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  2. autism_model.pkl +3 -0
  3. data.csv +801 -0
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@@ -0,0 +1,2245 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {},
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+ "source": [
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+ "# Autism"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {},
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+ "source": [
14
+ "Autism, also known as Autism Spectrum Disorder (ASD), is a neurodevelopmental condition characterized by challenges in social interaction, communication, and repetitive behaviors. Individuals with autism may exhibit a wide range of abilities and symptoms, forming a spectrum. Understanding and accurately classifying autism can be a complex task due to the diversity within the spectrum. Machine Learning (ML) plays a vital role in addressing this challenge by leveraging algorithms to analyze patterns and make predictions based on data."
15
+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
19
+ "metadata": {},
20
+ "source": [
21
+ "## Data\n",
22
+ "\n",
23
+ "ID - ID of the patient\n",
24
+ "\n",
25
+ "A1_Score to A10_Score - Score based on Autism Spectrum Quotient (AQ) 10 item screening tool\n",
26
+ "\n",
27
+ "age - Age of the patient in years\n",
28
+ "\n",
29
+ "gender - Gender of the patient\n",
30
+ "\n",
31
+ "ethnicity - Ethnicity of the patient\n",
32
+ "\n",
33
+ "jaundice - Whether the patient had jaundice at the time of birth\n",
34
+ "\n",
35
+ "autism - Whether an immediate family member has been diagnosed with autism\n",
36
+ "\n",
37
+ "contry_of_res - Country of residence of the patient\n",
38
+ "\n",
39
+ "used_app_before - Whether the patient has undergone a screening test before\n",
40
+ "\n",
41
+ "result - Score for AQ1-10 screening test\n",
42
+ "\n",
43
+ "age_desc - Age of the patient\n",
44
+ "\n",
45
+ "relation - Relation of patient who completed the test\n",
46
+ "\n",
47
+ "Class/ASD - Classified result as 0 or 1. Here 0 represents No and 1 represents Yes. This is the target column, and during submission submit the values as 0 or 1 only."
48
+ ]
49
+ },
50
+ {
51
+ "cell_type": "code",
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+ "execution_count": 1,
53
+ "metadata": {},
54
+ "outputs": [],
55
+ "source": [
56
+ "import numpy as np\n",
57
+ "import pandas as pd\n",
58
+ "from sklearn.model_selection import train_test_split\n",
59
+ "from sklearn.preprocessing import StandardScaler\n",
60
+ "from sklearn.metrics import confusion_matrix, accuracy_score, classification_report\n",
61
+ "from sklearn.linear_model import LogisticRegression \n",
62
+ "import joblib\n"
63
+ ]
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+ },
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+ {
66
+ "cell_type": "code",
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+ "execution_count": 2,
68
+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "data=pd.read_csv(\"data.csv\")"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 3,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/html": [
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+ "<div>\n",
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+ "<style scoped>\n",
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+ " .dataframe tbody tr th:only-of-type {\n",
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+ " vertical-align: middle;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe tbody tr th {\n",
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+ " vertical-align: top;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
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+ " }\n",
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+ "</style>\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
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+ " <thead>\n",
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+ " <tr style=\"text-align: right;\">\n",
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+ " <th></th>\n",
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+ " <th>ID</th>\n",
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+ " <th>gender</th>\n",
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+ " <th>A1_Score</th>\n",
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+ " <th>A2_Score</th>\n",
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+ " <th>A3_Score</th>\n",
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+ " <th>A4_Score</th>\n",
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+ " <th>A5_Score</th>\n",
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+ " <th>A6_Score</th>\n",
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+ " <th>A7_Score</th>\n",
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+ " <th>A8_Score</th>\n",
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+ " <th>...</th>\n",
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+ " <th>jaundice</th>\n",
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+ " <th>austim</th>\n",
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+ " <th>age</th>\n",
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+ " <th>ethnicity</th>\n",
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+ " <th>contry_of_res</th>\n",
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+ " <th>used_app_before</th>\n",
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+ " <th>result</th>\n",
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+ " <th>relation</th>\n",
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+ " <th>age_desc</th>\n",
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+ " <th>Class/ASD</th>\n",
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+ " </tr>\n",
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+ " </thead>\n",
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+ " <tbody>\n",
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+ " <tr>\n",
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+ " <th>0</th>\n",
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+ " <td>1</td>\n",
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+ " <td>f</td>\n",
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+ " <td>1</td>\n",
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+ " <td>0</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>0</td>\n",
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+ " <td>1</td>\n",
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+ " <td>...</td>\n",
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+ " <td>no</td>\n",
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+ " <td>no</td>\n",
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+ " <td>18.605397</td>\n",
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+ " <td>White-European</td>\n",
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+ " <td>United States</td>\n",
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+ " <td>no</td>\n",
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+ " <td>7.819715</td>\n",
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+ " <td>Self</td>\n",
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+ " <td>18 and more</td>\n",
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+ " <td>0</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>1</th>\n",
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+ " <td>2</td>\n",
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+ " <td>f</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>no</td>\n",
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+ " <td>no</td>\n",
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+ " <td>13.829369</td>\n",
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+ " <td>South Asian</td>\n",
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+ " <td>Australia</td>\n",
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+ " <td>no</td>\n",
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+ " <td>10.544296</td>\n",
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+ " <td>?</td>\n",
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+ " <td>18 and more</td>\n",
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+ " <td>0</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>2</th>\n",
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+ " <td>3</td>\n",
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+ " <td>f</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>...</td>\n",
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+ " <td>no</td>\n",
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+ " <td>no</td>\n",
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+ " <td>14.679893</td>\n",
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+ " <td>White-European</td>\n",
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+ " <td>United Kingdom</td>\n",
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+ " <td>no</td>\n",
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+ " <td>13.167506</td>\n",
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+ " <td>Self</td>\n",
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+ " <td>18 and more</td>\n",
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+ " <td>1</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>3</th>\n",
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+ " <td>4</td>\n",
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+ " <td>f</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>no</td>\n",
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+ " <td>no</td>\n",
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+ " <td>61.035288</td>\n",
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+ " <td>South Asian</td>\n",
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+ " <td>New Zealand</td>\n",
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+ " <td>no</td>\n",
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+ " <td>1.530098</td>\n",
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+ " <td>?</td>\n",
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+ " <td>18 and more</td>\n",
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+ " <td>0</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>4</th>\n",
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+ " <td>5</td>\n",
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+ " <td>m</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>1</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <td>...</td>\n",
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+ " <td>no</td>\n",
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+ " <td>yes</td>\n",
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+ " <td>14.256686</td>\n",
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+ " <td>Black</td>\n",
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+ " <td>Italy</td>\n",
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+ " <td>no</td>\n",
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+ " <td>7.949723</td>\n",
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+ " <td>Self</td>\n",
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+ " <td>18 and more</td>\n",
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+ " <td>0</td>\n",
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+ " <th>795</th>\n",
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+ " <td>796</td>\n",
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+ " <td>f</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>yes</td>\n",
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+ " <td>White-European</td>\n",
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+ " <td>no</td>\n",
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+ " <td>Asian</td>\n",
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+ " <td>New Zealand</td>\n",
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+ " <td>no</td>\n",
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+ " <td>Self</td>\n",
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375
+ " <td>1</td>\n",
376
+ " <td>...</td>\n",
377
+ " <td>no</td>\n",
378
+ " <td>no</td>\n",
379
+ " <td>32.170098</td>\n",
380
+ " <td>Asian</td>\n",
