Report

As a team, answer a subset of the questions submitted during the hackathon. But instead of using Tableau, you will need to write Javascript/Lodash code to derive your answers. Similar to before, each team member is responsible for one question. But everyone should work together to come up with a good solution. Your answer should consist of Lodash code and a brief writeup. Utilize _.map, _.filter, _.group ...etc. Do not use any for loop.

This time, the data is not already prepared for you in a nice JSON format. You will need to do it on your own, replacing the placeholder birdstrike.json with real data.

This report is prepared by

• William Farmer
• Parker Illig
• Kevin Gifford
• John Raesly
• Andrew Krodinger

NOTE: Command to transform birdstrikes.xlsx to birdstrike.csv:

prompt> in2csv birdstrikes.xlsx > birdstrike.csv

NOTE: Command to cut the data and output the birdstrike.json file utilized as the source data for this report:

prompt> csvcut -c 'Airport: Name','Aircraft: Airline/Operator','Aircraft: Make/Model','Effect: Indicated Damage','When: Phase of flight','Feet above ground','Conditions: Sky','Cost: Total $' birdstrike.csv | csvjson --indent 4 > birdstrike.json

The data looks like:

[
 {
  "Airport: Name": "NEWARK LIBERTY INTL ARPT",
  "Aircraft: Airline/Operator": "CONTINENTAL AIRLINES",
  "Aircraft: Make/Model": "B-757-200",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Take-off run",
  "Feet above ground": "0",
  "Conditions: Sky": "Overcast",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "UNKNOWN",
  "Aircraft: Airline/Operator": "UNITED AIRLINES",
  "Aircraft: Make/Model": "B-737-300",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "",
  "Feet above ground": "Not Reported",
  "Conditions: Sky": "",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "DENVER INTL AIRPORT",
  "Aircraft: Airline/Operator": "UNITED AIRLINES",
  "Aircraft: Make/Model": "B-737-300",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Climb",
  "Feet above ground": "Not Reported",
  "Conditions: Sky": "",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "CHICAGO O'HARE INTL ARPT",
  "Aircraft: Airline/Operator": "UNITED AIRLINES",
  "Aircraft: Make/Model": "B-727-200",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Approach",
  "Feet above ground": "Not Reported",
  "Conditions: Sky": "",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "JOHN F KENNEDY INTL",
  "Aircraft: Airline/Operator": "UNKNOWN",
  "Aircraft: Make/Model": "UNKNOWN",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "",
  "Feet above ground": "Not Reported",
  "Conditions: Sky": "",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "UNKNOWN",
  "Aircraft: Airline/Operator": "US CUSTOMS AND BORDER PROTECTION",
  "Aircraft: Make/Model": "C-550",
  "Effect: Indicated Damage": "Caused damage",
  "When: Phase of flight": "En Route",
  "Feet above ground": "1000",
  "Conditions: Sky": "",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "UNKNOWN",
  "Aircraft: Airline/Operator": "AMERICAN AIRLINES",
  "Aircraft: Make/Model": "B-727-200",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Take-off run",
  "Feet above ground": "0",
  "Conditions: Sky": "No Cloud",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "CINCINNATI MUNI ARPT-LUNKEN FIELD",
  "Aircraft: Airline/Operator": "BUSINESS",
  "Aircraft: Make/Model": "CITATION II",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Landing Roll",
  "Feet above ground": "0",
  "Conditions: Sky": "Overcast",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "MIAMI INTL",
  "Aircraft: Airline/Operator": "BUSINESS",
  "Aircraft: Make/Model": "DA-2000",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Approach",
  "Feet above ground": "2000",
  "Conditions: Sky": "No Cloud",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "SAN FRANCISCO INTL ARPT",
  "Aircraft: Airline/Operator": "UNITED AIRLINES",
  "Aircraft: Make/Model": "B-737-500",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Take-off run",
  "Feet above ground": "0",
  "Conditions: Sky": "No Cloud",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "SALT LAKE CITY INTL",
  "Aircraft: Airline/Operator": "DELTA AIR LINES",
  "Aircraft: Make/Model": "B-737-300",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Landing Roll",
  "Feet above ground": "0",
  "Conditions: Sky": "Some Cloud",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "MIAMI INTL",
  "Aircraft: Airline/Operator": "UNKNOWN",
  "Aircraft: Make/Model": "UNKNOWN",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "",
  "Feet above ground": "Not Reported",
  "Conditions: Sky": "",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "SOUTHWEST FLORIDA INTL ARPT",
  "Aircraft: Airline/Operator": "BUSINESS",
  "Aircraft: Make/Model": "HAWKER 800",
  "Effect: Indicated Damage": "Caused damage",
  "When: Phase of flight": "Approach",
  "Feet above ground": "200",
  "Conditions: Sky": "No Cloud",
  "Cost: Total $": "120273"
 },
 {
  "Airport: Name": "KANSAS CITY INTL",
  "Aircraft: Airline/Operator": "TRANS WORLD AIRLINES",
  "Aircraft: Make/Model": "MD-80",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Approach",
  "Feet above ground": "350",
  "Conditions: Sky": "No Cloud",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "NASHVILLE INTL",
  "Aircraft: Airline/Operator": "US AIRWAYS*",
  "Aircraft: Make/Model": "B-737-400",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Climb",
  "Feet above ground": "800",
  "Conditions: Sky": "Some Cloud",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "SAN ANTONIO INTL",
  "Aircraft: Airline/Operator": "SOUTHWEST AIRLINES",
  "Aircraft: Make/Model": "B-737",
  "Effect: Indicated Damage": "No damage",
  "When: Phase of flight": "Climb",
  "Feet above ground": "Not Reported",
  "Conditions: Sky": "",
  "Cost: Total $": "0"
 },
 {
  "Airport: Name": "SALT LAKE CITY INTL",
  "Aircraft: Airline/Operator": "DELTA AIR LINES",
  "Aircraft: Make/Model": "B-767-300",
  "Effect:

