Question

Using the data set as a pre-defined variable in your program, write code that uses the dataset to print the first names of people who have BOTH above average math grades AND below average age from the dataset.

The solutions for the textbook examples assume you are able to export in a framework like node.js, which is why in the data set I provide, I simply set the array of objects as a variable. Your code will be in the same file (treat it like any other array variable). You can do the same with the sample files the chapter provides. For example:

var ancestry = [
    {
       .. object ..
    },
    ...
]

// your code here

Requirements:

• Cannot use any array type built-in functions except filter(), map(), and reduce().

var dataSet = [
{
"name": "Maura Glass",
"age": 60,
"math": 97,
"english": 63,
"yearsOfEducation": 4
},
{
"name": "James Gates",
"age": 55,
"math": 72,
"english": 96,
"yearsOfEducation": 10
},
{
"name": "Mills Morris",
"age": 26,
"math": 83,
"english": 77,
"yearsOfEducation": 10
},
{
"name": "Deena Morton",
"age": 57,
"math": 63,
"english": 63,
"yearsOfEducation": 10
},
{
"name": "Edith Roth",
"age": 38,
"math": 79,
"english": 94,
"yearsOfEducation": 10
},
{
"name": "Marva Morse",
"age": 31,
"math": 93,
"english": 78,
"yearsOfEducation": 9
},
{
"name": "Etta Potts",
"age": 48,
"math": 57,
"english": 93,
"yearsOfEducation": 7
},
{
"name": "Tate Moss",
"age": 22,
"math": 83,
"english": 64,
"yearsOfEducation": 8
},
{
"name": "Sanders Burris",
"age": 27,
"math": 65,
"english": 66,
"yearsOfEducation": 5
},
{
"name": "Latoya Malone",
"age": 35,
"math": 100,
"english": 100,
"yearsOfEducation": 5
},
{
"name": "Wade Foreman",
"age": 25,
"math": 76,
"english": 87,
"yearsOfEducation": 10
},
{
"name": "Miller Valentine",
"age": 31,
"math": 56,
"english": 89,
"yearsOfEducation": 6
},
{
"name": "Rita Olson",
"age": 53,
"math": 100,
"english": 52,
"yearsOfEducation": 6
},
{
"name": "Potter Newton",
"age": 29,
"math": 91,
"english": 75,
"yearsOfEducation": 5
},
{
"name": "Madeline Bartlett",
"age": 23,
"math": 60,
"english": 74,
"yearsOfEducation": 10
},
{
"name": "Tamara Tran",
"age": 46,
"math": 73,
"english": 78,
"yearsOfEducation": 4
},
{
"name": "Elena Evans",
"age": 43,
"math": 60,
"english": 82,
"yearsOfEducation": 10
},
{
"name": "Cote Merrill",
"age": 55,
"math": 86,
"english": 63,
"yearsOfEducation": 7
},
{
"name": "Madeleine Brennan",
"age": 52,
"math": 82,
"english": 88,
"yearsOfEducation": 4
},
{
"name": "Alford Weber",
"age": 38,
"math": 71,
"english": 85,
"yearsOfEducation": 4
},
{
"name": "Kirsten Daniel",
"age": 35,
"math": 86,
"english": 61,
"yearsOfEducation": 8
},
{
"name": "Melton Chan",
"age": 26,
"math": 55,
"english": 96,
"yearsOfEducation": 4
},
{
"name": "Mcmahon Woodward",
"age": 54,
"math": 56,
"english": 63,
"yearsOfEducation": 9
},
{
"name": "Helga Monroe",
"age": 29,
"math": 79,
"english": 92,
"yearsOfEducation": 5
},
{
"name": "Patricia Herrera",
"age": 46,
"math": 94,
"english": 99,
"yearsOfEducation": 10
},
{
"name": "Mccullough Lambert",
"age": 56,
"math": 65,
"english": 96,
"yearsOfEducation": 8
},
{
"name": "Haynes Davidson",
"age": 60,
"math": 86,
"english": 50,
"yearsOfEducation": 5
}
]