381
+ " <td>New Zealand</td>\n",
382
+ " <td>no</td>\n",
383
+ " <td>12.060168</td>\n",
384
+ " <td>Self</td>\n",
385
+ " <td>18 and more</td>\n",
386
+ " <td>0</td>\n",
387
+ " </tr>\n",
388
+ " </tbody>\n",
389
+ "</table>\n",
390
+ "<p>800 rows × 22 columns</p>\n",
391
+ "</div>"
392
+ ],
393
+ "text/plain": [
394
+ " ID gender A1_Score A2_Score A3_Score A4_Score A5_Score A6_Score \\\n",
395
+ "0 1 f 1 0 1 1 1 1 \n",
396
+ "1 2 f 0 0 0 0 0 0 \n",
397
+ "2 3 f 1 1 1 1 1 1 \n",
398
+ "3 4 f 0 0 0 1 0 0 \n",
399
+ "4 5 m 0 0 0 0 1 0 \n",
400
+ ".. ... ... ... ... ... ... ... ... \n",
401
+ "795 796 f 1 1 1 1 1 1 \n",
402
+ "796 797 f 1 1 0 0 1 0 \n",
403
+ "797 798 m 0 0 0 0 0 0 \n",
404
+ "798 799 f 1 1 1 1 1 1 \n",
405
+ "799 800 f 1 0 0 1 1 0 \n",
406
+ "\n",
407
+ " A7_Score A8_Score ... jaundice austim age ethnicity \\\n",
408
+ "0 0 1 ... no no 18.605397 White-European \n",
409
+ "1 0 0 ... no no 13.829369 South Asian \n",
410
+ "2 0 0 ... no no 14.679893 White-European \n",
411
+ "3 0 0 ... no no 61.035288 South Asian \n",
412
+ "4 0 0 ... no yes 14.256686 Black \n",
413
+ ".. ... ... ... ... ... ... ... \n",
414
+ "795 1 1 ... no yes 42.084907 White-European \n",
415
+ "796 0 0 ... no no 17.669291 Asian \n",
416
+ "797 1 0 ... yes no 18.242557 White-European \n",
417
+ "798 0 1 ... no yes 19.241473 Middle Eastern \n",
418
+ "799 0 1 ... no no 32.170098 Asian \n",
419
+ "\n",
420
+ " contry_of_res used_app_before result relation age_desc \\\n",
421
+ "0 United States no 7.819715 Self 18 and more \n",
422
+ "1 Australia no 10.544296 ? 18 and more \n",
423
+ "2 United Kingdom no 13.167506 Self 18 and more \n",
424
+ "3 New Zealand no 1.530098 ? 18 and more \n",
425
+ "4 Italy no 7.949723 Self 18 and more \n",
426
+ ".. ... ... ... ... ... \n",
427
+ "795 United States no 13.390868 Self 18 and more \n",
428
+ "796 New Zealand no 9.454201 Self 18 and more \n",
429
+ "797 Jordan no 6.805509 Self 18 and more \n",
430
+ "798 United States no 3.682732 Relative 18 and more \n",
431
+ "799 New Zealand no 12.060168 Self 18 and more \n",
432
+ "\n",
433
+ " Class/ASD \n",
434
+ "0 0 \n",
435
+ "1 0 \n",
436
+ "2 1 \n",
437
+ "3 0 \n",
438
+ "4 0 \n",
439
+ ".. ... \n",
440
+ "795 1 \n",
441
+ "796 0 \n",
442
+ "797 1 \n",
443
+ "798 0 \n",
444
+ "799 0 \n",
445
+ "\n",
446
+ "[800 rows x 22 columns]"
447
+ ]
448
+ },
449
+ "execution_count": 3,
450
+ "metadata": {},
451
+ "output_type": "execute_result"
452
+ }
453
+ ],
454
+ "source": [
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+ "data"
456
+ ]
457
+ },
458
+ {
459
+ "cell_type": "code",
460
+ "execution_count": 4,
461
+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/html": [
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+ " <thead>\n",
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+ " <tr style=\"text-align: right;\">\n",
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+ " <th></th>\n",
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+ " <th>ID</th>\n",
485
+ " <th>A1_Score</th>\n",
486
+ " <th>A2_Score</th>\n",
487
+ " <th>A3_Score</th>\n",
488
+ " <th>A4_Score</th>\n",
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+ " <th>A5_Score</th>\n",
490
+ " <th>A6_Score</th>\n",
491
+ " <th>A7_Score</th>\n",
492
+ " <th>A8_Score</th>\n",
493
+ " <th>A9_Score</th>\n",
494
+ " <th>A10_Score</th>\n",
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+ " <th>age</th>\n",
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+ " <th>result</th>\n",
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+ " <th>Class/ASD</th>\n",
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+ " </tr>\n",
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+ " </thead>\n",
500
+ " <tbody>\n",
501
+ " <tr>\n",
502
+ " <th>count</th>\n",
503
+ " <td>800.0000</td>\n",
504
+ " <td>800.000000</td>\n",
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+ " <td>800.00000</td>\n",
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+ " <td>800.000000</td>\n",
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+ " <td>800.000000</td>\n",
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+ " <td>800.000000</td>\n",
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+ " <td>800.000000</td>\n",
516
+ " <td>800.000000</td>\n",
517
+ " </tr>\n",
518
+ " <tr>\n",
519
+ " <th>mean</th>\n",
520
+ " <td>400.5000</td>\n",
521
+ " <td>0.582500</td>\n",
522
+ " <td>0.28625</td>\n",
523
+ " <td>0.321250</td>\n",
524
+ " <td>0.41500</td>\n",
525
+ " <td>0.457500</td>\n",
526
+ " <td>0.20875</td>\n",
527
+ " <td>0.273750</td>\n",
528
+ " <td>0.717500</td>\n",
529
+ " <td>0.316250</td>\n",
530
+ " <td>0.460000</td>\n",
531
+ " <td>28.612306</td>\n",
532
+ " <td>7.058530</td>\n",
533
+ " <td>0.231250</td>\n",
534
+ " </tr>\n",
535
+ " <tr>\n",
536
+ " <th>std</th>\n",
537
+ " <td>231.0844</td>\n",
538
+ " <td>0.493455</td>\n",
539
+ " <td>0.45229</td>\n",
540
+ " <td>0.467249</td>\n",
541
+ " <td>0.49303</td>\n",
542
+ " <td>0.498502</td>\n",
543
+ " <td>0.40667</td>\n",
544
+ " <td>0.446161</td>\n",
545
+ " <td>0.450497</td>\n",
546
+ " <td>0.465303</td>\n",
547
+ " <td>0.498709</td>\n",
548
+ " <td>12.872373</td>\n",
549
+ " <td>3.788969</td>\n",
550
+ " <td>0.421896</td>\n",
551
+ " </tr>\n",
552
+ " <tr>\n",
553
+ " <th>min</th>\n",
554
+ " <td>1.0000</td>\n",
555
+ " <td>0.000000</td>\n",
556
+ " <td>0.00000</td>\n",
557
+ " <td>0.000000</td>\n",
558
+ " <td>0.00000</td>\n",
559
+ " <td>0.000000</td>\n",
560
+ " <td>0.00000</td>\n",
561
+ " <td>0.000000</td>\n",
562
+ " <td>0.000000</td>\n",
563
+ " <td>0.000000</td>\n",
564
+ " <td>0.000000</td>\n",
565
+ " <td>9.560505</td>\n",
566
+ " <td>-2.594654</td>\n",
567
+ " <td>0.000000</td>\n",
568
+ " </tr>\n",
569
+ " <tr>\n",
570
+ " <th>25%</th>\n",
571
+ " <td>200.7500</td>\n",
572
+ " <td>0.000000</td>\n",
573
+ " <td>0.00000</td>\n",
574
+ " <td>0.000000</td>\n",
575
+ " <td>0.00000</td>\n",
576
+ " <td>0.000000</td>\n",
577
+ " <td>0.00000</td>\n",
578
+ " <td>0.000000</td>\n",
579
+ " <td>0.000000</td>\n",
580
+ " <td>0.000000</td>\n",
581
+ " <td>0.000000</td>\n",
582
+ " <td>19.282082</td>\n",
583
+ " <td>4.527556</td>\n",
584
+ " <td>0.000000</td>\n",
585
+ " </tr>\n",
586
+ " <tr>\n",
587
+ " <th>50%</th>\n",
588
+ " <td>400.5000</td>\n",
589
+ " <td>1.000000</td>\n",
590
+ " <td>0.00000</td>\n",
591
+ " <td>0.000000</td>\n",
592
+ " <td>0.00000</td>\n",
593
+ " <td>0.000000</td>\n",
594
+ " <td>0.00000</td>\n",
595
+ " <td>0.000000</td>\n",
596
+ " <td>1.000000</td>\n",
597
+ " <td>0.000000</td>\n",
598
+ " <td>0.000000</td>\n",
599
+ " <td>25.479960</td>\n",
600
+ " <td>6.893472</td>\n",
601
+ " <td>0.000000</td>\n",
602
+ " </tr>\n",
603
+ " <tr>\n",
604
+ " <th>75%</th>\n",
605
+ " <td>600.2500</td>\n",
606
+ " <td>1.000000</td>\n",
607
+ " <td>1.00000</td>\n",
608
+ " <td>1.000000</td>\n",
609
+ " <td>1.00000</td>\n",
610
+ " <td>1.000000</td>\n",
611
+ " <td>0.00000</td>\n",
612
+ " <td>1.000000</td>\n",
613
+ " <td>1.000000</td>\n",
614
+ " <td>1.000000</td>\n",
615
+ " <td>1.000000</td>\n",
616
+ " <td>33.154755</td>\n",
617
+ " <td>9.892981</td>\n",
618
+ " <td>0.000000</td>\n",
619
+ " </tr>\n",
620
+ " <tr>\n",
621
+ " <th>max</th>\n",
622
+ " <td>800.0000</td>\n",
623
+ " <td>1.000000</td>\n",
624
+ " <td>1.00000</td>\n",
625
+ " <td>1.000000</td>\n",
626
+ " <td>1.00000</td>\n",
627
+ " <td>1.000000</td>\n",
628
+ " <td>1.00000</td>\n",
629
+ " <td>1.000000</td>\n",
630
+ " <td>1.000000</td>\n",
631
+ " <td>1.000000</td>\n",
632
+ " <td>1.000000</td>\n",
633
+ " <td>72.402488</td>\n",
634
+ " <td>13.390868</td>\n",
635
+ " <td>1.000000</td>\n",
636
+ " </tr>\n",
637
+ " </tbody>\n",
638
+ "</table>\n",
639
+ "</div>"
640
+ ],
641
+ "text/plain": [
642
+ " ID A1_Score A2_Score A3_Score A4_Score A5_Score \\\n",
643
+ "count 800.0000 800.000000 800.00000 800.000000 800.00000 800.000000 \n",
644
+ "mean 400.5000 0.582500 0.28625 0.321250 0.41500 0.457500 \n",
645
+ "std 231.0844 0.493455 0.45229 0.467249 0.49303 0.498502 \n",
646
+ "min 1.0000 0.000000 0.00000 0.000000 0.00000 0.000000 \n",
647
+ "25% 200.7500 0.000000 0.00000 0.000000 0.00000 0.000000 \n",
648
+ "50% 400.5000 1.000000 0.00000 0.000000 0.00000 0.000000 \n",
649
+ "75% 600.2500 1.000000 1.00000 1.000000 1.00000 1.000000 \n",
650
+ "max 800.0000 1.000000 1.00000 1.000000 1.00000 1.000000 \n",
651
+ "\n",
652
+ " A6_Score A7_Score A8_Score A9_Score A10_Score age \\\n",
653
+ "count 800.00000 800.000000 800.000000 800.000000 800.000000 800.000000 \n",
654
+ "mean 0.20875 0.273750 0.717500 0.316250 0.460000 28.612306 \n",
655
+ "std 0.40667 0.446161 0.450497 0.465303 0.498709 12.872373 \n",
656
+ "min 0.00000 0.000000 0.000000 0.000000 0.000000 9.560505 \n",
657
+ "25% 0.00000 0.000000 0.000000 0.000000 0.000000 19.282082 \n",
658
+ "50% 0.00000 0.000000 1.000000 0.000000 0.000000 25.479960 \n",
659
+ "75% 0.00000 1.000000 1.000000 1.000000 1.000000 33.154755 \n",
660
+ "max 1.00000 1.000000 1.000000 1.000000 1.000000 72.402488 \n",
661
+ "\n",
662
+ " result Class/ASD \n",
663
+ "count 800.000000 800.000000 \n",
664
+ "mean 7.058530 0.231250 \n",
665
+ "std 3.788969 0.421896 \n",
666
+ "min -2.594654 0.000000 \n",
667
+ "25% 4.527556 0.000000 \n",
668
+ "50% 6.893472 0.000000 \n",
669
+ "75% 9.892981 0.000000 \n",
670
+ "max 13.390868 1.000000 "
671
+ ]
672
+ },
673
+ "execution_count": 4,
674
+ "metadata": {},
675
+ "output_type": "execute_result"
676
+ }
677
+ ],
678
+ "source": [
679
+ "data.describe()"
680
+ ]
681
+ },
682
+ {
683
+ "cell_type": "code",
684
+ "execution_count": 5,
685
+ "metadata": {},
686
+ "outputs": [
687
+ {
688
+ "data": {
689
+ "text/plain": [
690
+ "ID 0\n",
691
+ "gender 0\n",
692
+ "A1_Score 0\n",
693
+ "A2_Score 0\n",
694
+ "A3_Score 0\n",
695
+ "A4_Score 0\n",
696
+ "A5_Score 0\n",
697
+ "A6_Score 0\n",
698
+ "A7_Score 0\n",
699
+ "A8_Score 0\n",
700
+ "A9_Score 0\n",
701
+ "A10_Score 0\n",
702
+ "jaundice 0\n",
703
+ "austim 0\n",
704
+ "age 0\n",
705
+ "ethnicity 0\n",
706
+ "contry_of_res 0\n",
707
+ "used_app_before 0\n",
708
+ "result 0\n",
709
+ "relation 0\n",
710
+ "age_desc 0\n",
711
+ "Class/ASD 0\n",
712
+ "dtype: int64"
713
+ ]
714
+ },
715
+ "execution_count": 5,
716
+ "metadata": {},
717
+ "output_type": "execute_result"
718
+ }
719
+ ],
720
+ "source": [
721
+ "data.isna().sum()"
722
+ ]
723
+ },
724
+ {
725
+ "cell_type": "markdown",
726
+ "metadata": {},
727
+ "source": [
728
+ "# Preprocessing"
729
+ ]
730
+ },
731
+ {
732
+ "cell_type": "markdown",
733
+ "metadata": {},
734
+ "source": [
735
+ "### 1.Data dosen't have a null value"
736
+ ]
737
+ },
738
+ {
739
+ "cell_type": "markdown",
740
+ "metadata": {},
741
+ "source": [
742
+ "### 2.Data Encoding"
743
+ ]
744
+ },
745
+ {
746
+ "cell_type": "code",
747
+ "execution_count": 6,
748
+ "metadata": {},
749
+ "outputs": [
750
+ {
751
+ "data": {
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+ "text/html": [
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+ " <thead>\n",
769
+ " <tr style=\"text-align: right;\">\n",
770
+ " <th></th>\n",
771
+ " <th>ID</th>\n",
772
+ " <th>gender</th>\n",
773
+ " <th>A1_Score</th>\n",
774
+ " <th>A2_Score</th>\n",
775
+ " <th>A3_Score</th>\n",
776
+ " <th>A4_Score</th>\n",
777
+ " <th>A5_Score</th>\n",
778
+ " <th>A6_Score</th>\n",
779
+ " <th>A7_Score</th>\n",
780
+ " <th>A8_Score</th>\n",
781
+ " <th>...</th>\n",
782
+ " <th>jaundice</th>\n",
783
+ " <th>austim</th>\n",
784
+ " <th>age</th>\n",
785
+ " <th>ethnicity</th>\n",
786
+ " <th>contry_of_res</th>\n",
787
+ " <th>used_app_before</th>\n",
788
+ " <th>result</th>\n",
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+ " <th>relation</th>\n",
790
+ " <th>age_desc</th>\n",
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+ " <th>Class/ASD</th>\n",
792
+ " </tr>\n",
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+ " </thead>\n",
794
+ " <tbody>\n",
795
+ " <tr>\n",
796
+ " <th>0</th>\n",
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+ " <td>1</td>\n",
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+ " <td>f</td>\n",
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+ " <td>1</td>\n",
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+ " <td>0</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>0</td>\n",
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+ " <td>1</td>\n",
