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William Playfair

Analysis of rates of murder by firearms in the US

William Playfair
Posted 3 years ago
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2 Replies
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8 Total Likes
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Data Collection

Murder by firearms

The FBI, through its criminal justice information services division, collects information on murders by types of weapon, at a state level. Statistics available are from 2011.

https://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-20

murderData = 
 Import["https://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/\
crime-in-the-u.s.-2011/tables/table-20", "Data"][[3, 2, 3, 
  2]]; murderLbl = First@murderData; murderData = 
 Most@First@Rest@murderData;
murderData[[All, 1]] = 
  Check[Interpreter["AdministrativeDivision"][#], #] & /@ 
   murderData[[All, 1]];
murderData[[12, 1]] = Entity["AdministrativeDivision", {"Illinois", "UnitedStates"}]
MapIndexed[Sequence, murderLbl]
   (*{"State", {1}, "Total murders 1", {2}, "Total firearms", {3}, "Handguns", {4}, "Rifles", {5}, "Shotguns", {6}, "Firearms (type unknown)", {7}, "Knives or cutting instruments", {8}, "Other \
weapons", {9}, "Hands, fists, feet, etc. 2", {10}}*)

Population Data

Population data is readily available in Wolfram Mathematica.

pop = EntityValue[murderData[[All, 1]], "Population"];

Legislative Control

State and legislative control data can be obtained from the National Conference of State Legislatures.

http://www.ncsl.org/Portals/1/Documents/Elections/LegisControl 2016_Apr20.pdf

Data was scrubbed and placed in variable stateComposition that holds the information on which party holds the power for the state. Finally a dataset was created holding the political control of each state.

dComp = Dataset[
  Association[(Thread[
     Rule[stateComposition[[All, 
       1]], (AssociationThread[{"abbreviation", "party"}, #] & /@ 
        stateComposition[[All, 2 ;; 3]])]])]]

GeoRegionValuePlot[(dComp[All, "party"] // Normal // 
    Normal) /. {"Dem" -> 1, "Rep" -> 2, "Divided" -> 3}, 
 ColorRules -> {1 -> Blue, 2 -> Red, 3 -> Yellow}, 
 PlotLegends -> 
  Placed[SwatchLegend[{Blue, Red, Yellow}, {"Democrat", "Republican", 
     "Divided"}, LegendFunction -> "Frame"], Bottom]]

enter image description here

Gun Freedom Index

Used Guns & Ammo Magazine data to rank states numerically based on the following categories.

  1. Right to Carry: how restrictive each state are in prohibiting carry in different locations, how readily can citizens obtain permits, etc.
  2. Modern Sporting Rifles: restrictions on semiautomatic firearms not regulated by NFA and restrictions on magazine capacity and/or accessories.
  3. NFA: The National Firearms Act (NFA) of 1934 has placed certain restrictions on the purchase of certain categories of weaponry. States can further restrict and regulate these weapons (machine guns, silencers, short-barrelled rifles and shotguns, etc..
  4. Castle Doctrine: English common law established that a man's home is his castle and has a right to defend it. Status and case law in each state can regulate and impose restrictions in a citizen's ability for self defense.
  5. Miscellaneous: issues such as purchase/registrations requirements, gun ownership percentage, availability of ranges, etc.

http://www.gunsandammo.com/network-topics/culture-politics-network/best-states-for-gun-owners-2014/

SetDirectory[NotebookDirectory[]];
gunFreedomIndexData = SemanticImport["gunfreedomindex.xlsx"];
gfi[state_] := 
 Flatten@Normal[
   Normal[gunFreedomIndexData[
      Select[#State == state &], {"Ranking", "total"}][Values]]]
gfi = gfi[#] & /@ murderData[[All, 1]];
(*data={#\[LeftDoubleBracket]1\[RightDoubleBracket],100000#\
\[LeftDoubleBracket]2\[RightDoubleBracket]/QuantityMagnitude[#\
\[LeftDoubleBracket]3\[RightDoubleBracket]]//N,#\[LeftDoubleBracket]4\
\[RightDoubleBracket],#\[LeftDoubleBracket]5\[RightDoubleBracket]}&/@(\
Flatten[#]&/@Transpose[{murderData[[All,{1,3}]],pop,gfi}])*)
ds = Dataset[Association[(Thread[Rule[data[[All, 1]], (AssociationThread[{"gunFreedomIndex", 
       "murderByFirearm"}, #] & /@ data[[All, {3, 2}]])]])]]

