Analysing data

Prison Helicopter Escapes

I chose this project because it is set as part of the Dataquest course optional projects. It's interesting because it:

1. provides an opportunity to practice skills learnt to date
2. provides an opportunity to work with Jupyter notebook
3. seeks to analyse an unusual dataset which I didn't even know existed!

It's interesting also because the analysis might provide information for law enforcement agencies to prevent escapes of this kind.

We begin by importing some helper functions.

from helper import *

Get the data

Now, let's get the data from the [List of helicopter prison escapes] (https://en.wikipedia.org/wiki/List_of_helicopter_prison_escapes) Wikipedia article.

url = "https://en.wikipedia.org/wiki/List_of_helicopter_prison_escapes"
data = data_from_url(url)

Let's print the first three rows.

for row in data[:3]:
    print(row)

['August 19, 1971', 'Santa Martha Acatitla', 'Mexico', 'Yes', 'Joel David Kaplan Carlos Antonio Contreras Castro', "Joel David Kaplan was a New York businessman who had been arrested for murder in 1962 in Mexico City and was incarcerated at the Santa Martha Acatitla prison in the Iztapalapa borough of Mexico City. Joel's sister, Judy Kaplan, arranged the means to help Kaplan escape, and on August 19, 1971, a helicopter landed in the prison yard. The guards mistakenly thought this was an official visit. In two minutes, Kaplan and his cellmate Carlos Antonio Contreras, a Venezuelan counterfeiter, were able to board the craft and were piloted away, before any shots were fired.[9] Both men were flown to Texas and then different planes flew Kaplan to California and Contreras to Guatemala.[3] The Mexican government never initiated extradition proceedings against Kaplan.[9] The escape is told in a book, The 10-Second Jailbreak: The Helicopter Escape of Joel David Kaplan.[4] It also inspired the 1975 action movie Breakout, which starred Charles Bronson and Robert Duvall.[9]"]
['October 31, 1973', 'Mountjoy Jail', 'Ireland', 'Yes', "JB O'Hagan Seamus TwomeyKevin Mallon", 'On October 31, 1973, an IRA member hijacked a helicopter and forced the pilot to land in the exercise yard of Dublin\'s Mountjoy Jail\'s D Wing at 3:40\xa0p.m. Three members of the IRA were able to escape: JB O\'Hagan, Seamus Twomey and Kevin Mallon. Another prisoner who also was in the prison was quoted as saying, "One shamefaced screw apologised to the governor and said he thought it was the new Minister for Defence (Paddy Donegan) arriving. I told him it was our Minister of Defence leaving." The Mountjoy helicopter escape became Republican lore and was immortalized by "The Helicopter Song", which contains the lines "It\'s up like a bird and over the city. There\'s three men a\'missing I heard the warder say".[1]']
['May 24, 1978', 'United States Penitentiary, Marion', 'United States', 'No', 'Garrett Brock TrapnellMartin Joseph McNallyJames Kenneth Johnson', "43-year-old Barbara Ann Oswald hijacked a Saint Louis-based charter helicopter and forced the pilot to land in the yard at USP Marion. While landing the aircraft, the pilot, Allen Barklage, who was a Vietnam War veteran, struggled with Oswald and managed to wrestle the gun away from her. Barklage then shot and killed Oswald, thwarting the escape.[10] A few months later Oswald's daughter hijacked TWA Flight 541 in an effort to free Trapnell."]

index = 0
for row in data:
    data[index] = row[:-1]
    index += 1

Remove the details

print(data[:3])

[['August 19, 1971', 'Santa Martha Acatitla', 'Mexico', 'Yes', 'Joel David Kaplan Carlos Antonio Contreras Castro'], ['October 31, 1973', 'Mountjoy Jail', 'Ireland', 'Yes', "JB O'Hagan Seamus TwomeyKevin Mallon"], ['May 24, 1978', 'United States Penitentiary, Marion', 'United States', 'No', 'Garrett Brock TrapnellMartin Joseph McNallyJames Kenneth Johnson']]

Extract the year

for row in data:
    date = fetch_year(row[0])
    row[0] = date

print(data[:3])