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+ " <td>...</td>\n",
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+ " <td>no</td>\n",
809
+ " <td>no</td>\n",
810
+ " <td>18.605397</td>\n",
811
+ " <td>White-European</td>\n",
812
+ " <td>United States</td>\n",
813
+ " <td>no</td>\n",
814
+ " <td>7.819715</td>\n",
815
+ " <td>Self</td>\n",
816
+ " <td>18 and more</td>\n",
817
+ " <td>0</td>\n",
818
+ " </tr>\n",
819
+ " <tr>\n",
820
+ " <th>1</th>\n",
821
+ " <td>2</td>\n",
822
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823
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+ " <td>no</td>\n",
833
+ " <td>no</td>\n",
834
+ " <td>13.829369</td>\n",
835
+ " <td>South Asian</td>\n",
836
+ " <td>Australia</td>\n",
837
+ " <td>no</td>\n",
838
+ " <td>10.544296</td>\n",
839
+ " <td>?</td>\n",
840
+ " <td>18 and more</td>\n",
841
+ " <td>0</td>\n",
842
+ " </tr>\n",
843
+ " <tr>\n",
844
+ " <th>2</th>\n",
845
+ " <td>3</td>\n",
846
+ " <td>f</td>\n",
847
+ " <td>1</td>\n",
848
+ " <td>1</td>\n",
849
+ " <td>1</td>\n",
850
+ " <td>1</td>\n",
851
+ " <td>1</td>\n",
852
+ " <td>1</td>\n",
853
+ " <td>0</td>\n",
854
+ " <td>0</td>\n",
855
+ " <td>...</td>\n",
856
+ " <td>no</td>\n",
857
+ " <td>no</td>\n",
858
+ " <td>14.679893</td>\n",
859
+ " <td>White-European</td>\n",
860
+ " <td>United Kingdom</td>\n",
861
+ " <td>no</td>\n",
862
+ " <td>13.167506</td>\n",
863
+ " <td>Self</td>\n",
864
+ " <td>18 and more</td>\n",
865
+ " <td>1</td>\n",
866
+ " </tr>\n",
867
+ " <tr>\n",
868
+ " <th>3</th>\n",
869
+ " <td>4</td>\n",
870
+ " <td>f</td>\n",
871
+ " <td>0</td>\n",
872
+ " <td>0</td>\n",
873
+ " <td>0</td>\n",
874
+ " <td>1</td>\n",
875
+ " <td>0</td>\n",
876
+ " <td>0</td>\n",
877
+ " <td>0</td>\n",
878
+ " <td>0</td>\n",
879
+ " <td>...</td>\n",
880
+ " <td>no</td>\n",
881
+ " <td>no</td>\n",
882
+ " <td>61.035288</td>\n",
883
+ " <td>South Asian</td>\n",
884
+ " <td>New Zealand</td>\n",
885
+ " <td>no</td>\n",
886
+ " <td>1.530098</td>\n",
887
+ " <td>?</td>\n",
888
+ " <td>18 and more</td>\n",
889
+ " <td>0</td>\n",
890
+ " </tr>\n",
891
+ " <tr>\n",
892
+ " <th>4</th>\n",
893
+ " <td>5</td>\n",
894
+ " <td>m</td>\n",
895
+ " <td>0</td>\n",
896
+ " <td>0</td>\n",
897
+ " <td>0</td>\n",
898
+ " <td>0</td>\n",
899
+ " <td>1</td>\n",
900
+ " <td>0</td>\n",
901
+ " <td>0</td>\n",
902
+ " <td>0</td>\n",
903
+ " <td>...</td>\n",
904
+ " <td>no</td>\n",
905
+ " <td>yes</td>\n",
906
+ " <td>14.256686</td>\n",
907
+ " <td>Black</td>\n",
908
+ " <td>Italy</td>\n",
909
+ " <td>no</td>\n",
910
+ " <td>7.949723</td>\n",
911
+ " <td>Self</td>\n",
912
+ " <td>18 and more</td>\n",
913
+ " <td>0</td>\n",
914
+ " </tr>\n",
915
+ " </tbody>\n",
916
+ "</table>\n",
917
+ "<p>5 rows × 22 columns</p>\n",
918
+ "</div>"
919
+ ],
920
+ "text/plain": [
921
+ " ID gender A1_Score A2_Score A3_Score A4_Score A5_Score A6_Score \\\n",
922
+ "0 1 f 1 0 1 1 1 1 \n",
923
+ "1 2 f 0 0 0 0 0 0 \n",
924
+ "2 3 f 1 1 1 1 1 1 \n",
925
+ "3 4 f 0 0 0 1 0 0 \n",
926
+ "4 5 m 0 0 0 0 1 0 \n",
927
+ "\n",
928
+ " A7_Score A8_Score ... jaundice austim age ethnicity \\\n",
929
+ "0 0 1 ... no no 18.605397 White-European \n",
930
+ "1 0 0 ... no no 13.829369 South Asian \n",
931
+ "2 0 0 ... no no 14.679893 White-European \n",
932
+ "3 0 0 ... no no 61.035288 South Asian \n",
933
+ "4 0 0 ... no yes 14.256686 Black \n",
934
+ "\n",
935
+ " contry_of_res used_app_before result relation age_desc Class/ASD \n",
936
+ "0 United States no 7.819715 Self 18 and more 0 \n",
937
+ "1 Australia no 10.544296 ? 18 and more 0 \n",
938
+ "2 United Kingdom no 13.167506 Self 18 and more 1 \n",
939
+ "3 New Zealand no 1.530098 ? 18 and more 0 \n",
940
+ "4 Italy no 7.949723 Self 18 and more 0 \n",
941
+ "\n",
942
+ "[5 rows x 22 columns]"
943
+ ]
944
+ },
945
+ "execution_count": 6,
946
+ "metadata": {},
947
+ "output_type": "execute_result"
948
+ }
949
+ ],
950
+ "source": [
951
+ "data.head()"
952
+ ]
953
+ },
954
+ {
955
+ "cell_type": "code",
956
+ "execution_count": 7,
957
+ "metadata": {},
958
+ "outputs": [],
959
+ "source": [
960
+ "cat = {'ethnicity':'category',\n",
961
+ " 'gender':'category', \n",
962
+ " 'jaundice':'category',\n",
963
+ " 'austim':'category',\n",
964
+ " 'contry_of_res':'category', \n",
965
+ " 'used_app_before':'category',\n",
966
+ " 'age_desc':'category',\n",
967
+ " 'relation':'category'}\n",
968
+ "data = data.astype(cat)"
969
+ ]
970
+ },
971
+ {
972
+ "cell_type": "code",
973
+ "execution_count": 8,
974
+ "metadata": {},
975
+ "outputs": [],
976
+ "source": [
977
+ "cat_columns = ['ethnicity', 'gender', 'jaundice', 'austim', 'contry_of_res', 'used_app_before', 'age_desc', 'relation']\n",
978
+ "\n",
979
+ "for col in cat_columns:\n",
980
+ " data[col] = data[col].cat.codes\n"
981
+ ]
982
+ },
983
+ {
984
+ "cell_type": "code",
985
+ "execution_count": 9,
986
+ "metadata": {},
987
+ "outputs": [
988
+ {
989
+ "data": {
990
+ "text/html": [
991
+ "<div>\n",
992
+ "<style scoped>\n",
993
+ " .dataframe tbody tr th:only-of-type {\n",
994
+ " vertical-align: middle;\n",
995
+ " }\n",
996
+ "\n",
997
+ " .dataframe tbody tr th {\n",
998
+ " vertical-align: top;\n",
999
+ " }\n",
1000
+ "\n",
1001
+ " .dataframe thead th {\n",
1002
+ " text-align: right;\n",
1003
+ " }\n",
1004
+ "</style>\n",
1005
+ "<table border=\"1\" class=\"dataframe\">\n",
1006
+ " <thead>\n",
1007
+ " <tr style=\"text-align: right;\">\n",
1008
+ " <th></th>\n",
1009
+ " <th>ID</th>\n",
1010
+ " <th>gender</th>\n",
1011
+ " <th>A1_Score</th>\n",
1012
+ " <th>A2_Score</th>\n",
1013
+ " <th>A3_Score</th>\n",
1014
+ " <th>A4_Score</th>\n",
1015
+ " <th>A5_Score</th>\n",
1016
+ " <th>A6_Score</th>\n",
1017
+ " <th>A7_Score</th>\n",
1018
+ " <th>A8_Score</th>\n",
1019
+ " <th>...</th>\n",
1020
+ " <th>jaundice</th>\n",
1021
+ " <th>austim</th>\n",
1022
+ " <th>age</th>\n",
1023
+ " <th>ethnicity</th>\n",
1024
+ " <th>contry_of_res</th>\n",
1025
+ " <th>used_app_before</th>\n",
1026
+ " <th>result</th>\n",
1027
+ " <th>relation</th>\n",
1028
+ " <th>age_desc</th>\n",
1029
+ " <th>Class/ASD</th>\n",
1030
+ " </tr>\n",
1031
+ " </thead>\n",
1032
+ " <tbody>\n",
1033
+ " <tr>\n",
1034
+ " <th>0</th>\n",
1035
+ " <td>1</td>\n",
1036
+ " <td>0</td>\n",
1037
+ " <td>1</td>\n",
1038
+ " <td>0</td>\n",
1039
+ " <td>1</td>\n",
1040
+ " <td>1</td>\n",
1041
+ " <td>1</td>\n",
1042
+ " <td>1</td>\n",
1043
+ " <td>0</td>\n",
1044
+ " <td>1</td>\n",
1045
+ " <td>...</td>\n",
1046
+ " <td>0</td>\n",
1047
+ " <td>0</td>\n",
1048
+ " <td>18.605397</td>\n",
1049
+ " <td>10</td>\n",
1050
+ " <td>58</td>\n",
1051
+ " <td>0</td>\n",
1052
+ " <td>7.819715</td>\n",
1053
+ " <td>5</td>\n",
1054
+ " <td>0</td>\n",
1055
+ " <td>0</td>\n",
1056
+ " </tr>\n",
1057
+ " <tr>\n",
1058
+ " <th>1</th>\n",
1059
+ " <td>2</td>\n",
1060
+ " <td>0</td>\n",
1061
+ " <td>0</td>\n",
1062
+ " <td>0</td>\n",
1063
+ " <td>0</td>\n",
1064
+ " <td>0</td>\n",
1065
+ " <td>0</td>\n",
1066
+ " <td>0</td>\n",
1067
+ " <td>0</td>\n",
1068
+ " <td>0</td>\n",
1069
+ " <td>...</td>\n",
1070
+ " <td>0</td>\n",
1071
+ " <td>0</td>\n",
1072
+ " <td>13.829369</td>\n",
1073
+ " <td>8</td>\n",
1074
+ " <td>6</td>\n",
1075
+ " <td>0</td>\n",
1076
+ " <td>10.544296</td>\n",
1077
+ " <td>0</td>\n",
1078
+ " <td>0</td>\n",
1079
+ " <td>0</td>\n",
1080
+ " </tr>\n",
1081
+ " <tr>\n",
1082
+ " <th>2</th>\n",
1083
+ " <td>3</td>\n",
1084
+ " <td>0</td>\n",
1085
+ " <td>1</td>\n",
1086
+ " <td>1</td>\n",
1087
+ " <td>1</td>\n",
1088
+ " <td>1</td>\n",
1089
+ " <td>1</td>\n",
1090
+ " <td>1</td>\n",
1091
+ " <td>0</td>\n",
1092
+ " <td>0</td>\n",
1093
+ " <td>...</td>\n",
1094
+ " <td>0</td>\n",
1095
+ " <td>0</td>\n",
1096
+ " <td>14.679893</td>\n",
1097
+ " <td>10</td>\n",
1098
+ " <td>57</td>\n",
1099
+ " <td>0</td>\n",
1100
+ " <td>13.167506</td>\n",
1101
+ " <td>5</td>\n",
1102
+ " <td>0</td>\n",
1103
+ " <td>1</td>\n",
1104
+ " </tr>\n",
1105
+ " <tr>\n",
1106
+ " <th>3</th>\n",
1107
+ " <td>4</td>\n",
1108
+ " <td>0</td>\n",
1109
+ " <td>0</td>\n",
1110
+ " <td>0</td>\n",
1111
+ " <td>0</td>\n",
1112
+ " <td>1</td>\n",
1113
+ " <td>0</td>\n",
1114
+ " <td>0</td>\n",
1115
+ " <td>0</td>\n",
1116
+ " <td>0</td>\n",
1117
+ " <td>...</td>\n",
1118
+ " <td>0</td>\n",
1119
+ " <td>0</td>\n",
1120
+ " <td>61.035288</td>\n",
1121
+ " <td>8</td>\n",
1122
+ " <td>39</td>\n",
1123
+ " <td>0</td>\n",
1124
+ " <td>1.530098</td>\n",
1125
+ " <td>0</td>\n",
1126
+ " <td>0</td>\n",
1127
+ " <td>0</td>\n",
1128
+ " </tr>\n",
1129
+ " <tr>\n",
1130
+ " <th>4</th>\n",
1131
+ " <td>5</td>\n",
1132
+ " <td>1</td>\n",
1133
+ " <td>0</td>\n",
1134
+ " <td>0</td>\n",
1135
+ " <td>0</td>\n",
1136
+ " <td>0</td>\n",
1137
+ " <td>1</td>\n",
1138
+ " <td>0</td>\n",
1139
+ " <td>0</td>\n",
1140
+ " <td>0</td>\n",
1141
+ " <td>...</td>\n",
1142
+ " <td>0</td>\n",
1143
+ " <td>1</td>\n",
1144
+ " <td>14.256686</td>\n",
1145
+ " <td>2</td>\n",
1146
+ " <td>32</td>\n",
1147
+ " <td>0</td>\n",
1148
+ " <td>7.949723</td>\n",
1149
+ " <td>5</td>\n",
1150
+ " <td>0</td>\n",
1151
+ " <td>0</td>\n",
1152
+ " </tr>\n",
1153
+ " </tbody>\n",
1154
+ "</table>\n",
1155
+ "<p>5 rows × 22 columns</p>\n",
1156
+ "</div>"
1157
+ ],
1158
+ "text/plain": [
1159
+ " ID gender A1_Score A2_Score A3_Score A4_Score A5_Score A6_Score \\\n",
1160
+ "0 1 0 1 0 1 1 1 1 \n",
1161
+ "1 2 0 0 0 0 0 0 0 \n",
1162
+ "2 3 0 1 1 1 1 1 1 \n",
1163
+ "3 4 0 0 0 0 1 0 0 \n",
1164
+ "4 5 1 0 0 0 0 1 0 \n",
1165
+ "\n",
1166
+ " A7_Score A8_Score ... jaundice austim age ethnicity \\\n",
1167
+ "0 0 1 ... 0 0 18.605397 10 \n",
1168
+ "1 0 0 ... 0 0 13.829369 8 \n",
1169
+ "2 0 0 ... 0 0 14.679893 10 \n",
1170
+ "3 0 0 ... 0 0 61.035288 8 \n",
1171
+ "4 0 0 ... 0 1 14.256686 2 \n",
1172
+ "\n",
1173
+ " contry_of_res used_app_before result relation age_desc Class/ASD \n",
1174
+ "0 58 0 7.819715 5 0 0 \n",
1175
+ "1 6 0 10.544296 0 0 0 \n",
1176
+ "2 57 0 13.167506 5 0 1 \n",
1177
+ "3 39 0 1.530098 0 0 0 \n",
1178
+ "4 32 0 7.949723 5 0 0 \n",
1179
+ "\n",
1180
+ "[5 rows x 22 columns]"
1181
+ ]
1182
+ },
1183
+ "execution_count": 9,
1184
+ "metadata": {},
1185
+ "output_type": "execute_result"
1186
+ }
1187
+ ],
1188
+ "source": [
1189
+ "data.head()"
1190
+ ]
1191
+ },
1192
+ {
1193
+ "cell_type": "code",
1194
+ "execution_count": 10,
1195
+ "metadata": {},
1196
+ "outputs": [
1197
+ {
1198
+ "name": "stdout",
1199
+ "output_type": "stream",
1200
+ "text": [
1201
+ "ID int64\n",
1202
+ "gender int8\n",
1203
+ "A1_Score int64\n",
1204
+ "A2_Score int64\n",
1205
+ "A3_Score int64\n",
1206
+ "A4_Score int64\n",
1207
+ "A5_Score int64\n",
1208
+ "A6_Score int64\n",
1209
+ "A7_Score int64\n",
1210
+ "A8_Score int64\n",
1211
+ "A9_Score int64\n",
1212
+ "A10_Score int64\n",
1213
+ "jaundice int8\n",
1214
+ "austim int8\n",
1215
+ "age float64\n",
1216
+ "ethnicity int8\n",
1217
+ "contry_of_res int8\n",
1218
+ "used_app_before int8\n",
1219
+ "result float64\n",
1220
+ "relation int8\n",
1221
+ "age_desc int8\n",
1222
+ "Class/ASD int64\n",
1223
+ "dtype: object\n"
1224
+ ]
1225
+ }
1226
+ ],
1227
+ "source": [
1228
+ "print(data.dtypes)"
1229
+ ]
1230
+ },
1231
+ {
1232
+ "cell_type": "markdown",
1233
+ "metadata": {},
1234
+ "source": [
1235
+ "### 3.Drob unusiful data"
1236
+ ]
1237
+ },
1238
+ {
1239
+ "cell_type": "code",
1240
+ "execution_count": 11,
1241
+ "metadata": {},
1242
+ "outputs": [],
1243
+ "source": [
1244
+ "data=data.drop('ID', axis=1)\n",
1245
+ "data=data.drop('used_app_before', axis=1)\n",
1246
+ "data=data.drop('relation', axis=1)\n",
1247
+ "data=data.drop('result', axis=1)\n",
1248
+ "data=data.drop('age_desc', axis=1)\n",
1249
+ "data=data.drop('contry_of_res', axis=1)"
1250
+ ]
1251
+ },
1252
+ {
1253
+ "cell_type": "markdown",
1254
+ "metadata": {},
1255
+ "source": [
1256
+ "### 4.Split Data"
1257
+ ]
1258
+ },
1259
+ {
1260
+ "cell_type": "code",
1261
+ "execution_count": 12,
1262
+ "metadata": {},
1263
+ "outputs": [],
1264
+ "source": [
1265
+ "X = data.drop('Class/ASD', axis=1)\n",
1266
+ "y = data['Class/ASD']\n",
1267
+ "X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=3)"
1268
+ ]
1269
+ },
1270
+ {
1271
+ "cell_type": "markdown",
1272
+ "metadata": {},
1273
+ "source": [
1274
+ "### 5.Standard Scaler\n"
1275
+ ]
1276
+ },
1277
+ {
1278
+ "cell_type": "code",
1279
+ "execution_count": 13,
1280
+ "metadata": {},
1281
+ "outputs": [],
1282