Auxiliary functions for Data Visualization

colorRules = {"Dem" -> (BaseStyle -> {FontColor -> White, 
       Background -> Blue}), 
   "Divided" -> (BaseStyle -> {FontColor -> Black, 
       Background -> Yellow}), 
   "Rep" -> (BaseStyle -> {FontColor -> White, Background -> Red})};
text[state_, function_] := 
 Text[dComp[state, "abbreviation"], function[state], 
  dComp[state, "party"] /. colorRules]

Data Visualization

Murder Rates by Firearms vs. Gun Control

Let's chart the murder rates vs. the gun freedom ranking. This should give us an indication if the gun control restrictions have any influence on murder rates committed with firearms.

coords[state_] := 
 ds[state][{"gunFreedomIndex", "murderByFirearm"}] // Values // Normal
lmf = LinearModelFit[coords /@ Normal[Keys[ds]], x, x];
Column[{Show[
   ListPlot[coords /@ Normal[Keys[ds]], PlotTheme -> "Detailed", 
    FrameLabel -> {"Gun Freemdom Ranking", 
      "MurderByFireArmRate (per 100k)"}, 
    Epilog -> 
     Inset[Style[
       "\!\(\*SuperscriptBox[\(R\), \(2\)]\)=" <> 
        ToString@lmf["AdjustedRSquared"]], {5, 11}], 
    PlotRangePadding -> None, PlotRange -> {{0, 52}, {0, 12}}, 
    ImageSize -> Large, 
    PlotLabel -> 
     Style["Murder Rate vs Gun Control Measures", Black, Bold]], 
   Plot[lmf[x], {x, 0, 52}], 
   Graphics[text[#, coords] & /@ Normal[Keys[ds]]]], 
  Row[{Text["Democrat", 
     BaseStyle -> {FontColor -> White, Background -> Blue}], 
    Text["    "], 
    Text["Divided", BaseStyle -> {Background -> Yellow}], 
    Text["    "], 
    Text["Republican", 
     BaseStyle -> {FontColor -> White, Background -> Red}]}]}, 
 Alignment -> Center]

enter image description here

There seems to be no correlation between murders by firearms and the gun freedom index.

Murder Rates by Firearms vs. Gun Ownership Rates

The article by Bindu Kalesan, et al "Gun Ownership and social culture" provide some data points on the gun ownership rates by state.

gunOwnerShip = Import["GunOwnershipRate.xlsx", {"Data", 1}]; 
gunOwnerShip[[All, 1]] = 
 Interpreter["AdministrativeDivision"][#] & /@ gunOwnerShip[[All, 1]];
go = Dataset[Association[Rule[#1, #2] & @@@ gunOwnerShip]]
gof[state_] := {go[state], ds[state]["murderByFirearm"]}
lmf = LinearModelFit[gof /@ Normal[Keys[ds]], x, x];
Column[{Show[
   ListPlot[gof /@ Normal[Keys[ds]], PlotTheme -> "Detailed", 
    FrameLabel -> {"Gun Ownership (%)", 
      "MurderByFireArmRate (per 100k)"}, 
    Epilog -> 
     Inset[Style[
       "\!\(\*SuperscriptBox[\(R\), \(2\)]\)=" <> 
        ToString@lmf["AdjustedRSquared"]], {60, 11}], 
    PlotRangePadding -> None, ImageSize -> Large, 
    PlotRange -> {{0, 70}, {0, 12}}, 
    PlotLabel -> 
     Style["Murder Rate vs Gun Ownership (%)", Black, Bold]], 
   Plot[lmf[x], {x, 0, 70}], 
   Graphics[text[#, gof] & /@ Normal[Keys[ds]]]], 
  Row[{Text["Democrat", 
     BaseStyle -> {FontColor -> White, Background -> Blue}], 
    Text["    "], 
    Text["Divided", BaseStyle -> {Background -> Yellow}], 
    Text["    "], 
    Text["Republican", 
     BaseStyle -> {FontColor -> White, Background -> Red}]}]}, 
 Alignment -> Center]

enter image description here

In this case, again, we don't see a correlation between citizen gun ownership and murder rates. We can't say the same regarding the availability of guns to law abiding citizens.

