string, int>> dictCoord_Item_Count = new Dictionary<string, Dictionary<string, int>>();
            string lastdate = "";
            using (var reader = new StreamReader("C:\\IOWASPIRITS\\iowaspirits2018plus.csv"))
            using (var csv = new CsvReader(reader, CultureInfo.InvariantCulture))
            {
                csv.Read();
                csv.ReadHeader();
                while (csv.Read())
                {
                    string date = csv.GetField("Date").ToString();
                    if ( lastdate != date)
                        Console.WriteLine(date);
                    lastdate = date;
                    DateTime fDate = csv.GetField("Date");
                    string city = csv.GetField("City").ToString();
                    string categoryName = csv.GetField("Category Name").ToString();
                    string bottlesSold = csv.GetField("Bottles Sold").ToString();
                    int iBottlesSold = int.Parse(csv.GetField("Bottles Sold").ToString());
                    string litersSold = csv.GetField("Volume Sold (Liters)").ToString();
                    string itemDescription = csv.GetField("Item Description").ToString();
                    string storelocation = csv.GetField("Store Location").ToString();
                    storelocation = Regex.Replace(storelocation, "POINT \\(", "");
                    storelocation = Regex.Replace(storelocation, "\\)", "");
                    storelocation = Regex.Replace(storelocation, " ", ",");
 
                    if (dictCoord_Item_Count.ContainsKey(storelocation))
                    {
                        Dictionary&lt;string, int&gt; existingDict = new Dictionary&lt;string, int&gt;();
                        existingDict = dictCoord_Item_Count[storelocation];
                        if (existingDict.ContainsKey(categoryName))
                        {
                            int existingBottleSold = existingDict[categoryName];
                            existingBottleSold += iBottlesSold;
                            existingDict[categoryName] = existingBottleSold;
                        }
                        else
                        {
                            existingDict.Add(categoryName, iBottlesSold);
                        }
                        dictCoord_Item_Count[storelocation] = existingDict;
                    }
                    else
                    {
                        Dictionary&lt;string, int&gt; tempDictItemCount = new Dictionary&lt;string, int&gt;();
                        tempDictItemCount.Add(categoryName, iBottlesSold);
                        dictCoord_Item_Count.Add(storelocation, tempDictItemCount);
                    }
                }
            }
            foreach ( string parent_key in dictCoord_Item_Count.Keys)
            {
                Console.Write(parent_key + ",");
                foreach (var item in dictCoord_Item_Count[parent_key].OrderByDescending(r =&gt; r.Value))
                {
                    Console.Write("{0}, {1}", item.Key, item.Value);
                    break;
                }
                Console.WriteLine();
            }
        }
    }
}

UK Bicycle Theft in Major Cities 2017 to 2020

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Revisiting UK’s bicycle thefts. The data comes from https://data.police.uk/. The date ranged used was from May 2017 through April 2020. All surrounding police forces were used to obtain a comprehensive list of bicycle theft incidents. Previous post from 2016 can be found here. Carto was used to render the maps. Cities include: London, Manchester, Birmingham, and Bristol

London Click to enlarge 3.12 mb

London Click to enlarge 3.73 mb

Manchester Click to enlarge 1.07 mb

Birmingham Click to enlarge 706 kb

Bristol Click to enlarge 656 kb

If you would like to create your own UK crime maps, and are frustrated at the way data.police.uk presents its data. You may use this simple C# console application to aggregate it yourself. Simply paste the downloadables into a directory called LONDON4, and use the script below to generate an output file containing incidents from multiple police forces. Cheers.

C# Console Application

string dirPath = @"C:\LONDON4\";
List dirs = new List(Directory.EnumerateDirectories(dirPath));
Dictionary&lt;string, int&gt; dictUniqueCrime = new Dictionary&lt;string, int&gt;();
foreach (var dir in dirs)
{
    Console.WriteLine("{0}", dir.Substring(dir.LastIndexOf("\\") + 1));
    string filepath = @"C:\LONDON4\";
    filepath += dir.Substring(dir.LastIndexOf("\\") + 1);
    Console.WriteLine(filepath);
    string line;
    string[] fileEntries = Directory.GetFiles(filepath);
    foreach (string fileName in fileEntries)
    {
        Console.WriteLine(fileName);
        System.IO.StreamReader file =
            new System.IO.StreamReader(fileName);
        while ((line = file.ReadLine()) != null)
        {
            string[] parts = line.Split(',');
            string month = parts[1];
            string longitude = parts[4];
            string latitude = parts[5];
            string crimetype = parts[9];
            if (crimetype == "Bicycle theft")
            {
                string lines = month + "-1, " + longitude + ", " + latitude + "";
                System.IO.StreamWriter file1 = new System.IO.StreamWriter("C:\\Airplanes\\____BRITISHBICYCLES.csv", true);
                file1.WriteLine(lines);
                file1.Close();
            }
        }
        file.Close();
    }
}

Subreddit Relationships by Strong User Overlap

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Checking out some strong subreddit relationships stemming from a chosen root subreddit. The relationships below are ordered by User Overlap Scores from subredditstats.com. An interesting way of discovering related subreddits based on user overlap.

AgainstHateSubreddits

ConsumeProduct

Interesting dichotomy of users between AgainstHateSubreddits and ConsumeProduct.


ProtectAndServe

JoeRogan top 5 of 3

Sino top 5 and 3

Coronavirus top 5 and 3

These glimpses use the User Overlap scores from https://subredditstats.com/subreddit-user-overlaps. Look up a subreddit yourself, for fun.