+ "source": [
1283
+ "scaler = StandardScaler()\n",
1284
+ "X_train = scaler.fit_transform(X_train)\n",
1285
+ "X_val = scaler.transform(X_val)"
1286
+ ]
1287
+ },
1288
+ {
1289
+ "cell_type": "markdown",
1290
+ "metadata": {},
1291
+ "source": [
1292
+ "# Classification"
1293
+ ]
1294
+ },
1295
+ {
1296
+ "cell_type": "code",
1297
+ "execution_count": 14,
1298
+ "metadata": {},
1299
+ "outputs": [],
1300
+ "source": [
1301
+ "model = LogisticRegression()"
1302
+ ]
1303
+ },
1304
+ {
1305
+ "cell_type": "code",
1306
+ "execution_count": 15,
1307
+ "metadata": {},
1308
+ "outputs": [
1309
+ {
1310
+ "data": {
1311
+ "text/html": [
1312
+ "<style>#sk-container-id-1 {\n",
1313
+ " /* Definition of color scheme common for light and dark mode */\n",
1314
+ " --sklearn-color-text: black;\n",
1315
+ " --sklearn-color-line: gray;\n",
1316
+ " /* Definition of color scheme for unfitted estimators */\n",
1317
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
1318
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
1319
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
1320
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
1321
+ " /* Definition of color scheme for fitted estimators */\n",
1322
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
1323
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
1324
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
1325
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
1326
+ "\n",
1327
+ " /* Specific color for light theme */\n",
1328
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
1329
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
1330
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
1331
+ " --sklearn-color-icon: #696969;\n",
1332
+ "\n",
1333
+ " @media (prefers-color-scheme: dark) {\n",
1334
+ " /* Redefinition of color scheme for dark theme */\n",
1335
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
1336
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
1337
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
1338
+ " --sklearn-color-icon: #878787;\n",
1339
+ " }\n",
1340
+ "}\n",
1341
+ "\n",
1342
+ "#sk-container-id-1 {\n",
1343
+ " color: var(--sklearn-color-text);\n",
1344
+ "}\n",
1345
+ "\n",
1346
+ "#sk-container-id-1 pre {\n",
1347
+ " padding: 0;\n",
1348
+ "}\n",
1349
+ "\n",
1350
+ "#sk-container-id-1 input.sk-hidden--visually {\n",
1351
+ " border: 0;\n",
1352
+ " clip: rect(1px 1px 1px 1px);\n",
1353
+ " clip: rect(1px, 1px, 1px, 1px);\n",
1354
+ " height: 1px;\n",
1355
+ " margin: -1px;\n",
1356
+ " overflow: hidden;\n",
1357
+ " padding: 0;\n",
1358
+ " position: absolute;\n",
1359
+ " width: 1px;\n",
1360
+ "}\n",
1361
+ "\n",
1362
+ "#sk-container-id-1 div.sk-dashed-wrapped {\n",
1363
+ " border: 1px dashed var(--sklearn-color-line);\n",
1364
+ " margin: 0 0.4em 0.5em 0.4em;\n",
1365
+ " box-sizing: border-box;\n",
1366
+ " padding-bottom: 0.4em;\n",
1367
+ " background-color: var(--sklearn-color-background);\n",
1368
+ "}\n",
1369
+ "\n",
1370
+ "#sk-container-id-1 div.sk-container {\n",
1371
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
1372
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
1373
+ " so we also need the `!important` here to be able to override the\n",
1374
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
1375
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
1376
+ " display: inline-block !important;\n",
1377
+ " position: relative;\n",
1378
+ "}\n",
1379
+ "\n",
1380
+ "#sk-container-id-1 div.sk-text-repr-fallback {\n",
1381
+ " display: none;\n",
1382
+ "}\n",
1383
+ "\n",
1384
+ "div.sk-parallel-item,\n",
1385
+ "div.sk-serial,\n",
1386
+ "div.sk-item {\n",
1387
+ " /* draw centered vertical line to link estimators */\n",
1388
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
1389
+ " background-size: 2px 100%;\n",
1390
+ " background-repeat: no-repeat;\n",
1391
+ " background-position: center center;\n",
1392
+ "}\n",
1393
+ "\n",
1394
+ "/* Parallel-specific style estimator block */\n",
1395
+ "\n",
1396
+ "#sk-container-id-1 div.sk-parallel-item::after {\n",
1397
+ " content: \"\";\n",
1398
+ " width: 100%;\n",
1399
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
1400
+ " flex-grow: 1;\n",
1401
+ "}\n",
1402
+ "\n",
1403
+ "#sk-container-id-1 div.sk-parallel {\n",
1404
+ " display: flex;\n",
1405
+ " align-items: stretch;\n",
1406
+ " justify-content: center;\n",
1407
+ " background-color: var(--sklearn-color-background);\n",
1408
+ " position: relative;\n",
1409
+ "}\n",
1410
+ "\n",
1411
+ "#sk-container-id-1 div.sk-parallel-item {\n",
1412
+ " display: flex;\n",
1413
+ " flex-direction: column;\n",
1414
+ "}\n",
1415
+ "\n",
1416
+ "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
1417
+ " align-self: flex-end;\n",
1418
+ " width: 50%;\n",
1419
+ "}\n",
1420
+ "\n",
1421
+ "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
1422
+ " align-self: flex-start;\n",
1423
+ " width: 50%;\n",
1424
+ "}\n",
1425
+ "\n",
1426
+ "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
1427
+ " width: 0;\n",
1428
+ "}\n",
1429
+ "\n",
1430
+ "/* Serial-specific style estimator block */\n",
1431
+ "\n",
1432
+ "#sk-container-id-1 div.sk-serial {\n",
1433
+ " display: flex;\n",
1434
+ " flex-direction: column;\n",
1435
+ " align-items: center;\n",
1436
+ " background-color: var(--sklearn-color-background);\n",
1437
+ " padding-right: 1em;\n",
1438
+ " padding-left: 1em;\n",
1439
+ "}\n",
1440
+ "\n",
1441
+ "\n",
1442
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
1443
+ "clickable and can be expanded/collapsed.\n",
1444
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
1445
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
1446
+ "*/\n",
1447
+ "\n",
1448
+ "/* Pipeline and ColumnTransformer style (default) */\n",
1449
+ "\n",
1450
+ "#sk-container-id-1 div.sk-toggleable {\n",
1451
+ " /* Default theme specific background. It is overwritten whether we have a\n",
1452
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
1453
+ " background-color: var(--sklearn-color-background);\n",
1454
+ "}\n",
1455
+ "\n",
1456
+ "/* Toggleable label */\n",
1457
+ "#sk-container-id-1 label.sk-toggleable__label {\n",
1458
+ " cursor: pointer;\n",
1459
+ " display: block;\n",
1460
+ " width: 100%;\n",
1461
+ " margin-bottom: 0;\n",
1462
+ " padding: 0.5em;\n",
1463
+ " box-sizing: border-box;\n",
1464
+ " text-align: center;\n",
1465
+ "}\n",
1466
+ "\n",
1467
+ "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
1468
+ " /* Arrow on the left of the label */\n",
1469
+ " content: \"▸\";\n",
1470
+ " float: left;\n",
1471
+ " margin-right: 0.25em;\n",
1472
+ " color: var(--sklearn-color-icon);\n",
1473
+ "}\n",
1474
+ "\n",
1475
+ "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
1476
+ " color: var(--sklearn-color-text);\n",
1477
+ "}\n",
1478
+ "\n",
1479
+ "/* Toggleable content - dropdown */\n",
1480
+ "\n",
1481
+ "#sk-container-id-1 div.sk-toggleable__content {\n",
1482
+ " max-height: 0;\n",
1483
+ " max-width: 0;\n",
1484
+ " overflow: hidden;\n",
1485
+ " text-align: left;\n",
1486
+ " /* unfitted */\n",
1487
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
1488
+ "}\n",
1489
+ "\n",
1490
+ "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
1491
+ " /* fitted */\n",
1492
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
1493
+ "}\n",
1494
+ "\n",
1495
+ "#sk-container-id-1 div.sk-toggleable__content pre {\n",
1496
+ " margin: 0.2em;\n",
1497
+ " border-radius: 0.25em;\n",
1498
+ " color: var(--sklearn-color-text);\n",
1499
+ " /* unfitted */\n",
1500
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
1501
+ "}\n",
1502
+ "\n",
1503
+ "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
1504
+ " /* unfitted */\n",
1505
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
1506
+ "}\n",
1507
+ "\n",
1508
+ "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
1509
+ " /* Expand drop-down */\n",
1510
+ " max-height: 200px;\n",
1511
+ " max-width: 100%;\n",
1512
+ " overflow: auto;\n",
1513
+ "}\n",
1514
+ "\n",
1515
+ "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
1516
+ " content: \"▾\";\n",
1517
+ "}\n",
1518
+ "\n",
1519
+ "/* Pipeline/ColumnTransformer-specific style */\n",
1520
+ "\n",
1521
+ "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
1522
+ " color: var(--sklearn-color-text);\n",
1523
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
1524
+ "}\n",
1525
+ "\n",
1526
+ "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
1527
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
1528
+ "}\n",
1529
+ "\n",
1530
+ "/* Estimator-specific style */\n",
1531
+ "\n",
1532
+ "/* Colorize estimator box */\n",
1533
+ "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
1534
+ " /* unfitted */\n",
1535
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
1536
+ "}\n",
1537
+ "\n",
1538
+ "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
1539
+ " /* fitted */\n",
1540
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
1541
+ "}\n",
1542
+ "\n",
1543
+ "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
1544
+ "#sk-container-id-1 div.sk-label label {\n",
1545
+ " /* The background is the default theme color */\n",
1546
+ " color: var(--sklearn-color-text-on-default-background);\n",
1547
+ "}\n",
1548
+ "\n",
1549
+ "/* On hover, darken the color of the background */\n",
1550
+ "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
1551
+ " color: var(--sklearn-color-text);\n",
1552
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
1553
+ "}\n",
1554
+ "\n",
1555
+ "/* Label box, darken color on hover, fitted */\n",
1556
+ "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
1557
+ " color: var(--sklearn-color-text);\n",
1558
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
1559
+ "}\n",
1560
+ "\n",
1561
+ "/* Estimator label */\n",
1562
+ "\n",
1563
+ "#sk-container-id-1 div.sk-label label {\n",
1564
+ " font-family: monospace;\n",
1565
+ " font-weight: bold;\n",
1566
+ " display: inline-block;\n",
1567
+ " line-height: 1.2em;\n",
1568
+ "}\n",
1569
+ "\n",
1570
+ "#sk-container-id-1 div.sk-label-container {\n",
1571
+ " text-align: center;\n",
1572
+ "}\n",
1573
+ "\n",
1574
+ "/* Estimator-specific */\n",
1575
+ "#sk-container-id-1 div.sk-estimator {\n",
1576
+ " font-family: monospace;\n",
1577
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
1578
+ " border-radius: 0.25em;\n",
1579
+ " box-sizing: border-box;\n",
1580
+ " margin-bottom: 0.5em;\n",
1581
+ " /* unfitted */\n",
1582
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
1583
+ "}\n",
1584
+ "\n",
1585
+ "#sk-container-id-1 div.sk-estimator.fitted {\n",
1586
+ " /* fitted */\n",
1587
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
1588
+ "}\n",
1589
+ "\n",
1590
+ "/* on hover */\n",
1591
+ "#sk-container-id-1 div.sk-estimator:hover {\n",
1592
+ " /* unfitted */\n",
1593
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
1594
+ "}\n",
1595
+ "\n",
1596
+ "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
1597
+ " /* fitted */\n",
1598
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
1599
+ "}\n",
1600
+ "\n",
1601
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
1602
+ "\n",
1603
+ "/* Common style for \"i\" and \"?\" */\n",
1604
+ "\n",
1605
+ ".sk-estimator-doc-link,\n",
1606
+ "a:link.sk-estimator-doc-link,\n",
1607
+ "a:visited.sk-estimator-doc-link {\n",
1608
+ " float: right;\n",
1609
+ " font-size: smaller;\n",
1610
+ " line-height: 1em;\n",
1611
+ " font-family: monospace;\n",
1612
+ " background-color: var(--sklearn-color-background);\n",
1613
+ " border-radius: 1em;\n",
1614
+ " height: 1em;\n",
1615
+ " width: 1em;\n",
1616
+ " text-decoration: none !important;\n",
1617
+ " margin-left: 1ex;\n",
1618
+ " /* unfitted */\n",
1619
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
1620
+ " color: var(--sklearn-color-unfitted-level-1);\n",
1621
+ "}\n",
1622
+ "\n",
1623
+ ".sk-estimator-doc-link.fitted,\n",
1624
+ "a:link.sk-estimator-doc-link.fitted,\n",
1625
+ "a:visited.sk-estimator-doc-link.fitted {\n",
1626
+ " /* fitted */\n",
1627
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
1628
+ " color: var(--sklearn-color-fitted-level-1);\n",
1629
+ "}\n",
1630
+ "\n",
1631
+ "/* On hover */\n",
1632
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
1633