gRestriction[state_] := {ds[state]["gunFreedomIndex"], go[state]};
lmf = LinearModelFit[gRestriction /@ Normal[Keys[ds]], x, 
  x]; Column[{Show[
   ListPlot[gRestriction /@ Normal[Keys[ds]], PlotTheme -> "Detailed",
     FrameLabel -> {"Gun Freedom Ranking", "Gun Ownership (%)"}, 
    Epilog -> 
     Inset[Style[
       "\!\(\*SuperscriptBox[\(R\), \(2\)]\)=" <> 
        ToString@lmf["AdjustedRSquared"]], {5, 48}], 
    PlotRangePadding -> None, ImageSize -> Large, 
    PlotRange -> {{0, 52}, {0, 70}}, 
    PlotLabel -> 
     Style["Gun Ownership (%) vs. Gun Freedom Ranking", Black, Bold]],
    Plot[lmf[x], {x, 0, 52}], 
   Graphics[text[#, gRestriction] & /@ Normal[Keys[ds]]]], 
  Row[{Text["Democrat", 
     BaseStyle -> {FontColor -> White, Background -> Blue}], 
    Text["    "], 
    Text["Divided", BaseStyle -> {Background -> Yellow}], 
    Text["    "], 
    Text["Republican", 
     BaseStyle -> {FontColor -> White, Background -> Red}]}]}, 
 Alignment -> Center]

enter image description here

Let's explore the data against socioeconomic factors now.

Murder Rates vs Income Inequality

The Gini Index is a measure of income inequality:

gini[state_] := {EntityValue[state, "GiniIndex"], 
  ds[state]["murderByFirearm"]}
lmf = LinearModelFit[gini /@ Normal[Keys[ds]], x, x]
Column[{Show[
   ListPlot[gini /@ Normal[Keys[ds]], PlotTheme -> "Detailed", 
    FrameLabel -> {"Gini Index", "MurderByFireArmRate (per 100k)"}, 
    Epilog -> 
     Inset[Style[
       "\!\(\*SuperscriptBox[\(R\), \(2\)]\)=" <> 
        ToString@lmf["AdjustedRSquared"]], {0.53, 8}], 
    PlotRangePadding -> None, ImageSize -> Large, 
    PlotRange -> {{0.4, 0.55}, {0, 12}}, 
    PlotLabel -> Style["Murder Rate vs Gini Index", Black, Bold]], 
   Plot[lmf[x], {x, 0.4, 0.55}], 
   Graphics[text[#, gini] & /@ Normal[Keys[ds]]]], 
  Row[{Text["Democrat", 
     BaseStyle -> {FontColor -> White, Background -> Blue}], 
    Text["    "], 
    Text["Divided", BaseStyle -> {Background -> Yellow}], 
    Text["    "], 
    Text["Republican", 
     BaseStyle -> {FontColor -> White, Background -> Red}]}]}, 
 Alignment -> Center]

enter image description here

Murder Rate vs. Poverty Level

Poverty level data was obtained from the Census Bureau. Numbers represent estimated number of individuals in 2009 living below the poverty level. (http://www2.census.gov/library/publications/2011/compendia/statab/131ed/tables/12s0709.xls)

    stateRules = 
     Thread[Rule[
       EntityValue[
        EntityList[
         EntityClass["AdministrativeDivision", "AllUSStatesPlusDC"]], 
        "StateAbbreviation"], 
       EntityList[
        EntityClass["AdministrativeDivision", "AllUSStatesPlusDC"]]]]