[[1971, 'Santa Martha Acatitla', 'Mexico', 'Yes', 'Joel David Kaplan Carlos Antonio Contreras Castro'], [1973, 'Mountjoy Jail', 'Ireland', 'Yes', "JB O'Hagan Seamus TwomeyKevin Mallon"], [1978, 'United States Penitentiary, Marion', 'United States', 'No', 'Garrett Brock TrapnellMartin Joseph McNallyJames Kenneth Johnson']]

Attempts per year

First find the minimum and maximum years by iterating over the data list and selecting the value at the first position of each element, then selecting the first element of the result.

min_year = min(data, key=lambda x: x[0])[0]
max_year = max(data, key=lambda x: x[0])[0]

Test code - print the result to track progress.

print(min_year)
print(max_year)

1971
2020

Generate a list of all the years between min_year and max_year inclusive.

years = []
for year in range(min_year, max_year + 1):
    years.append(year)

Test code

print(years)

[1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]

Create a new list where each row is a list of the year and number of attempts.

First, we extract the year to add to each item on the row.

attempts_per_year = []
for year in years:
    attempts_per_year.append([year, 0])

Test code

print(attempts_per_year)

[[1971, 0], [1972, 0], [1973, 0], [1974, 0], [1975, 0], [1976, 0], [1977, 0], [1978, 0], [1979, 0], [1980, 0], [1981, 0], [1982, 0], [1983, 0], [1984, 0], [1985, 0], [1986, 0], [1987, 0], [1988, 0], [1989, 0], [1990, 0], [1991, 0], [1992, 0], [1993, 0], [1994, 0], [1995, 0], [1996, 0], [1997, 0], [1998, 0], [1999, 0], [2000, 0], [2001, 0], [2002, 0], [2003, 0], [2004, 0], [2005, 0], [2006, 0], [2007, 0], [2008, 0], [2009, 0], [2010, 0], [2011, 0], [2012, 0], [2013, 0], [2014, 0], [2015, 0], [2016, 0], [2017, 0], [2018, 0], [2019, 0], [2020, 0]]

Second we extract the number of attempts and assign it to the list item with the corresponding year.

for row in data:
    for year_attempt in attempts_per_year:
        year = year_attempt[0]
        if row[0] == year:
            year_attempt[1] += 1
            
print(attempts_per_year)  

[[1971, 1], [1972, 0], [1973, 1], [1974, 0], [1975, 0], [1976, 0], [1977, 0], [1978, 1], [1979, 0], [1980, 0], [1981, 2], [1982, 0], [1983, 1], [1984, 0], [1985, 2], [1986, 3], [1987, 1], [1988, 1], [1989, 2], [1990, 1], [1991, 1], [1992, 2], [1993, 1], [1994, 0], [1995, 0], [1996, 1], [1997, 1], [1998, 0], [1999, 1], [2000, 2], [2001, 3], [2002, 2], [2003, 1], [2004, 0], [2005, 2], [2006, 1], [2007, 3], [2008, 0], [2009, 3], [2010, 1], [2011, 0], [2012, 1], [2013, 2], [2014, 1], [2015, 0], [2016, 1], [2017, 0], [2018, 1], [2019, 0], [2020, 1]]

Next, we create a bar plot representing attempts per year. This presents the data in a format that might be easier to interpret.

%matplotlib inline
barplot(attempts_per_year)

The most attempts at breaking out of prison with a helicopter occurred in 1986, 2001, 2007 and 2009 with three breakouts each year.

countries_frequency = df["Country"].value_counts()
print_pretty_table(countries_frequency)

Country	Number of Occurrences
France	15
United States	8
Belgium	4
Greece	4
Canada	4
Australia	2
United Kingdom	2
Brazil	2
Italy	1
Netherlands	1
Mexico	1
Puerto Rico	1
Ireland	1
Russia	1
Chile	1

France has the most occurrences, followed by the US.

Conclusion

The project gave me skills in using Jupyter and in developing code to analyse the dataset. Results showed fascinating data indicating France has a significant and decades-long problem with escapes via helicopter. Further analysis might provide more detail about how France and other countries might deal with this issue.