gun data analysis

gun-data.py

#!/usr/bin/env python
import csv


with open("gun-data.csv") as f:
    r = csv.reader(f)
    head = next(r)
    i_date = head.index("Date")
    i_deaths = head.index("Fatalities")
    i_type = head.index("Type of weapons")
    results = {
        "1984-1994": {
            "n_events": 0,
            "n_deaths": 0,
        },
        "1994-2004": {
            "n_events": 0,
            "n_deaths": 0,
        },
        "2004-2014": {
            "n_events": 0,
            "n_deaths": 0,
        },
    }
    n_events = 0
    n_deaths = 0
    for line in r:
        weapons = line[i_type]
        if "rifle" not in weapons.lower():
            continue
        date = line[i_date]
        year = int(date.split("/")[2])
        if year < 1900:
            year = 2000 + year
        if year > 2014 or year < 1984:
            continue
        if year > 2004:
            bucket = "2004-2014"
        elif year > 1994:
            bucket = "1994-2004"
        else:
            bucket = "1984-1994"
        results[bucket]["n_events"] += 1
        results[bucket]["n_deaths"] += int(line[i_deaths])
    print(results["1984-1994"])
    print(results["1994-2004"])
    print(results["2004-2014"])

results:

{'n_deaths': 78, 'n_events': 10}
{'n_deaths': 46, 'n_events': 7}
{'n_deaths': 78, 'n_events': 8}

So I did my own quick analysis and I think that you may have been overly restrictive in your use of rifle as the predicate, since the Assault Weapons Ban in question also banned pistols and shotguns. My results are much more in keeping with the article. https://github.com/timvisher/gun-violence-analysis

$ lein run
{:bucket "2004-2014", :incidents 23, :deaths 226}
{:bucket "1994-2004", :incidents 8, :deaths 63}
{:bucket "1984-1994", :incidents 9, :deaths 104}