+ ".sk-estimator-doc-link:hover,\n",
1634
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
1635
+ ".sk-estimator-doc-link:hover {\n",
1636
+ " /* unfitted */\n",
1637
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
1638
+ " color: var(--sklearn-color-background);\n",
1639
+ " text-decoration: none;\n",
1640
+ "}\n",
1641
+ "\n",
1642
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
1643
+ ".sk-estimator-doc-link.fitted:hover,\n",
1644
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
1645
+ ".sk-estimator-doc-link.fitted:hover {\n",
1646
+ " /* fitted */\n",
1647
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
1648
+ " color: var(--sklearn-color-background);\n",
1649
+ " text-decoration: none;\n",
1650
+ "}\n",
1651
+ "\n",
1652
+ "/* Span, style for the box shown on hovering the info icon */\n",
1653
+ ".sk-estimator-doc-link span {\n",
1654
+ " display: none;\n",
1655
+ " z-index: 9999;\n",
1656
+ " position: relative;\n",
1657
+ " font-weight: normal;\n",
1658
+ " right: .2ex;\n",
1659
+ " padding: .5ex;\n",
1660
+ " margin: .5ex;\n",
1661
+ " width: min-content;\n",
1662
+ " min-width: 20ex;\n",
1663
+ " max-width: 50ex;\n",
1664
+ " color: var(--sklearn-color-text);\n",
1665
+ " box-shadow: 2pt 2pt 4pt #999;\n",
1666
+ " /* unfitted */\n",
1667
+ " background: var(--sklearn-color-unfitted-level-0);\n",
1668
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
1669
+ "}\n",
1670
+ "\n",
1671
+ ".sk-estimator-doc-link.fitted span {\n",
1672
+ " /* fitted */\n",
1673
+ " background: var(--sklearn-color-fitted-level-0);\n",
1674
+ " border: var(--sklearn-color-fitted-level-3);\n",
1675
+ "}\n",
1676
+ "\n",
1677
+ ".sk-estimator-doc-link:hover span {\n",
1678
+ " display: block;\n",
1679
+ "}\n",
1680
+ "\n",
1681
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
1682
+ "\n",
1683
+ "#sk-container-id-1 a.estimator_doc_link {\n",
1684
+ " float: right;\n",
1685
+ " font-size: 1rem;\n",
1686
+ " line-height: 1em;\n",
1687
+ " font-family: monospace;\n",
1688
+ " background-color: var(--sklearn-color-background);\n",
1689
+ " border-radius: 1rem;\n",
1690
+ " height: 1rem;\n",
1691
+ " width: 1rem;\n",
1692
+ " text-decoration: none;\n",
1693
+ " /* unfitted */\n",
1694
+ " color: var(--sklearn-color-unfitted-level-1);\n",
1695
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
1696
+ "}\n",
1697
+ "\n",
1698
+ "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
1699
+ " /* fitted */\n",
1700
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
1701
+ " color: var(--sklearn-color-fitted-level-1);\n",
1702
+ "}\n",
1703
+ "\n",
1704
+ "/* On hover */\n",
1705
+ "#sk-container-id-1 a.estimator_doc_link:hover {\n",
1706
+ " /* unfitted */\n",
1707
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
1708
+ " color: var(--sklearn-color-background);\n",
1709
+ " text-decoration: none;\n",
1710
+ "}\n",
1711
+ "\n",
1712
+ "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
1713
+ " /* fitted */\n",
1714
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
1715
+ "}\n",
1716
+ "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
1717
+ ],
1718
+ "text/plain": [
1719
+ "LogisticRegression()"
1720
+ ]
1721
+ },
1722
+ "execution_count": 15,
1723
+ "metadata": {},
1724
+ "output_type": "execute_result"
1725
+ }
1726
+ ],
1727
+ "source": [
1728
+ "model.fit(X_train, y_train)"
1729
+ ]
1730
+ },
1731
+ {
1732
+ "cell_type": "code",
1733
+ "execution_count": 16,
1734
+ "metadata": {},
1735
+ "outputs": [],
1736
+ "source": [
1737
+ "y_pred = model.predict(X_val)"
1738
+ ]
1739
+ },
1740
+ {
1741
+ "cell_type": "code",
1742
+ "execution_count": 17,
1743
+ "metadata": {},
1744
+ "outputs": [
1745
+ {
1746
+ "name": "stdout",
1747
+ "output_type": "stream",
1748
+ "text": [
1749
+ "Accuracy: 0.9\n"
1750
+ ]
1751
+ }
1752
+ ],
1753
+ "source": [
1754
+ "accuracy = accuracy_score(y_val, y_pred)\n",
1755
+ "print(\"Accuracy:\", accuracy)"
1756
+ ]
1757
+ },
1758
+ {
1759
+ "cell_type": "code",
1760
+ "execution_count": 18,
1761
+ "metadata": {},
1762
+ "outputs": [
1763
+ {
1764
+ "data": {
1765
+ "text/html": [
1766
+ "<div>\n",
1767
+ "<style scoped>\n",
1768
+ " .dataframe tbody tr th:only-of-type {\n",
1769
+ " vertical-align: middle;\n",
1770
+ " }\n",
1771
+ "\n",
1772
+ " .dataframe tbody tr th {\n",
1773
+ " vertical-align: top;\n",
1774
+ " }\n",
1775
+ "\n",
1776
+ " .dataframe thead th {\n",
1777
+ " text-align: right;\n",
1778
+ " }\n",
1779
+ "</style>\n",
1780
+ "<table border=\"1\" class=\"dataframe\">\n",
1781
+ " <thead>\n",
1782
+ " <tr style=\"text-align: right;\">\n",
1783
+ " <th></th>\n",
1784
+ " <th>gender</th>\n",
1785
+ " <th>A1_Score</th>\n",
1786
+ " <th>A2_Score</th>\n",
1787
+ " <th>A3_Score</th>\n",
1788
+ " <th>A4_Score</th>\n",
1789
+ " <th>A5_Score</th>\n",
1790
+ " <th>A6_Score</th>\n",
1791
+ " <th>A7_Score</th>\n",
1792
+ " <th>A8_Score</th>\n",
1793
+ " <th>A9_Score</th>\n",
1794
+ " <th>A10_Score</th>\n",
1795
+ " <th>jaundice</th>\n",
1796
+ " <th>austim</th>\n",
1797
+ " <th>age</th>\n",
1798
+ " <th>ethnicity</th>\n",
1799
+ " <th>Class/ASD</th>\n",
1800
+ " </tr>\n",
1801
+ " </thead>\n",
1802
+ " <tbody>\n",
1803
+ " <tr>\n",
1804
+ " <th>0</th>\n",
1805
+ " <td>0</td>\n",
1806
+ " <td>1</td>\n",
1807
+ " <td>0</td>\n",
1808
+ " <td>1</td>\n",
1809
+ " <td>1</td>\n",
1810
+ " <td>1</td>\n",
1811
+ " <td>1</td>\n",
1812
+ " <td>0</td>\n",
1813
+ " <td>1</td>\n",
1814
+ " <td>1</td>\n",
1815
+ " <td>1</td>\n",
1816
+ " <td>0</td>\n",
1817
+ " <td>0</td>\n",
1818
+ " <td>18.605397</td>\n",
1819
+ " <td>10</td>\n",
1820
+ " <td>0</td>\n",
1821
+ " </tr>\n",
1822
+ " <tr>\n",
1823
+ " <th>1</th>\n",
1824
+ " <td>0</td>\n",
1825
+ " <td>0</td>\n",
1826
+ " <td>0</td>\n",
1827
+ " <td>0</td>\n",
1828
+ " <td>0</td>\n",
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+ " <td>0</td>\n",
1830
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1831
+ " <td>0</td>\n",
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+ " <td>0</td>\n",
1833
+ " <td>0</td>\n",
1834
+ " <td>1</td>\n",
1835
+ " <td>0</td>\n",
1836
+ " <td>0</td>\n",
1837
+ " <td>13.829369</td>\n",
1838
+ " <td>8</td>\n",
1839
+ " <td>0</td>\n",
1840
+ " </tr>\n",
1841
+ " <tr>\n",
1842
+ " <th>2</th>\n",
1843
+ " <td>0</td>\n",
1844
+ " <td>1</td>\n",
1845
+ " <td>1</td>\n",
1846
+ " <td>1</td>\n",
1847
+ " <td>1</td>\n",
1848
+ " <td>1</td>\n",
1849
+ " <td>1</td>\n",
1850
+ " <td>0</td>\n",
1851
+ " <td>0</td>\n",
1852
+ " <td>1</td>\n",
1853
+ " <td>1</td>\n",
1854
+ " <td>0</td>\n",
1855
+ " <td>0</td>\n",
1856
+ " <td>14.679893</td>\n",
1857
+ " <td>10</td>\n",
1858
+ " <td>1</td>\n",
1859
+ " </tr>\n",
1860
+ " <tr>\n",
1861
+ " <th>3</th>\n",
1862
+ " <td>0</td>\n",
1863
+ " <td>0</td>\n",
1864
+ " <td>0</td>\n",
1865
+ " <td>0</td>\n",
1866
+ " <td>1</td>\n",
1867
+ " <td>0</td>\n",
1868
+ " <td>0</td>\n",
1869
+ " <td>0</td>\n",
1870
+ " <td>0</td>\n",
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+ " <td>0</td>\n",
1872
+ " <td>0</td>\n",
1873
+ " <td>0</td>\n",
1874
+ " <td>0</td>\n",
1875
+ " <td>61.035288</td>\n",
1876
+ " <td>8</td>\n",
1877
+ " <td>0</td>\n",
1878
+ " </tr>\n",
1879
+ " <tr>\n",
1880
+ " <th>4</th>\n",
1881
+ " <td>1</td>\n",
1882
+ " <td>0</td>\n",
1883
+ " <td>0</td>\n",
1884
+ " <td>0</td>\n",
1885
+ " <td>0</td>\n",
1886
+ " <td>1</td>\n",
1887
+ " <td>0</td>\n",
1888
+ " <td>0</td>\n",
1889
+ " <td>0</td>\n",
1890
+ " <td>1</td>\n",
1891
+ " <td>1</td>\n",
1892
+ " <td>0</td>\n",
1893
+ " <td>1</td>\n",
1894
+ " <td>14.256686</td>\n",
1895
+ " <td>2</td>\n",
1896
+ " <td>0</td>\n",
1897
+ " </tr>\n",
1898
+ " <tr>\n",
1899
+ " <th>...</th>\n",
1900
+ " <td>...</td>\n",
1901
+ " <td>...</td>\n",
1902
+ " <td>...</td>\n",
1903
+ " <td>...</td>\n",
1904
+ " <td>...</td>\n",
1905
+ " <td>...</td>\n",
1906
+ " <td>...</td>\n",
1907
+ " <td>...</td>\n",
1908
+ " <td>...</td>\n",
1909
+ " <td>...</td>\n",
1910
+ " <td>...</td>\n",
1911
+ " <td>...</td>\n",
1912
+ " <td>...</td>\n",
1913
+ " <td>...</td>\n",
1914
+ " <td>...</td>\n",
1915
+ " <td>...</td>\n",
1916
+ " </tr>\n",
1917
+ " <tr>\n",
1918
+ " <th>795</th>\n",
1919
+ " <td>0</td>\n",
1920
+ " <td>1</td>\n",
1921
+ " <td>1</td>\n",
1922
+ " <td>1</td>\n",
1923
+ " <td>1</td>\n",
1924
+ " <td>1</td>\n",
1925
+ " <td>1</td>\n",
1926
+ " <td>1</td>\n",
1927
+ " <td>1</td>\n",
1928
+ " <td>1</td>\n",
1929
+ " <td>1</td>\n",
1930
+ " <td>0</td>\n",
1931
+ " <td>1</td>\n",
1932
+ " <td>42.084907</td>\n",
1933
+ " <td>10</td>\n",
1934
+ " <td>1</td>\n",
1935
+ " </tr>\n",
1936
+ " <tr>\n",
1937
+ " <th>796</th>\n",
1938
+ " <td>0</td>\n",
1939
+ " <td>1</td>\n",
1940
+ " <td>1</td>\n",
1941
+ " <td>0</td>\n",
1942
+ " <td>0</td>\n",
1943
+ " <td>1</td>\n",
1944
+ " <td>0</td>\n",
1945
+ " <td>0</td>\n",
1946
+ " <td>0</td>\n",
1947
+ " <td>1</td>\n",
1948
+ " <td>1</td>\n",
1949
+ " <td>0</td>\n",
1950
+ " <td>0</td>\n",
1951
+ " <td>17.669291</td>\n",
1952
+ " <td>1</td>\n",
1953
+ " <td>0</td>\n",
1954
+ " </tr>\n",
1955
+ " <tr>\n",
1956
+ " <th>797</th>\n",
1957
+ " <td>1</td>\n",
1958
+ " <td>0</td>\n",
1959
+ " <td>0</td>\n",
1960
+ " <td>0</td>\n",
1961
+ " <td>0</td>\n",
1962
+ " <td>0</td>\n",
1963
+ " <td>0</td>\n",
1964
+ " <td>1</td>\n",
1965
+ " <td>0</td>\n",
1966
+ " <td>1</td>\n",
1967
+ " <td>1</td>\n",
1968
+ " <td>1</td>\n",
1969
+ " <td>0</td>\n",
1970
+ " <td>18.242557</td>\n",
1971
+ " <td>10</td>\n",
1972
+ " <td>1</td>\n",
1973
+ " </tr>\n",
1974
+ " <tr>\n",
1975
+ " <th>798</th>\n",
1976
+ " <td>0</td>\n",
1977
+ " <td>1</td>\n",
1978
+ " <td>1</td>\n",
1979
+ " <td>1</td>\n",
1980
+ " <td>1</td>\n",
1981
+ " <td>1</td>\n",
1982
+ " <td>1</td>\n",
1983
+ " <td>0</td>\n",
1984
+ " <td>1</td>\n",
1985
+ " <td>1</td>\n",
1986
+ " <td>1</td>\n",
1987
+ " <td>0</td>\n",
1988
+ " <td>1</td>\n",
1989
+ " <td>19.241473</td>\n",
1990
+ " <td>5</td>\n",
1991
+ " <td>0</td>\n",
1992
+ " </tr>\n",
1993
+ " <tr>\n",
1994
+ " <th>799</th>\n",
1995
+ " <td>0</td>\n",
1996
+ " <td>1</td>\n",
1997
+ " <td>0</td>\n",
1998
+ " <td>0</td>\n",
1999
+ " <td>1</td>\n",
2000
+ " <td>1</td>\n",
2001
+ " <td>0</td>\n",
2002
+ " <td>0</td>\n",
2003
+ " <td>1</td>\n",
2004
+ " <td>1</td>\n",
2005
+ " <td>1</td>\n",
2006
+ " <td>0</td>\n",
2007
+ " <td>0</td>\n",
2008
+ " <td>32.170098</td>\n",
2009
+ " <td>1</td>\n",
2010
+ " <td>0</td>\n",
2011
+ " </tr>\n",
2012
+ " </tbody>\n",
2013
+ "</table>\n",
2014
+ "<p>800 rows × 16 columns</p>\n",
2015
+ "</div>"
2016
+ ],
2017
+ "text/plain": [
2018
+ " gender A1_Score A2_Score A3_Score A4_Score A5_Score A6_Score \\\n",
2019
+ "0 0 1 0 1 1 1 1 \n",
2020
+ "1 0 0 0 0 0 0 0 \n",
2021
+ "2 0 1 1 1 1 1 1 \n",
2022
+ "3 0 0 0 0 1 0 0 \n",
2023
+ "4 1 0 0 0 0 1 0 \n",
2024
+ ".. ... ... ... ... ... ... ... \n",
2025
+ "795 0 1 1 1 1 1 1 \n",
2026
+ "796 0 1 1 0 0 1 0 \n",
2027
+ "797 1 0 0 0 0 0 0 \n",
2028
+ "798 0 1 1 1 1 1 1 \n",
2029
+ "799 0 1 0 0 1 1 0 \n",
2030
+ "\n",
2031
+ " A7_Score A8_Score A9_Score A10_Score jaundice austim age \\\n",
2032
+ "0 0 1 1 1 0 0 18.605397 \n",
2033
+ "1 0 0 0 1 0 0 13.829369 \n",
2034
+ "2 0 0 1 1 0 0 14.679893 \n",
2035
+ "3 0 0 0 0 0 0 61.035288 \n",
2036
+ "4 0 0 1 1 0 1 14.256686 \n",
2037
+ ".. ... ... ... ... ... ... ... \n",
2038
+ "795 1 1 1 1 0 1 42.084907 \n",
2039
+ "796 0 0 1 1 0 0 17.669291 \n",
2040
+ "797 1 0 1 1 1 0 18.242557 \n",
2041
+ "798 0 1 1 1 0 1 19.241473 \n",
2042
+ "799 0 1 1 1 0 0 32.170098 \n",
2043
+ "\n",
2044
+ " ethnicity Class/ASD \n",
2045
+ "0 10 0 \n",
2046
+ "1 8 0 \n",
2047
+ "2 10 1 \n",
2048
+ "3 8 0 \n",
2049
+ "4 2 0 \n",
2050
+ ".. ... ... \n",
2051
+ "795 10 1 \n",
2052
+ "796 1 0 \n",
2053
+ "797 10 1 \n",
2054
+ "798 5 0 \n",
2055
+ "799 1 0 \n",
2056
+ "\n",
2057
+ "[800 rows x 16 columns]"
2058
+ ]
2059
+ },
2060
+ "execution_count": 18,
2061
+ "metadata": {},
2062
+ "output_type": "execute_result"
2063
+ }
2064
+ ],
2065
+ "source": [
2066
+ "data"
2067
+ ]
2068
+ },
2069
+ {
2070
+ "cell_type": "markdown",
2071
+ "metadata": {},
2072
+ "source": [
2073
+ "Test the model"
2074
+ ]
2075
+ },
2076
+ {
2077
+ "cell_type": "code",
2078
+ "execution_count": 19,
2079
+ "metadata": {},
2080
+ "outputs": [
2081
+ {
2082
+ "name": "stdout",
2083
+ "output_type": "stream",
2084
+ "text": [
2085
+ "[0]\n"
2086
+ ]
2087
+ }
2088
+ ],
2089
+ "source": [
2090