Answer 1

SOURCE CODE

var dataSet = [

{

"name": "Maura Glass",

"age": 60,

"math": 97,

"english": 63,

"yearsOfEducation": 4

},

{

"name": "James Gates",

"age": 55,

"math": 72,

"english": 96,

"yearsOfEducation": 10

},

{

"name": "Mills Morris",

"age": 26,

"math": 83,

"english": 77,

"yearsOfEducation": 10

},

{

"name": "Deena Morton",

"age": 57,

"math": 63,

"english": 63,

"yearsOfEducation": 10

},

{

"name": "Edith Roth",

"age": 38,

"math": 79,

"english": 94,

"yearsOfEducation": 10

},

{

"name": "Marva Morse",

"age": 31,

"math": 93,

"english": 78,

"yearsOfEducation": 9

},

{

"name": "Etta Potts",

"age": 48,

"math": 57,

"english": 93,

"yearsOfEducation": 7

},

{

"name": "Tate Moss",

"age": 22,

"math": 83,

"english": 64,

"yearsOfEducation": 8

},

{

"name": "Sanders Burris",

"age": 27,

"math": 65,

"english": 66,

"yearsOfEducation": 5

},

{

"name": "Latoya Malone",

"age": 35,

"math": 100,

"english": 100,

"yearsOfEducation": 5

},

{

"name": "Wade Foreman",

"age": 25,

"math": 76,

"english": 87,

"yearsOfEducation": 10

},

{

"name": "Miller Valentine",

"age": 31,

"math": 56,

"english": 89,

"yearsOfEducation": 6

},

{

"name": "Rita Olson",

"age": 53,

"math": 100,

"english": 52,

"yearsOfEducation": 6

},

{

"name": "Potter Newton",

"age": 29,

"math": 91,

"english": 75,

"yearsOfEducation": 5

},

{

"name": "Madeline Bartlett",

"age": 23,

"math": 60,

"english": 74,

"yearsOfEducation": 10

},

{

"name": "Tamara Tran",

"age": 46,

"math": 73,

"english": 78,

"yearsOfEducation": 4

},

{

"name": "Elena Evans",

"age": 43,

"math": 60,

"english": 82,

"yearsOfEducation": 10

},

{

"name": "Cote Merrill",

"age": 55,

"math": 86,

"english": 63,

"yearsOfEducation": 7

},

{

"name": "Madeleine Brennan",

"age": 52,

"math": 82,

"english": 88,

"yearsOfEducation": 4

},

{

"name": "Alford Weber",

"age": 38,

"math": 71,

"english": 85,

"yearsOfEducation": 4

},

{

"name": "Kirsten Daniel",

"age": 35,

"math": 86,

"english": 61,

"yearsOfEducation": 8

},

{

"name": "Melton Chan",

"age": 26,

"math": 55,

"english": 96,

"yearsOfEducation": 4

},

{

"name": "Mcmahon Woodward",

"age": 54,

"math": 56,

"english": 63,

"yearsOfEducation": 9

},

{

"name": "Helga Monroe",

"age": 29,

"math": 79,

"english": 92,

"yearsOfEducation": 5

},

{

"name": "Patricia Herrera",

"age": 46,

"math": 94,

"english": 99,

"yearsOfEducation": 10

},

{

"name": "Mccullough Lambert",

"age": 56,

"math": 65,

"english": 96,

"yearsOfEducation": 8

},

{

"name": "Haynes Davidson",

"age": 60,

"math": 86,

"english": 50,

"yearsOfEducation": 5

}

]

// using reduce to find the sum of math grades

var sum_math_grades = dataSet.reduce(function(acc, person){

return (acc + person["math"])

}, 0);

// using the sum to find average of math grades

var avg_math_grade = sum_math_grades / dataSet.length

// using reduce to find sum of age

var sum_age = dataSet.reduce(function(acc, person){

return (acc + person["age"])

}, 0);

// using the sum tofind average age

var avg_age = sum_age / dataSet.length

// using filter to get only yhose persons meeting the required condition

var final_array = dataSet.filter(function(person)

{

return person["math"] >= avg_math_grade && person["age"] <= avg_age

})

// using map to only store the first names of the person in an array

person_final = final_array.map(function(person){

return person["name"].split(" ")[0]

})

// printing the result

console.log(person_final)

OUTPUT