Question 1: What are the condition:sky where usually caused a damage? From: fadhilfath By: William Farmer

var flist = _.filter(data, function(f) {
    return _.any(f['Effect: Indicated Damage'], function(d) {
        return d != "No Damage"
    })
})
var list = _.map(flist, function(n) {
    var weather = n['Conditions: Sky']
    if (n['Conditions: Sky'] == "No Cloud") weather = "No Clouds"
    if (n['Conditions: Sky'] == "Some Cloud") weather = "Some Clouds"
    var airport = n['Airport: Name']
    return { "airportName": airport, "skyCondition": weather }
})
var groups = _.groupBy(list, 'skyCondition')
return _.mapValues(groups, function(d) {
    return d.length
})

Table 1-1: What is the distibution of sky conditions where damaged occurred

Question 2a: What is the most common flight phase where a birdstrike occurred? From: KevinKGifford By: KevinKGifford

var groups = _.groupBy(data, 'When: Phase of flight')
var results = _.mapValues(groups, function(d){
    return d.length
})
var sorted_output = _.sortBy(_.pairs(results), function(d) {
    return d[1]
})
return sorted_output

Table 2-1: What is the most common flight phase where a birdstrike occurred

Question 2b: What is the correlation between the feet above the ground and the number of bird strikes? From: Linenfelser By: KevinKGifford

var list = _.map(data, function(n) {
    if (n['Feet above ground'] == "") {
        n['Feet above ground'] = "Not Reported"
    }
    var feet = (_.round(n['Feet above ground'] / 1000)) * 1000
    var airport = n['Airport: Name']
    return { "airportName": airport, "Feet above ground": n['Feet above ground'], "elevationBin": feet }
})
var groups = _.groupBy(list, 'elevationBin')
return _.mapValues(groups, function(d) {
    return d.length
})

Table 2-2: What is the correlation between the feet above the ground and the number of bird strikes?

Question 3: Which airport had the highest number of bird strikes? From: Zhya215 By: Andrew Krodinger

var groups = _.groupBy(data, 'Airport: Name')
var results = _.mapValues(groups, function(d) {
    return d.length
})
var sorted_output = _.sortByOrder(_.pairs(results), function(d) {
    return d[1]
},'desc')
return sorted_output

Table 3-1: Which airport had the highest number of bird strikes?

Question 4: Which airline have to incur most repair cost due to damage? From: sumi6109 By: Parker Illig

var list = _.filter(data, function(f) {
    return _.any(f['Cost: Total $'], function(d) {
        return d > 0
    })
})
var groups = _.groupBy(list, 'Aircraft: Airline/Operator')
// Sum the damage costs on a per airline (key) basis
var results = _.mapValues(groups, function(d) {
    return _.sum(_.pluck(d, 'Cost: Total $'))
})
var sorted_output = _.sortByOrder(_.pairs(results), function(d) {
    return d[1]
},'desc')
return sorted_output

Table 4-1: Which airline incurred the most repair cost due to damage?

Question 5: Which plane model strikes the most birds? From: twagar95 By: John Raesly

var groups = _.groupBy(data, 'Aircraft: Make/Model')
var results = _.mapValues(groups, function(d) {
    return d.length
})
var sorted_output = _.sortByOrder(_.pairs(results), function(d) {
    return d[1]
},'desc')
return sorted_output

Table 5-1: Which plane model strikes the most birds?