+ "input_data = np.array([1\t,0\t,0\t,0\t,0\t,0\t,0\t,1\t,0\t,1\t,1\t,1\t,0\t,18.242557\t,10])\n",
2091
+ "input_data_reshaped = input_data.reshape(1, -1)\n",
2092
+ "predication = model.predict(input_data_reshaped)\n",
2093
+ "print(predication)"
2094
+ ]
2095
+ },
2096
+ {
2097
+ "cell_type": "markdown",
2098
+ "metadata": {},
2099
+ "source": [
2100
+ "Save the model and the scaler\n"
2101
+ ]
2102
+ },
2103
+ {
2104
+ "cell_type": "code",
2105
+ "execution_count": 20,
2106
+ "metadata": {},
2107
+ "outputs": [
2108
+ {
2109
+ "data": {
2110
+ "text/plain": [
2111
+ "['scaler.pkl']"
2112
+ ]
2113
+ },
2114
+ "execution_count": 20,
2115
+ "metadata": {},
2116
+ "output_type": "execute_result"
2117
+ }
2118
+ ],
2119
+ "source": [
2120
+ "joblib.dump(model, 'autism_model.pkl')\n",
2121
+ "joblib.dump(scaler, 'scaler.pkl')"
2122
+ ]
2123
+ },
2124
+ {
2125
+ "cell_type": "code",
2126
+ "execution_count": 21,
2127
+ "metadata": {},
2128
+ "outputs": [],
2129
+ "source": [
2130
+ "import joblib\n",
2131
+ "import pandas as pd"
2132
+ ]
2133
+ },
2134
+ {
2135
+ "cell_type": "code",
2136
+ "execution_count": 22,
2137
+ "metadata": {},
2138
+ "outputs": [],
2139
+ "source": [
2140
+ "model = joblib.load(\"autism_model.pkl\")"
2141
+ ]
2142
+ },
2143
+ {
2144
+ "cell_type": "code",
2145
+ "execution_count": 27,
2146
+ "metadata": {},
2147
+ "outputs": [],
2148
+ "source": [
2149
+ "sample_input ={\n",
2150
+ " \"A1_Score\": 1,\n",
2151
+ " \"A2_Score\": 0,\n",
2152
+ " \"A3_Score\": 0,\n",
2153
+ " \"A4_Score\": 0,\n",
2154
+ " \"A5_Score\": 0,\n",
2155
+ " \"A6_Score\": 0,\n",
2156
+ " \"A7_Score\": 0,\n",
2157
+ " \"A8_Score\": 1,\n",
2158
+ " \"A9_Score\": 0,\n",
2159
+ " \"A10_Score\": 1,\n",
2160
+ " \"jaundice\": 1,\n",
2161
+ " \"autism\": 1,\n",
2162
+ " \"age\": 18.242557,\n",
2163
+ " \"gender\": 1,\n",
2164
+ " \"ethnicity\":1\n",
2165
+ "}"
2166
+ ]
2167
+ },
2168
+ {
2169
+ "cell_type": "code",
2170
+ "execution_count": 29,
2171
+ "metadata": {},
2172
+ "outputs": [
2173
+ {
2174
+ "name": "stdout",
2175
+ "output_type": "stream",
2176
+ "text": [
2177
+ "[[ 1. 0. 0. 0. 0. 0. 0.\n",
2178
+ " 1. 0. 1. 1. 1. 18.242557 1.\n",
2179
+ " 1. ]]\n"
2180
+ ]
2181
+ }
2182
+ ],
2183
+ "source": [
2184
+ "import numpy as np\n",
2185
+ "\n",
2186
+ "# Given dictionary\n",
2187
+ "data = {\n",
2188
+ " 'A1_Score': 1, 'A2_Score': 0, 'A3_Score': 0, 'A4_Score': 0, 'A5_Score': 0, \n",
2189
+ " 'A6_Score': 0, 'A7_Score': 0, 'A8_Score': 1, 'A9_Score': 0, 'A10_Score': 1, \n",
2190
+ " 'jaundice': 1, 'autism': 1, 'age': 18.242557, \"gender\": 1,\n",
2191
+ " \"ethnicity\":1\n",
2192
+ "}\n",
2193
+ "\n",
2194
+ "# Convert the dictionary values to a list\n",
2195
+ "data_list = list(data.values())\n",
2196
+ "\n",
2197
+ "# Convert the list to a 2D numpy array\n",
2198
+ "data_array = np.array(data_list).reshape(1, -1)\n",
2199
+ "\n",
2200
+ "print(data_array)\n"
2201
+ ]
2202
+ },
2203
+ {
2204
+ "cell_type": "code",
2205
+ "execution_count": 34,
2206
+ "metadata": {},
2207
+ "outputs": [
2208
+ {
2209
+ "data": {
2210
+ "text/plain": [
2211
+ "1"
2212
+ ]
2213
+ },
2214
+ "execution_count": 34,
2215
+ "metadata": {},
2216
+ "output_type": "execute_result"
2217
+ }
2218
+ ],
2219
+ "source": [
2220
+ "model.predict(data_array)[0]"
2221
+ ]
2222
+ }
2223
+ ],
2224
+ "metadata": {
2225
+ "kernelspec": {
2226
+ "display_name": "base",
2227
+ "language": "python",
2228
+ "name": "python3"
2229
+ },
2230
+ "language_info": {
2231
+ "codemirror_mode": {
2232
+ "name": "ipython",
2233
+ "version": 3
2234
+ },
2235
+ "file_extension": ".py",
2236
+ "mimetype": "text/x-python",
2237
+ "name": "python",
2238
+ "nbconvert_exporter": "python",
2239
+ "pygments_lexer": "ipython3",
2240
+ "version": "3.12.4"
2241
+ }
2242
+ },
2243
+ "nbformat": 4,
2244
+ "nbformat_minor": 2
2245
+ }
autism_model.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:9d8ef8aa23c654f82cb2604e6cb6ba12258d903d3b3fedd2f569bcd5a3890eb2
3
+ size 991
data.csv ADDED
@@ -0,0 +1,801 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ID,gender,A1_Score,A2_Score,A3_Score,A4_Score,A5_Score,A6_Score,A7_Score,A8_Score,A9_Score,A10_Score,jaundice,austim,age,ethnicity,contry_of_res,used_app_before,result,relation,age_desc,Class/ASD
2
+ 1,f,1,0,1,1,1,1,0,1,1,1,no,no,18.60539681,White-European,United States,no,7.819715187,Self,18 and more,0
3
+ 2,f,0,0,0,0,0,0,0,0,0,1,no,no,13.82936938,South Asian,Australia,no,10.54429644,?,18 and more,0
4
+ 3,f,1,1,1,1,1,1,0,0,1,1,no,no,14.67989264,White-European,United Kingdom,no,13.1675062,Self,18 and more,1
5
+ 4,f,0,0,0,1,0,0,0,0,0,0,no,no,61.03528807,South Asian,New Zealand,no,1.530097682,?,18 and more,0
6
+ 5,m,0,0,0,0,1,0,0,0,1,1,no,yes,14.25668605,Black,Italy,no,7.949722607,Self,18 and more,0
7
+ 6,m,1,0,0,0,0,0,0,1,0,0,no,no,15.57819071,Asian,Nicaragua,no,7.445003289,?,18 and more,0
8
+ 7,f,1,1,1,1,1,1,0,1,0,0,no,no,21.36698098,White-European,Canada,no,12.59858317,Self,18 and more,0
9
+ 8,m,0,0,0,0,0,0,0,0,0,0,yes,no,28.93006774,Middle Eastern ,United Arab Emirates,no,3.525720056,?,18 and more,0
10
+ 9,f,1,1,1,1,1,1,1,1,1,0,yes,no,20.30594341,White-European,United Kingdom,no,11.90246137,Self,18 and more,1
11
+ 10,f,0,0,0,0,0,0,1,1,0,1,yes,no,17.96459873,?,United States,no,8.633346444,Self,18 and more,1
12
+ 11,m,1,0,0,1,0,0,0,1,0,0,no,no,15.40690273,others,Netherlands,no,1.015305534,?,18 and more,0
13
+ 12,f,1,0,0,0,1,0,1,1,0,1,no,no,22.87041047,Middle Eastern ,Australia,no,5.439973417,?,18 and more,0
14
+ 13,f,1,0,1,1,1,1,1,1,1,1,yes,yes,29.11206645,White-European,United States,no,12.81112483,Self,18 and more,1
15
+ 14,m,1,0,1,1,0,0,0,1,0,0,yes,no,45.7861637,?,New Zealand,no,6.057170377,Self,18 and more,0
16
+ 15,f,1,0,0,1,1,0,0,0,1,0,no,no,28.71312905,?,Sri Lanka,no,6.347515321,Self,18 and more,0
17
+ 16,f,1,1,0,0,1,0,0,0,0,0,yes,no,36.08435983,Latino,Australia,no,2.983511434,Self,18 and more,1
18
+ 17,f,1,1,0,0,0,0,0,0,1,0,no,no,52.20892387,South Asian,United Arab Emirates,no,6.858826004,Self,18 and more,0
19
+ 18,m,0,0,0,0,0,0,0,0,0,0,no,no,13.97301145,Middle Eastern ,United Arab Emirates,no,1.573960341,?,18 and more,0
20
+ 19,f,0,0,0,0,0,0,0,0,0,1,no,no,15.55955208,?,United Arab Emirates,no,4.426813229,Self,18 and more,0
21
+ 20,m,1,0,0,0,0,0,0,0,0,0,no,no,13.99395149,Asian,Canada,yes,7.822974767,Health care professional,18 and more,0
22
+ 21,m,0,0,0,0,0,0,0,0,0,0,no,no,24.34811834,Middle Eastern ,India,no,1.418385496,Self,18 and more,0
23
+ 22,f,1,1,1,1,1,1,1,1,1,1,yes,yes,38.5945887,White-European,New Zealand,no,13.24903914,Self,18 and more,1
24
+ 23,f,0,0,0,0,0,0,1,1,0,0,no,no,37.54394119,Asian,United States,no,4.791004268,Self,18 and more,0
25
+ 24,m,1,0,0,0,1,0,0,0,1,1,yes,no,15.77964696,South Asian,United Kingdom,no,6.602036821,Self,18 and more,0
26
+ 25,f,1,0,0,1,0,0,1,0,0,0,no,no,37.91975494,?,Nicaragua,no,5.553657029,Parent,18 and more,1
27
+ 26,m,1,0,0,0,1,0,0,1,1,1,no,no,31.79042116,?,India,no,8.843999341,Self,18 and more,0
28
+ 27,f,1,0,0,1,1,0,1,1,0,1,no,yes,54.51081856,White-European,New Zealand,no,9.516903607,Self,18 and more,0
29
+ 28,m,1,0,0,1,1,0,0,1,1,1,no,no,24.2640054,Middle Eastern ,Netherlands,no,2.899589804,Self,18 and more,0
30
+ 29,m,1,1,1,1,1,0,0,1,1,1,no,no,44.85675975,White-European,United Kingdom,no,5.388901885,Self,18 and more,1
31
+ 30,m,0,1,0,0,0,0,0,1,0,0,no,no,13.71660497,Black,Netherlands,no,4.950485754,Self,18 and more,0
32
+ 31,m,1,0,1,1,1,0,1,1,1,1,yes,no,23.01064721,White-European,United States,no,12.66041654,Self,18 and more,1
33
+ 32,f,1,0,0,1,0,0,1,1,0,1,no,no,34.48599757,Latino,New Zealand,no,6.624202657,Health care professional,18 and more,0
34
+ 33,m,1,0,0,0,1,0,0,1,0,0,no,no,24.62929977,White-European,Armenia,no,0.657363734,Self,18 and more,0
35
+ 34,f,0,0,0,0,1,0,1,1,0,0,no,no,45.98472454,Asian,Sierra Leone,no,3.413026832,Self,18 and more,0
36
+ 35,m,1,0,0,0,1,0,0,1,0,1,no,no,23.8768401,Latino,India,yes,10.08048811,?,18 and more,0
37
+ 36,m,1,0,0,1,0,1,1,1,1,1,no,no,54.53720884,White-European,Argentina,no,5.644474048,Self,18 and more,0
38
+ 37,m,1,0,1,1,1,0,0,0,0,0,yes,no,13.53526348,Latino,Azerbaijan,no,4.631590733,Self,18 and more,0
39
+ 38,m,1,0,0,0,0,0,0,1,0,0,no,no,25.55286793,?,Iceland,no,1.540616969,?,18 and more,0
40
+ 39,f,0,0,1,1,1,1,1,1,1,1,no,no,55.07023813,Middle Eastern ,Egypt,no,13.25243282,Self,18 and more,1
41
+ 40,m,1,0,0,0,1,0,0,1,0,0,no,no,44.8700017,Asian,United Arab Emirates,no,7.073171612,Self,18 and more,0
42
+ 41,f,1,1,0,0,1,0,1,1,1,1,no,no,14.24974298,South Asian,Serbia,no,12.84156099,Self,18 and more,0
43
+ 42,m,1,0,1,1,1,0,1,1,0,1,yes,yes,39.43876274,White-European,United Arab Emirates,no,10.40867918,Self,18 and more,1
44
+ 43,m,0,0,0,0,0,0,0,1,0,0,no,no,37.11566426,?,Sri Lanka,no,2.25190921,Relative,18 and more,1
45
+ 44,f,0,0,0,0,0,0,0,0,0,0,no,no,16.09705879,?,United Arab Emirates,no,3.855358769,Self,18 and more,0
46
+ 45,f,1,1,1,0,0,0,0,1,1,1,no,no,65.6951177,?,United Kingdom,no,7.871215678,Self,18 and more,0
47
+ 46,f,1,0,0,1,0,0,0,0,1,1,no,no,17.9297571,Middle Eastern ,United States,no,9.784631775,Self,18 and more,0
48
+ 47,f,1,0,0,0,0,0,0,1,1,1,yes,no,38.0985636,Middle Eastern ,Afghanistan,yes,4.975028787,Health care professional,18 and more,0
49
+ 48,f,1,1,1,1,1,1,1,1,1,1,no,yes,31.26745092,White-European,United States,no,10.07775141,Self,18 and more,1
50
+ 49,m,1,0,0,0,0,0,0,1,0,0,yes,yes,37.37522679,White-European,Costa Rica,no,4.691590642,Self,18 and more,0
51
+ 50,m,0,0,0,0,0,0,0,1,0,0,no,no,27.47619568,Asian,United Arab Emirates,no,6.396593911,Self,18 and more,0
52
+ 51,f,1,0,0,1,1,0,0,1,0,1,yes,no,24.04423243,White-European,United States,no,10.340678,Self,18 and more,1
53
+ 52,f,1,1,1,1,1,1,0,1,1,1,no,yes,15.92003387,White-European,Afghanistan,yes,10.54503923,Parent,18 and more,1
54
+ 53,f,1,1,0,1,1,1,1,1,1,1,yes,no,14.39803871,White-European,United States,no,12.88664935,Self,18 and more,1
55
+ 54,m,1,1,0,0,0,0,0,1,0,0,no,no,17.63356169,Latino,New Zealand,no,5.709313009,Self,18 and more,0
56
+ 55,f,0,0,0,1,0,0,0,1,0,0,no,no,22.14783581,Black,Afghanistan,no,6.534879168,Self,18 and more,0
57
+ 56,m,1,0,0,0,0,0,0,1,0,0,no,no,41.71234687,?,United Arab Emirates,no,8.709428864,?,18 and more,0
58
+ 57,f,1,0,0,0,0,0,0,1,0,1,no,no,48.56647483,Middle Eastern ,Jordan,no,8.335489926,Parent,18 and more,0
59
+ 58,m,0,0,0,1,1,0,0,1,0,1,no,no,51.80196369,?,India,no,11.28614543,Self,18 and more,0
60
+ 59,m,0,0,0,0,0,0,0,1,0,1,no,no,30.64667127,?,New Zealand,no,3.705601706,Self,18 and more,0
61
+ 60,m,1,1,1,0,0,1,0,1,0,0,no,no,33.05861987,?,Australia,no,0.286266851,Self,18 and more,0
62
+ 61,f,0,0,0,0,1,0,0,0,0,0,no,no,20.53650583,Middle Eastern ,Angola,no,6.594542137,Self,18 and more,0
63
+ 62,f,1,1,1,1,1,0,0,1,1,1,yes,no,27.24063427,Middle Eastern ,Pakistan,no,7.825169567,Self,18 and more,0
64
+ 63,m,0,0,0,0,0,0,0,1,0,0,yes,no,26.30248764,?,Australia,no,9.646207259,Self,18 and more,0
65
+ 64,f,1,0,0,0,1,0,1,1,0,0,no,no,32.42403082,White-European,Brazil,no,7.209593788,?,18 and more,0
66
+ 65,f,1,0,1,1,1,0,1,1,1,1,no,yes,52.02688326,Middle Eastern ,Ireland,no,12.56780339,Health care professional,18 and more,0
67
+ 66,f,1,0,1,1,1,1,1,1,1,0,no,no,44.09821754,White-European,United States,no,8.153973354,Self,18 and more,0
68
+ 67,m,1,0,1,1,1,1,0,1,1,1,no,no,21.10272977,White-European,United Kingdom,no,12.60656763,Self,18 and more,1
69
+ 68,m,1,0,0,0,0,0,0,1,0,0,no,no,17.51408417,Middle Eastern ,Egypt,no,7.232900229,Self,18 and more,0
70
+ 69,f,0,0,0,0,1,0,0,1,0,1,no,no,15.59883742,South Asian,Kazakhstan,no,9.811655578,Self,18 and more,0
71
+ 70,m,0,0,0,0,0,0,0,1,0,0,no,no,19.53559466,White-European,Sri Lanka,no,4.070286041,Self,18 and more,0
72
+ 71,f,1,0,0,0,1,1,1,1,0,0,no,no,17.42176325,Asian,United Kingdom,no,4.669019897,Self,18 and more,0
73
+ 72,f,0,1,0,0,0,0,0,0,0,0,yes,no,17.38545741,Latino,New Zealand,no,7.448004589,Self,18 and more,0
74
+ 73,m,0,0,0,0,0,1,0,0,0,1,no,no,9.560504591,Latino,United States,no,7.840968847,Self,18 and more,0
75
+ 74,f,0,0,0,0,1,0,0,1,0,1,no,no,25.95016033,White-European,Netherlands,no,9.766300148,Self,18 and more,0
76
+ 75,m,1,0,0,0,1,0,1,0,0,0,no,no,35.83746454,?,India,no,9.54909141,Self,18 and more,0
77
+ 76,m,1,0,1,0,1,0,0,1,0,0,no,yes,11.54993958,White-European,United States,no,8.933598665,Self,18 and more,0
78
+ 77,m,1,1,1,1,1,1,0,1,0,1,no,no,38.67351458,White-European,Viet Nam,no,9.76324347,Self,18 and more,0
79
