static void Main(string[] args)
{
// create data sets
var nameDataSet = new Bogus.DataSets.Name();
var addressDataSet = new Bogus.DataSets.Address();
var phoneDataSet = new Bogus.DataSets.PhoneNumbers();
// create list to hold results
var list = new List <Address>();
for (var i = 0; i < 780000; i++)
{
// generate a result
var address = new Address();
address.First = nameDataSet.FirstName();
address.Last = nameDataSet.LastName();
address.Street = addressDataSet.StreetAddress();
address.City = addressDataSet.City();
address.State = addressDataSet.State();
address.Zip = addressDataSet.ZipCode();
address.Phone = phoneDataSet.PhoneNumberFormat(0);
list.Add(address);
}
// serialize to output.json
var json = Newtonsoft.Json.JsonConvert.SerializeObject(list);
File.WriteAllText("output.json", json);
}
public Record()
{
var randombogus = new Bogus.DataSets.Name.Gender();
var randomName = new Bogus.DataSets.Name("en");
var randomPhone = new Bogus.DataSets.PhoneNumbers("en");
var randomAddress = new Bogus.DataSets.Address("en");
Random rand = new Random();
if (rand.NextDouble() >= 0.5)
{
Sex = "female";
randombogus = (Bogus.DataSets.Name.Gender) 1;
}
else
{
Sex = "male";
randombogus = (Bogus.DataSets.Name.Gender) 0;
}
//generate race
//source for stats: 2019 US census beaurau estimates
var racerand = rand.NextDouble();
if (racerand <= 0.6)
{
Race = "white";
}
else if (racerand > 0.6 && racerand <= 0.78)
{
Race = "hispanic (of any race)";
}
else if (racerand > 0.78 && racerand <= 0.91)
{
Race = "black";
}
else if (racerand > 0.91 && racerand <= 0.97)
{
Race = "asian";
}
else if (racerand > 0.97 && racerand <= 0.98)
{
Race = "native american or alaskan native";
}
else if (racerand > 0.98 && racerand <= 0.985)
{
Race = "native hawaiian or other pacific islander";
}
else
{
Race = "two or more races";
}
if (Sex == "male")
{
//The multiplier makes taller people slightly heavier. Someone 1.9 meters will be about 8% heavier than someone that's 1.5 meters, compared to without the bonus. Make divisor smaller to make effect more extreme
HeightInMeters = NormalDistribution.Random(1.8, 0.1);
//if (HeightInMeters < 2.0) { var heightWeightMultiplier = (1 + (HeightInMeters - 2.0) / 4.0); }
//else { var heightWeightMultiplier = (2.0 + ((HeightInMeters -2.0) / 4.0)); }
Weight = NormalDistribution.Random(86, 18); //average values and stddev. source: google
Waistline = 40 + ((Weight - 86) / 4); //you gain 1in / 4kg
}
else
{
HeightInMeters = NormalDistribution.Random(1.65, 0.1);
//if (HeightInMeters < 2.0) { var heightWeightMultiplier = (1 + (HeightInMeters - 2.0) / 4.0); }
//else { var heightWeightMultiplier = (2.0 + ((HeightInMeters - 2.0) / 4.0)); }
Weight = NormalDistribution.Random(78, 14);
Waistline = 36 + ((Weight - 86) / 4); //in meters. since 1kg causes +/- 0.01m waistline. average just happens to be 1.0
}
double weightHeightCorrelation = (.5) * ((HeightInMeters * 100) - 180);
Weight += weightHeightCorrelation;
//convert meters to ft/in
var inchFeet = (HeightInMeters / 0.3048);
HeightFeet = (int)inchFeet;
HeightInches = Math.Floor(Math.Round((inchFeet - HeightFeet) / 0.0833));
//convert kg to pounds
WeightInLb = Weight * 2.20462;
FirstName = randomName.FirstName(randombogus);
LastName = randomName.LastName();
PhoneNumber = randomPhone.PhoneNumber();
Address = randomAddress.StreetAddress();
Random gen = new Random();
double probability = gen.NextDouble();
DateTime start = new DateTime(DateTime.Today.Year - 85, 1, 1);
int rangeMax; int rangeMin;
if (probability <= 0.15)
{
rangeMin = 0; rangeMax = (85 * 365 - 65 * 365);
}
else
{
rangeMin = 21 * 365; rangeMax = 65 * 365;
}
DateOfBirth = start.AddDays(gen.Next(rangeMin, rangeMax));
Age = DateTime.Today.Year - DateOfBirth.Year;
if (DateOfBirth.Date > DateTime.Today.AddYears(-Age))
{
Age--;
}
BMI = Weight / Math.Pow(HeightInMeters, 2);
}