    povertyLevel = 
     Dataset[Association[
       Rule[#1, #2] & @@@ {{"AL", 17.5}, {"AK", 9.}, {"AZ", 16.5}, {"AR", 
           18.8}, {"CA", 14.2}, {"CO", 12.9}, {"CT", 9.4}, {"DE", 
           10.8}, {"DC", 18.4}, {"FL", 14.9}, {"GA", 16.5}, {"HI", 
           10.4}, {"ID", 14.3}, {"IL", 13.3}, {"IN", 14.4}, {"IA", 
           11.8}, {"KS", 13.4}, {"KY", 18.6}, {"LA", 17.3}, {"ME", 
           12.3}, {"MD", 9.1}, {"MA", 10.3}, {"MI", 16.2}, {"MN", 
           11.}, {"MS", 21.9}, {"MO", 14.6}, {"MT", 15.1}, {"NE", 
           12.3}, {"NV", 12.4}, {"NH", 8.5}, {"NJ", 9.4}, {"NM", 
           18.}, {"NY", 14.2}, {"NC", 16.3}, {"ND", 11.7}, {"OH", 
           15.2}, {"OK", 16.2}, {"OR", 14.3}, {"PA", 12.5}, {"RI", 
           11.5}, {"SC", 17.1}, {"SD", 14.2}, {"TN", 17.1}, {"TX", 
           17.2}, {"UT", 11.5}, {"VT", 11.4}, {"VA", 10.5}, {"WA", 
           12.3}, {"WV", 17.7}, {"WI", 12.4}, {"WY", 9.8}} /. stateRules]]
poverty[state_] := {povertyLevel[state], ds[state]["murderByFirearm"]}
lmf = LinearModelFit[poverty /@ Normal[Keys[ds]], x, x]
Column[{Show[
   ListPlot[poverty /@ Normal[Keys[ds]], PlotTheme -> "Detailed", 
    FrameLabel -> {"Individuals under Poverty Line (%)", 
      "MurderByFireArmRate (per 100k)"}, 
    Epilog -> 
     Inset[Style[
       "\!\(\*SuperscriptBox[\(R\), \(2\)]\)=" <> 
        ToString@lmf["AdjustedRSquared"]], {23, 6}], 
    PlotRangePadding -> None, ImageSize -> Large, 
    PlotRange -> {{5, 25}, {0, 12}}, 
    PlotLabel -> Style["Murder Rate vs Poverty Level", Black, Bold]], 
   Plot[lmf[x], {x, 5, 25}], 
   Graphics[text[#, poverty] & /@ Normal[Keys[ds]]]], 
  Row[{Text["Democrat", 
     BaseStyle -> {FontColor -> White, Background -> Blue}], 
    Text["    "], 
    Text["Divided", BaseStyle -> {Background -> Yellow}], 
    Text["    "], 
    Text["Republican", 
     BaseStyle -> {FontColor -> White, Background -> Red}]}]}, 
 Alignment -> Center]

enter image description here

Murder Rates vs Race Composition

Population estimates by race were obtained from the US Census Bureau. (https://www.census.gov/popest/data/state/asrh/2014/index.html)

  race = Import["PEP_2011_PEPSR5H.xls", {"Data", 1}];
  racelbl = Rest@First@race; race = Rest@Rest@race;
  race[[All, 1]] = 
    Interpreter["AdministrativeDivision"][#] & /@ race[[All, 1]];
  dsRace = Dataset[
    Association[
     Thread[Rule[race[[All, 1]], 
       AssociationThread[racelbl, #] & /@ race[[All, 2 ;;]]]]]]
aaRate[state_] := {100 dsRace[state, "africanamericanRate"], 
  ds[state, "murderByFirearm"]}
lmf = LinearModelFit[aaRate /@ Normal[Keys[ds]], x, x]
Column[{Show[
   ListPlot[aaRate /@ Normal[Keys[ds]], PlotTheme -> "Detailed", 
    FrameLabel -> {"African American Population (%)", 
      "MurderByFireArmRate (per 100k)"}, PlotRangePadding -> None, 
    ImageSize -> Large, PlotRange -> {{0, 60}, {0, 12}}, 
    Epilog -> 
     Inset[Style[
       "\!\(\*SuperscriptBox[\(R\), \(2\)]\)=" <> 
        ToString@lmf["AdjustedRSquared"]], {50, 10}], 
    PlotLabel -> 
     Style["Murder Rate vs African American Population(%)", Black, 
      Bold]], Plot[lmf[x], {x, 0, 60}], 
   Graphics[text[#, aaRate] & /@ Normal[Keys[ds]]]], 
  Row[{Text["Democrat", 
     BaseStyle -> {FontColor -> White, Background -> Blue}], 
    Text["    "], 
    Text["Divided", BaseStyle -> {Background -> Yellow}], 
    Text["    "], 
    Text["Republican", 
     BaseStyle -> {FontColor -> White, Background -> Red}]}]}, 
 Alignment -> Center]