+ 78,f,0,1,0,0,0,0,1,0,0,0,yes,no,29.6603158,Black,Ethiopia,no,6.214286274,Parent,18 and more,1
80
+ 79,f,1,0,0,1,0,0,0,0,1,0,no,no,42.2214725,Turkish,New Zealand,no,3.732497665,Self,18 and more,0
81
+ 80,m,0,0,0,0,0,0,0,0,0,0,yes,no,30.57399179,Latino,Austria,no,-2.594654288,?,18 and more,0
82
+ 81,f,1,1,1,1,1,1,0,1,1,1,yes,yes,27.58499933,Black,United States,no,10.03619864,Self,18 and more,1
83
+ 82,f,1,0,1,1,1,1,1,1,1,1,no,no,12.94714991,White-European,United States,no,13.23949205,Self,18 and more,0
84
+ 83,m,0,0,0,0,0,0,0,0,0,0,no,no,30.07064518,Others,India,no,3.614902134,Others,18 and more,0
85
+ 84,f,0,1,1,0,0,0,0,1,1,1,no,yes,21.60769114,White-European,Finland,no,9.750764191,Self,18 and more,0
86
+ 85,m,1,1,0,0,0,0,0,1,0,0,no,no,18.65259136,Latino,New Zealand,no,12.76442307,?,18 and more,0
87
+ 86,f,1,1,0,1,0,0,1,1,0,1,no,no,20.22910815,Asian,New Zealand,no,10.05862243,Self,18 and more,0
88
+ 87,m,1,0,0,1,0,0,0,1,0,0,no,no,14.69486744,Asian,India,no,5.224989407,Self,18 and more,0
89
+ 88,m,0,0,0,0,0,0,0,0,0,0,no,no,70.80160415,?,United Arab Emirates,no,1.99710083,Self,18 and more,0
90
+ 89,m,1,1,1,1,1,0,1,1,1,1,no,no,19.46573847,South Asian,United States,no,4.793345886,Self,18 and more,0
91
+ 90,f,0,0,1,0,0,0,1,0,0,0,no,no,29.98828071,Middle Eastern ,United States,no,4.417103419,Self,18 and more,0
92
+ 91,f,0,0,0,0,0,0,0,1,0,0,no,no,21.55665806,Middle Eastern ,Italy,no,5.013694417,Parent,18 and more,0
93
+ 92,f,1,0,0,0,0,0,0,1,0,1,no,no,28.76435032,Others,France,no,4.606360182,Self,18 and more,0
94
+ 93,f,1,1,0,1,1,1,1,1,0,1,no,no,14.4545617,White-European,New Zealand,no,4.695521319,Self,18 and more,0
95
+ 94,f,0,0,1,0,0,0,0,0,0,0,no,no,24.27300103,?,Australia,no,9.937854231,Self,18 and more,0
96
+ 95,f,1,0,0,0,0,0,0,0,0,0,no,no,24.55505931,Asian,United Arab Emirates,no,3.878289078,Self,18 and more,0
97
+ 96,m,1,0,1,1,1,0,0,1,0,1,no,no,28.24751537,?,Australia,no,6.581864991,Self,18 and more,1
98
+ 97,f,0,0,0,0,0,0,0,1,0,1,no,no,17.39781861,Asian,Sri Lanka,no,5.071976366,Self,18 and more,0
99
+ 98,f,1,1,1,1,1,1,1,1,1,1,no,yes,46.14982009,White-European,United States,no,12.69293695,Self,18 and more,1
100
+ 99,m,0,0,0,0,0,0,0,0,0,0,no,no,24.4713742,?,United Kingdom,no,-0.650589998,Self,18 and more,0
101
+ 100,m,1,0,0,0,0,0,0,1,0,1,no,no,32.23937347,Asian,United Arab Emirates,no,5.06611889,Self,18 and more,0
102
+ 101,f,1,1,1,1,1,1,1,1,1,1,yes,no,69.09837764,Latino,Jordan,no,12.25208458,Self,18 and more,0
103
+ 102,f,1,0,0,0,0,0,0,0,0,0,no,no,45.37472227,Asian,Netherlands,no,6.115176125,Parent,18 and more,0
104
+ 103,m,0,0,0,0,0,0,0,0,0,0,no,no,47.84566809,Black,India,no,7.566585884,Self,18 and more,0
105
+ 104,f,0,0,1,0,0,0,1,0,0,1,yes,no,28.56308891,Asian,Afghanistan,no,3.269826126,Self,18 and more,0
106
+ 105,f,0,0,0,0,0,0,0,0,0,0,no,no,13.09682249,Middle Eastern ,India,no,6.284792344,Self,18 and more,0
107
+ 106,m,0,0,0,0,0,0,0,1,0,0,no,no,19.80506544,?,United States,no,10.83261719,Self,18 and more,0
108
+ 107,m,0,0,0,0,0,0,0,1,0,0,yes,no,27.61175669,?,United Arab Emirates,no,5.095273997,Self,18 and more,0
109
+ 108,m,0,1,0,0,1,0,0,0,0,1,no,no,16.7146808,Asian,Afghanistan,no,7.841211971,Parent,18 and more,0
110
+ 109,m,0,0,0,1,0,0,0,1,0,0,no,no,26.41488838,Middle Eastern ,Malaysia,no,4.941242446,Self,18 and more,0
111
+ 110,f,0,0,0,0,0,0,0,0,0,0,yes,no,29.33349476,?,Afghanistan,no,4.998445064,Self,18 and more,0
112
+ 111,f,1,0,0,0,0,0,0,0,0,1,yes,no,21.32706907,South Asian,United States,no,10.94097596,Others,18 and more,0
113
+ 112,f,0,1,0,0,0,0,1,1,1,0,no,no,67.55850162,South Asian,India,no,5.578162198,Self,18 and more,0
114
+ 113,m,1,0,0,0,0,0,0,1,0,0,no,no,18.50446693,?,Sri Lanka,no,2.620210131,?,18 and more,0
115
+ 114,f,1,1,0,1,0,1,1,1,0,1,no,no,19.53928574,Hispanic,France,yes,8.07013112,?,18 and more,1
116
+ 115,m,0,0,0,0,0,0,0,0,0,0,no,no,31.43579833,Asian,New Zealand,no,5.344506477,Parent,18 and more,0
117
+ 116,m,1,0,0,1,1,1,1,1,0,0,yes,no,20.08757477,?,Austria,no,3.430217985,Self,18 and more,0
118
+ 117,f,1,0,0,1,0,0,0,1,0,0,no,no,69.05226045,Black,Jordan,no,7.296902543,Others,18 and more,0
119
+ 118,m,0,0,0,0,0,0,0,0,0,0,no,no,23.05540341,Middle Eastern ,New Zealand,no,4.449269716,Self,18 and more,0
120
+ 119,m,0,1,1,1,1,1,1,1,1,1,yes,no,62.01077975,White-European,United States,no,10.70238151,Self,18 and more,1
121
+ 120,m,0,0,0,0,0,0,0,1,0,1,no,no,14.59720978,Black,United Kingdom,no,-1.212396333,Self,18 and more,0
122
+ 121,m,1,0,0,0,0,0,0,0,0,0,no,no,47.87638561,White-European,United Arab Emirates,no,6.300921052,Self,18 and more,0
123
+ 122,f,1,1,1,1,1,1,1,1,1,1,no,yes,42.21516864,White-European,United Kingdom,no,13.32706355,Self,18 and more,1
124
+ 123,m,0,1,0,1,1,0,1,0,0,0,no,no,22.62568164,?,Jordan,no,4.396275519,Relative,18 and more,0
125
+ 124,f,1,0,1,1,1,1,1,1,1,1,no,no,14.92302777,White-European,Netherlands,no,12.70479673,Self,18 and more,1
126
+ 125,f,1,0,1,1,1,1,1,1,1,1,yes,no,53.25270496,White-European,United States,no,12.48470147,Self,18 and more,1
127
+ 126,m,0,0,0,0,0,0,0,1,0,0,no,no,25.55856781,Middle Eastern ,United Kingdom,no,3.224013563,?,18 and more,0
128
+ 127,f,1,1,1,1,1,0,1,1,1,1,yes,yes,15.47212097,White-European,United States,no,12.62577922,Self,18 and more,1
129
+ 128,m,0,0,0,1,1,1,1,1,0,1,no,no,32.86252139,?,United States,no,11.37187551,Self,18 and more,1
130
+ 129,f,1,1,1,1,1,1,0,1,1,1,yes,yes,32.4945138,Latino,New Zealand,yes,9.260484285,Self,18 and more,0
131
+ 130,f,0,0,0,0,0,0,0,1,0,0,no,no,26.30495213,Middle Eastern ,Viet Nam,no,4.783945805,Self,18 and more,0
132
+ 131,f,1,0,1,1,1,1,1,1,1,1,no,no,55.87718249,White-European,United Kingdom,no,11.46899443,Parent,18 and more,1
133
+ 132,m,1,1,1,1,0,0,0,1,1,1,no,no,28.16768892,Middle Eastern ,New Zealand,no,5.798850311,Self,18 and more,0
134
+ 133,m,1,0,1,1,1,0,0,1,1,1,no,no,18.74165104,Latino,France,yes,8.509552181,Parent,18 and more,1
135
+ 134,f,1,1,1,1,1,1,1,1,1,1,no,no,18.24228234,White-European,Jordan,no,13.25738119,Self,18 and more,1
136
+ 135,f,1,1,1,1,1,1,0,1,1,1,yes,no,45.17808556,Others,United States,no,12.93862184,Self,18 and more,0
137
+ 136,m,1,0,0,1,0,0,0,1,0,1,no,no,26.72393465,White-European,Australia,no,4.385270593,Self,18 and more,0
138
+ 137,m,1,1,1,1,1,0,0,1,1,1,yes,no,71.08419062,Asian,Australia,no,9.631162929,Self,18 and more,1
139
+ 138,f,0,0,0,1,0,0,0,1,0,0,no,no,25.77650282,?,Canada,no,9.159208904,Self,18 and more,0
140
+ 139,m,1,1,0,1,1,1,1,1,1,0,no,yes,18.00560631,White-European,Canada,no,6.703483003,Parent,18 and more,0
141
+ 140,m,0,0,1,1,0,0,1,1,0,0,no,no,22.12052239,?,Jordan,no,5.224789303,Self,18 and more,0
142
+ 141,m,0,1,1,1,1,0,0,1,1,1,no,no,21.23165613,White-European,United States,no,12.62889495,Self,18 and more,1
143
+ 142,f,1,0,1,1,1,0,1,1,1,1,no,no,47.98800877,White-European,United Kingdom,no,9.640370415,Self,18 and more,1
144
+ 143,f,0,1,1,1,0,0,0,1,0,1,yes,no,24.65502345,White-European,United Kingdom,yes,2.820220928,Self,18 and more,0
145
+ 144,f,1,1,0,1,1,0,0,1,1,1,no,no,19.5181971,Asian,United States,no,11.17609738,Self,18 and more,0
146
+ 145,m,1,0,0,0,0,0,0,0,0,1,no,no,29.74431679,Asian,United States,no,4.750577945,Relative,18 and more,0
147
+ 146,m,0,0,0,0,0,0,0,0,0,0,no,no,39.70332795,Middle Eastern ,Japan,no,4.908919455,Self,18 and more,0
148
+ 147,f,1,0,0,0,0,0,0,1,0,0,no,no,29.31918969,White-European,India,no,3.903968223,Self,18 and more,0
149
+ 148,f,1,1,0,1,1,0,0,1,0,0,yes,no,35.72545637,Hispanic,New Zealand,no,6.045432109,Self,18 and more,0
150
+ 149,m,0,1,0,1,0,0,0,0,0,0,no,no,27.81662774,Black,United Kingdom,no,1.308156877,Self,18 and more,0
151
+ 150,m,1,0,1,1,1,0,0,1,1,1,yes,no,23.45687224,?,India,no,4.528126639,Self,18 and more,0
152
+ 151,f,0,0,0,1,1,0,0,1,0,0,yes,yes,24.97098115,Black,India,no,6.321999645,Self,18 and more,0
153
+ 152,f,1,1,1,0,0,0,1,1,0,1,no,no,17.03338276,White-European,New Zealand,no,7.175613886,Self,18 and more,0
154
+ 153,m,0,0,0,1,0,0,0,0,1,0,no,no,18.56656926,Others,New Zealand,no,10.93789702,Self,18 and more,0
155
+ 154,m,1,1,1,1,1,1,1,1,1,1,no,yes,22.57895951,Asian,Austria,no,12.26593849,Self,18 and more,1
156
+ 155,m,0,0,0,0,0,0,0,0,0,0,yes,no,20.99807204,Middle Eastern ,Jordan,no,7.260661648,?,18 and more,0
157
+ 156,f,1,0,0,1,1,1,0,1,1,1,no,yes,20.85087407,Black,New Zealand,no,8.261758002,Parent,18 and more,1
158
+ 157,m,1,1,1,1,1,0,0,1,1,1,no,no,33.15345606,Black,Netherlands,no,9.436401795,Self,18 and more,0
159
+ 158,m,0,0,0,0,0,0,0,1,0,0,no,no,16.91617977,Asian,United Arab Emirates,no,4.525843437,Self,18 and more,0
160
+ 159,f,1,1,1,1,1,1,1,1,1,1,no,yes,17.49596329,White-European,United States,no,8.904978493,Self,18 and more,1
161
+ 160,m,0,0,0,0,0,0,0,0,1,0,no,no,17.56342082,Black,United Arab Emirates,no,7.160638033,Self,18 and more,0
162
+ 161,m,0,0,0,1,1,0,0,1,1,1,yes,no,37.38204891,Middle Eastern ,India,no,7.941886935,Self,18 and more,1
163
+ 162,m,1,1,1,1,0,0,0,1,1,1,yes,no,17.86860128,White-European,Spain,no,11.11568277,Self,18 and more,0
164
+ 163,m,0,0,0,1,0,1,0,1,1,0,no,no,30.68204661,Asian,New Zealand,no,5.615052675,Self,18 and more,0
165
+ 164,f,0,0,1,1,1,1,0,1,1,1,yes,no,30.5726803,Asian,New Zealand,no,9.818735624,Self,18 and more,0
166
+ 165,m,1,0,1,0,0,0,0,1,0,1,no,no,30.65806538,?,Afghanistan,no,4.820591224,Self,18 and more,0
167
+ 166,f,0,0,0,0,1,0,0,1,1,1,yes,no,24.78260151,Asian,India,no,4.522125675,Parent,18 and more,0
168
+ 167,f,1,0,0,0,1,1,0,1,0,1,yes,no,20.3267982,Middle Eastern ,United States,no,11.88115013,Self,18 and more,0
169
+ 168,f,1,0,0,0,1,0,0,1,0,0,no,no,19.0425534,Asian,United States,yes,7.378649836,Self,18 and more,0
170
+ 169,f,1,1,1,1,1,0,1,1,1,1,no,no,35.05333688,?,United Kingdom,yes,12.22051412,Self,18 and more,0
171
+ 170,m,0,0,0,0,0,0,0,0,0,0,no,no,31.18446071,Asian,Viet Nam,no,4.614599813,?,18 and more,0
172
+ 171,f,0,0,0,0,0,0,0,1,0,0,no,no,22.27304531,?,United Arab Emirates,yes,5.103677971,Self,18 and more,0
173
+ 172,f,1,1,1,1,0,0,1,1,1,1,no,no,12.3573003,White-European,United States,no,9.628453432,Self,18 and more,1
174
+ 173,f,1,1,1,1,1,1,1,1,1,1,no,yes,55.32273412,White-European,United States,no,13.27453963,Self,18 and more,1
175
+ 174,f,1,1,1,1,0,0,0,1,0,1,no,no,64.07729888,Pasifika,India,no,7.308089374,Self,18 and more,0
176
+ 175,m,0,0,0,0,1,0,1,0,1,1,no,no,16.99434028,Middle Eastern ,Iceland,no,5.325614476,Self,18 and more,0
177
+ 176,m,0,1,0,0,0,0,0,1,0,0,no,no,27.97710674,White-European,India,no,8.390241629,Self,18 and more,1
178
+ 177,m,0,0,0,0,0,0,0,1,0,0,no,no,22.38919405,South Asian,New Zealand,no,5.570278988,Relative,18 and more,0
179
+ 178,m,0,0,0,0,1,0,0,1,0,1,yes,no,30.63901324,Latino,Jordan,no,2.11659871,Relative,18 and more,0
180
+ 179,f,0,0,1,0,0,0,0,1,0,1,no,no,20.29018852,?,Australia,no,8.02232221,Parent,18 and more,0
181
+ 180,m,1,1,0,1,0,0,0,1,0,0,no,no,24.87843843,Asian,Jordan,no,7.318053842,Self,18 and more,0
182
+ 181,f,1,1,1,1,1,1,1,1,1,1,yes,no,53.31213707,White-European,Australia,no,8.553977333,Self,18 and more,1
183
+ 182,m,1,1,1,1,1,1,1,1,1,1,no,no,38.62482504,Pasifika,United Kingdom,no,10.19382235,Self,18 and more,1
184
+ 183,m,1,0,0,0,1,0,0,1,0,0,yes,no,12.24753182,Middle Eastern ,United States,no,2.375430861,Self,18 and more,0
185
+ 184,m,0,0,0,0,0,0,0,1,0,0,no,no,24.17754462,Asian,India,no,3.744542993,Self,18 and more,0
186
+ 185,m,1,0,0,1,1,1,0,1,1,1,yes,no,59.97435003,Asian,Philippines,no,11.37321626,Self,18 and more,0
187
+ 186,m,1,0,1,1,1,0,0,1,0,0,yes,no,18.53436695,White-European,Jordan,no,6.460316172,Self,18 and more,1
188
+ 187,m,0,0,0,0,0,0,0,1,0,0,no,no,16.53744586,?,United Arab Emirates,no,4.869798393,Others,18 and more,0
189
+ 188,f,1,0,0,0,0,0,0,1,0,0,no,no,22.47238061,Middle Eastern ,India,no,4.705954948,Self,18 and more,0
190
+ 189,m,1,0,0,0,1,0,0,0,0,0,no,no,54.1267139,Middle Eastern ,Iran,yes,6.385142744,?,18 and more,0
191
+ 190,f,1,1,0,0,1,0,1,1,0,0,no,no,26.72591344,Others,Afghanistan,no,8.453439218,Self,18 and more,0
192
+ 191,f,0,0,0,0,0,0,0,0,0,0,no,no,27.42240544,Middle Eastern ,Australia,no,1.199615665,?,18 and more,0
193
+ 192,m,0,0,0,0,0,0,0,0,0,0,no,no,16.49152984,South Asian,United Arab Emirates,no,4.566825697,?,18 and more,0
194
+ 193,f,1,0,0,0,0,0,0,0,0,0,no,no,17.84015282,Middle Eastern ,United Arab Emirates,no,10.58500677,Self,18 and more,0
195
+ 194,m,0,0,0,0,0,0,0,0,0,1,no,no,13.00076319,?,India,no,5.692644159,?,18 and more,0
196
+ 195,f,0,0,0,1,0,0,0,1,0,0,no,no,21.33664412,?,United States,no,8.376743889,Self,18 and more,0