enter image description here

The Pew Hispanic center monitors the trends of hispanic population in the US. Breakout of the population population by states is availabe t their website. http://www.pewhispanic.org/states/

hispanicData = 
  Import["http://www.pewhispanic.org/files/states/xls/ALL_11.xlsx", \
{"Data", 1}];
hispanicDataLbl = hispanicData[[5]];
hispanicData = hispanicData[[7 ;;]];
hispanicData[[All, 1]] = 
  Interpreter ["AdministrativeDivision"][#] & /@ 
   hispanicData[[All, 1]];
dsHispanic = 
 Dataset[Association[
   Thread[Rule[hispanicData[[All, 1]], hispanicData[[All, 3]]]]]];
hispanic[state_] := {100 dsHispanic[state], 
  ds[state, "murderByFirearm"]}
lmf = LinearModelFit[hispanic /@ Normal[Keys[ds]], x, x]

Column[{Show[
   ListPlot[hispanic /@ Normal[Keys[ds]], PlotTheme -> "Detailed", 
    FrameLabel -> {"Hispanic Population (%)", 
      "MurderByFireArmRate (per 100k)"}, PlotRangePadding -> None, 
    ImageSize -> Large, PlotRange -> {{0, 60}, {0, 12}}, 
    Epilog -> 
     Inset[Style[
       "\!\(\*SuperscriptBox[\(R\), \(2\)]\)=" <> 
        ToString@lmf["AdjustedRSquared"]], {55, 3}], 
    PlotLabel -> 
     Style["Murder Rate vs Hispanic Population(%)", Black, Bold]], 
   Plot[lmf[x], {x, 0, 60}], 
   Graphics[text[#, hispanic] & /@ Normal[Keys[ds]]]], 
  Row[{Text["Democrat", 
     BaseStyle -> {FontColor -> White, Background -> Blue}], 
    Text["    "], 
    Text["Divided", BaseStyle -> {Background -> Yellow}], 
    Text["    "], 
    Text["Republican", 
     BaseStyle -> {FontColor -> White, Background -> Red}]}]}, 
 Alignment -> Center]

enter image description here
POSTED BY: William Playfair
Answer
2 Replies
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The Moderation Team is removing several comments that are off topic and might also be regarded as inflammatory. We recognize that this is a politically fraught topic and request that comments be kept within scope and address the analysis rather than individuals' political opinions.
POSTED BY: Moderation Team
Answer
Stephan Foley
Stephan Foley
Posted 3 years ago

Hi, nice looking analysis. I would work a bit on the map projection (although understanding map projections is easily a few weeks study!). Maybe something like:

GeoRegionValuePlot[
    ...
    GeoProjection -> {
        "LambertAzimuthal",
        "Centering" -> ....
    },
    ....
]

Here is a good stackexchange example. Also useful is An Album of Map Projections.

Although I might be misunderstanding your analysis, you state:

There seems to be no correlation between murders by firearms and the gun freedom index.

but, common sense would seem to say with more guns, you get more violence. For example, the following paper states:

While many factors influence the rate of gun-related violence in any state, comparison of these rankings with the aggregate ranking of states based on gun-violence outcomes reveals a significant correlation between weak state gun laws and increased gun violence in a state. Across the key gun-violence indicators that we analyzed, the 10 states with the weakest gun laws collectively have a level of gun violence that is more than twice as high as the 10 states with the strongest gun laws.

Source: America Under the Gun - A 50-State Analysis of Gun Violence and Its Link to Weak State Gun Laws
POSTED BY: Stephan Foley
Answer

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