197
+ 196,f,1,1,1,1,1,1,1,1,0,1,yes,no,48.50984312,White-European,Afghanistan,no,11.44296624,Self,18 and more,1
198
+ 197,f,0,0,0,0,0,0,0,0,0,0,no,no,24.5500137,Pasifika,United Arab Emirates,no,5.858026532,?,18 and more,0
199
+ 198,f,1,1,0,0,0,1,0,1,0,1,yes,no,17.84051133,Hispanic,Jordan,yes,9.190435762,Self,18 and more,0
200
+ 199,f,1,0,0,1,0,0,0,1,0,1,no,no,14.67194994,Black,France,no,6.301266432,?,18 and more,0
201
+ 200,f,1,0,1,0,0,0,0,0,0,0,no,no,26.13266488,Asian,Jordan,no,9.22865554,?,18 and more,0
202
+ 201,f,1,1,1,1,1,1,1,1,1,1,yes,yes,58.23716737,White-European,United States,no,13.38671243,Self,18 and more,1
203
+ 202,m,1,1,1,0,0,1,0,0,0,1,no,yes,27.77326719,Black,United States,no,4.504274878,Self,18 and more,0
204
+ 203,f,1,1,0,1,0,0,0,1,0,1,no,no,28.39174517,White-European,Brazil,no,4.913809832,Self,18 and more,0
205
+ 204,m,1,0,0,0,0,0,0,0,0,0,no,no,38.19603988,Hispanic,Czech Republic,no,4.998207109,Self,18 and more,0
206
+ 205,f,0,0,0,0,0,0,0,0,0,1,yes,no,19.48255661,?,India,no,10.71734934,Self,18 and more,0
207
+ 206,f,1,0,0,0,0,0,0,1,0,0,no,no,23.10647714,Middle Eastern ,India,no,7.468901184,Self,18 and more,0
208
+ 207,f,0,0,1,1,1,0,0,1,0,0,no,no,37.32451578,Asian,Jordan,no,7.223873083,Self,18 and more,0
209
+ 208,m,0,0,0,0,0,0,0,0,0,0,no,no,28.0402643,Middle Eastern ,Russia,no,8.75744368,Relative,18 and more,0
210
+ 209,f,1,0,1,0,1,0,0,1,1,1,no,yes,42.17293948,White-European,United Arab Emirates,no,6.891238655,Self,18 and more,1
211
+ 210,m,1,0,1,1,1,0,0,1,1,1,no,no,16.45927794,Middle Eastern ,India,no,10.83012283,Parent,18 and more,0
212
+ 211,f,0,0,0,0,0,0,0,0,0,0,no,no,21.20709159,?,United Arab Emirates,no,3.489950937,Self,18 and more,0
213
+ 212,f,0,0,0,0,0,0,0,0,0,0,no,no,14.25136597,?,Jordan,no,-0.396712075,Self,18 and more,0
214
+ 213,f,1,0,0,0,0,0,0,0,0,0,no,no,20.39654655,Asian,United States,no,6.044276636,Self,18 and more,0
215
+ 214,f,1,1,0,1,1,1,1,1,0,0,no,yes,59.64456984,?,Canada,no,7.536001517,Self,18 and more,0
216
+ 215,m,1,0,0,0,0,0,0,0,0,1,no,no,26.27653497,Middle Eastern ,Romania,no,1.273605895,Self,18 and more,0
217
+ 216,m,0,0,0,0,0,0,0,0,0,0,no,no,24.50929034,?,United Arab Emirates,no,6.46369743,Self,18 and more,0
218
+ 217,f,1,0,0,0,0,0,0,1,0,1,yes,no,50.13199013,Black,New Zealand,no,1.917302604,Self,18 and more,0
219
+ 218,m,1,0,0,0,1,0,0,1,0,0,no,no,26.44489182,Asian,United States,no,5.550252113,Self,18 and more,0
220
+ 219,f,0,0,1,0,0,0,1,0,1,1,no,yes,31.11362034,?,Jordan,no,11.89953146,Self,18 and more,1
221
+ 220,m,1,1,0,0,0,0,0,1,0,0,yes,no,29.12153036,Others,United Kingdom,no,3.205580177,Self,18 and more,0
222
+ 221,m,0,0,0,0,0,0,0,1,0,0,no,no,18.25537813,Asian,Czech Republic,no,0.581144869,Self,18 and more,0
223
+ 222,m,0,1,0,1,0,0,1,0,1,1,yes,yes,30.488441,White-European,Australia,no,5.477293457,Relative,18 and more,0
224
+ 223,f,1,0,0,1,1,0,1,1,1,0,no,yes,44.38044644,White-European,United States,no,12.14966009,Self,18 and more,0
225
+ 224,f,1,0,1,0,0,0,0,0,0,1,no,no,28.97897254,?,United Arab Emirates,no,6.819458362,Self,18 and more,0
226
+ 225,f,1,0,1,0,0,0,0,1,0,1,no,yes,52.9680159,White-European,Sri Lanka,no,5.107056609,Self,18 and more,0
227
+ 226,f,0,0,0,0,1,0,1,0,0,0,no,no,12.03765423,Asian,Canada,no,7.925329707,Self,18 and more,0
228
+ 227,m,0,0,0,0,0,0,0,1,0,0,no,no,29.37295411,South Asian,Mexico,no,5.033162205,?,18 and more,0
229
+ 228,m,1,0,0,1,1,0,0,1,0,0,no,no,49.34355056,?,United Kingdom,no,6.710785772,Self,18 and more,1
230
+ 229,f,0,0,1,1,1,0,0,1,0,1,no,no,23.99403586,Asian,United States,no,2.574220803,Self,18 and more,0
231
+ 230,f,1,0,0,0,0,0,0,0,0,1,no,no,23.04771671,Middle Eastern ,Australia,no,6.372565465,Self,18 and more,0
232
+ 231,m,0,0,0,0,0,0,0,1,0,0,no,no,39.31612047,Middle Eastern ,Romania,no,0.491429912,Relative,18 and more,0
233
+ 232,m,0,0,0,0,0,0,0,0,0,0,no,no,19.52180736,Latino,Austria,no,4.684938463,?,18 and more,0
234
+ 233,f,1,1,1,1,1,0,0,1,1,1,no,yes,10.0682642,Hispanic,New Zealand,no,6.852833012,Self,18 and more,0
235
+ 234,m,0,0,1,0,1,1,1,1,1,1,no,yes,42.56842778,Asian,United States,no,8.482545581,Self,18 and more,0
236
+ 235,f,0,0,0,0,0,0,0,0,0,0,no,no,28.40672129,Asian,United States,no,4.682341003,Relative,18 and more,0
237
+ 236,f,1,1,1,1,1,1,0,1,1,1,yes,no,25.17584032,White-European,United Kingdom,no,12.09403623,Self,18 and more,1
238
+ 237,f,1,1,0,1,1,0,0,1,1,1,no,no,44.95667763,White-European,United States,yes,9.813100169,Self,18 and more,0
239
+ 238,f,1,0,0,1,1,0,0,1,0,1,no,no,12.49217538,White-European,India,no,12.31885744,Self,18 and more,0
240
+ 239,m,1,0,1,1,0,0,1,1,1,1,no,no,72.40248841,White-European,United States,no,9.783101189,Self,18 and more,0
241
+ 240,f,0,0,0,1,0,0,0,1,0,0,no,no,29.98825247,?,Egypt,no,7.03454204,Relative,18 and more,0
242
+ 241,m,1,0,0,1,1,0,0,1,0,1,no,yes,48.53059445,Latino,Belgium,no,4.008542171,Relative,18 and more,1
243
+ 242,f,1,0,0,0,0,0,0,1,0,0,no,no,23.30157997,South Asian,United Arab Emirates,no,7.065567751,Relative,18 and more,0
244
+ 243,m,0,1,0,0,0,0,1,0,0,0,yes,no,44.21478178,Asian,United Arab Emirates,yes,9.270989784,?,18 and more,0
245
+ 244,m,0,0,0,0,0,0,0,0,0,0,no,no,17.97550298,Asian,Netherlands,no,0.334146871,?,18 and more,0
246
+ 245,f,0,1,1,1,1,0,0,1,1,0,no,no,41.54513901,White-European,United States,no,11.78183686,Self,18 and more,0
247
+ 246,f,1,0,0,1,1,0,0,1,0,0,no,no,26.26550774,Pasifika,India,no,7.021983864,Relative,18 and more,0
248
+ 247,m,1,0,0,0,0,0,0,1,0,0,no,no,27.79462444,Middle Eastern ,United Arab Emirates,no,9.196799364,Parent,18 and more,0
249
+ 248,m,0,0,0,0,0,0,0,1,0,0,no,no,29.54503981,White-European,Nicaragua,no,4.276302029,Self,18 and more,0
250
+ 249,m,0,0,0,0,0,0,0,0,0,0,no,no,23.22476695,?,India,no,0.067869621,?,18 and more,0
251
+ 250,m,0,0,0,1,0,0,1,1,1,1,no,no,38.69865911,Asian,India,no,5.405891366,Self,18 and more,0
252
+ 251,f,1,0,1,1,0,0,0,1,0,1,no,no,33.15865325,White-European,United Arab Emirates,no,10.36395382,Self,18 and more,0
253
+ 252,f,0,1,0,0,0,0,0,0,0,0,no,no,18.54376162,Middle Eastern ,United States,no,8.05311575,Self,18 and more,0
254
+ 253,m,0,1,0,0,0,0,0,1,0,1,yes,yes,14.08733098,?,Aruba,no,6.302734927,Self,18 and more,0
255
+ 254,f,0,0,0,0,0,0,0,1,0,0,no,no,18.76366889,South Asian,United Arab Emirates,no,6.468329718,?,18 and more,0
256
+ 255,m,1,0,1,0,0,0,0,1,1,0,no,yes,30.34815679,Asian,Sri Lanka,no,7.779740928,Self,18 and more,0
257
+ 256,m,1,0,0,0,0,0,1,1,0,0,no,no,30.05008465,Pasifika,India,no,5.005139466,Self,18 and more,0
258
+ 257,f,1,0,0,0,0,0,0,0,0,0,no,no,19.76478629,Middle Eastern ,Japan,no,6.564945194,Self,18 and more,1
259
+ 258,m,1,0,0,0,0,0,0,0,0,1,no,no,12.84895746,Middle Eastern ,Russia,no,5.301532,Others,18 and more,0
260
+ 259,f,1,0,0,0,0,0,0,1,0,0,no,no,21.43814876,Asian,New Zealand,no,4.953441874,Self,18 and more,0
261
+ 260,f,1,0,0,0,0,0,0,0,0,0,no,no,25.49186707,Others,Australia,no,4.212151999,Self,18 and more,0
262
+ 261,f,1,0,0,0,1,1,1,0,0,1,no,no,27.0273135,?,New Zealand,no,4.767911,Relative,18 and more,0
263
+ 262,m,1,1,0,0,1,0,0,1,0,1,no,yes,20.26061777,Black,United Kingdom,no,12.33754963,Self,18 and more,0
264
+ 263,m,0,1,1,1,0,0,0,0,0,0,no,no,49.78834545,White-European,Uruguay,no,3.043317021,Self,18 and more,0
265
+ 264,f,0,0,1,0,0,0,0,1,0,0,no,no,40.57666928,Turkish,Australia,yes,7.7594656,?,18 and more,0
266
+ 265,m,1,0,0,0,1,0,0,1,0,0,no,no,15.25926213,?,United States,no,6.448077267,Self,18 and more,0
267
+ 266,m,0,0,0,0,1,0,0,1,1,1,no,no,22.3768334,Middle Eastern ,Jordan,no,8.739162812,Self,18 and more,0
268
+ 267,m,1,0,0,0,1,1,0,1,0,0,no,no,18.59984127,Middle Eastern ,New Zealand,no,6.777451027,Self,18 and more,0
269
+ 268,m,1,0,0,0,1,0,0,1,0,0,no,no,35.45904379,Asian,United Arab Emirates,no,6.152681826,Self,18 and more,0
270
+ 269,f,0,0,0,0,0,0,0,0,0,0,no,no,70.45727239,South Asian,Canada,no,3.52634494,?,18 and more,0
271
+ 270,m,0,1,1,1,1,0,0,0,1,1,yes,no,64.7846482,Asian,Brazil,no,9.304044275,Parent,18 and more,1
272
+ 271,f,1,0,0,0,1,0,0,1,1,0,yes,no,19.41178926,Hispanic,United Kingdom,no,9.620736344,Self,18 and more,0
273
+ 272,m,0,0,0,0,0,0,1,1,0,0,no,no,29.29194323,?,United Arab Emirates,no,2.386216264,Self,18 and more,0
274
+ 273,f,0,0,0,0,1,0,0,0,0,0,no,no,25.1984157,?,Sri Lanka,no,7.290158394,Self,18 and more,0
275
+ 274,f,0,0,0,0,0,0,0,0,0,0,no,no,27.79857497,Others,India,no,0.63630177,Relative,18 and more,0
276
+ 275,f,1,0,1,1,1,0,1,0,1,1,yes,no,35.23840537,South Asian,United Kingdom,no,12.05446259,Self,18 and more,0
277
+ 276,f,1,1,0,1,1,0,1,1,1,1,no,no,10.5634741,White-European,Jordan,no,11.703504,Self,18 and more,0
278
+ 277,f,1,1,0,0,0,0,0,1,0,0,no,no,21.01101122,Middle Eastern ,Sri Lanka,no,8.791906377,Self,18 and more,0
279
+ 278,m,0,0,0,1,0,0,1,1,1,0,no,yes,42.48618909,White-European,Australia,no,12.26234366,?,18 and more,0
280
+ 279,f,1,1,0,1,0,0,0,1,0,0,no,no,42.75701238,Middle Eastern ,Jordan,yes,-0.524132132,Self,18 and more,0
281
+ 280,m,0,1,0,1,1,0,1,1,0,1,yes,no,17.58923301,White-European,United States,no,10.81288329,Self,18 and more,1
282
+ 281,m,0,0,1,0,1,0,0,0,0,1,no,no,19.46567705,Asian,Italy,no,4.298842076,Self,18 and more,0
283
+ 282,m,0,0,0,0,0,0,0,0,0,0,no,no,17.73800278,Middle Eastern ,United Arab Emirates,no,1.907108929,?,18 and more,0
284
+ 283,m,0,0,0,0,0,0,0,0,0,0,yes,no,26.73184805,Asian,United Arab Emirates,no,5.752815448,Self,18 and more,0
285
+ 284,m,1,1,1,1,1,1,1,1,1,1,yes,yes,24.3593635,White-European,Australia,no,13.20920533,Self,18 and more,1
286
+ 285,f,1,0,0,0,0,0,0,1,0,1,no,no,29.4190243,?,India,no,5.920914216,?,18 and more,1
287
+ 286,m,0,0,0,0,1,0,1,1,0,1,no,yes,18.18918108,?,India,no,6.536817286,Self,18 and more,0
288
+ 287,m,1,0,0,0,0,0,0,1,0,0,yes,no,21.16633943,Pasifika,Mexico,no,1.927369175,Self,18 and more,0
289
+ 288,m,0,0,0,0,0,0,0,0,0,0,no,no,24.88092657,South Asian,New Zealand,no,5.224401384,Self,18 and more,0
290
+ 289,m,1,1,0,0,0,0,0,1,0,0,no,no,17.38496811,Middle Eastern ,United Arab Emirates,no,6.033449076,Self,18 and more,0
291
+ 290,f,0,0,0,0,0,0,1,0,0,0,no,no,20.84357913,?,Austria,no,7.868742072,Self,18 and more,0
292
+ 291,m,0,0,0,0,0,0,0,0,0,0,no,no,13.05526927,Middle Eastern ,Indonesia,no,3.349251469,Self,18 and more,0
293
+ 292,f,1,0,0,1,1,0,0,1,0,1,no,no,52.29804788,Asian,United Kingdom,no,11.26167514,Self,18 and more,0
294
+ 293,m,1,0,0,0,1,0,0,0,0,1,no,no,14.20305959,South Asian,Ukraine,no,3.533760283,Self,18 and more,0
295
+ 294,f,1,0,0,0,1,0,1,1,0,0,no,no,33.1608928,Asian,United States,no,11.75003153,Parent,18 and more,0
296
+ 295,f,1,1,1,1,1,1,0,1,1,1,yes,no,23.03114875,Turkish,Kazakhstan,no,11.40019063,Self,18 and more,1
297
+ 296,m,0,0,0,0,0,0,0,0,0,0,no,no,31.91563805,Hispanic,New Zealand,no,5.925811077,Self,18 and more,0
298
+ 297,m,0,0,0,0,0,0,1,0,0,0,no,no,60.77273685,Asian,United Arab Emirates,no,3.489521042,Self,18 and more,0
299
+ 298,m,0,0,0,0,0,0,0,0,0,0,no,no,23.20204756,?,India,no,5.448813597,Self,18 and more,0
300
+ 299,f,0,0,0,0,0,0,0,1,0,0,yes,no,23.68015292,Asian,United Arab Emirates,no,8.590826425,Self,18 and more,0
301
+ 300,f,0,0,0,0,0,0,0,0,0,0,no,no,30.09420007,?,United Arab Emirates,no,-2.145654186,Self,18 and more,0
302
+ 301,f,1,0,0,0,0,0,0,0,0,0,no,no,18.25856763,Asian,United Arab Emirates,no,8.178771633,Self,18 and more,0
303
+ 302,f,1,1,1,1,1,1,1,1,1,1,no,yes,30.86833336,Hispanic,Australia,no,4.104718101,Parent,18 and more,1
304
+ 303,m,1,0,0,0,0,0,1,1,0,0,yes,no,19.44791381,Asian,Afghanistan,no,9.515771923,Relative,18 and more,0
305
+ 304,m,1,0,0,0,0,0,0,1,0,0,yes,no,30.93069813,?,Austria,no,8.09409375,Self,18 and more,0
306
+ 305,m,1,1,0,1,1,0,0,1,0,1,no,no,31.30726252,Others,Italy,no,8.224582899,Self,18 and more,0
307
+ 306,m,0,0,0,0,1,0,0,0,0,0,no,no,36.56146232,?,India,no,4.76614512,Self,18 and more,0
308
+ 307,m,1,0,0,0,0,0,0,0,0,0,yes,no,31.22291175,White-European,Russia,no,1.328079123,Parent,18 and more,0
309
+ 308,f,1,0,0,1,1,0,0,0,0,0,no,no,23.2182734,White-European,New Zealand,yes,4.463859974,Self,18 and more,0
310
+ 309,m,1,0,0,0,0,0,0,1,0,0,no,no,26.54786312,Middle Eastern ,United Arab Emirates,no,5.316559102,Self,18 and more,0
311
+ 310,f,1,0,0,0,1,0,1,1,0,0,no,no,24.95433283,White-European,United States,no,9.725057107,Parent,18 and more,0
312
+ 311,m,1,1,0,0,0,0,0,1,0,0,yes,yes,42.68425606,White-European,India,no,5.963798455,Self,18 and more,0
313
+ 312,m,1,0,0,0,0,0,0,1,0,0,no,no,13.56535916,Others,Italy,no,7.051900091,Self,18 and more,1
314
+ 313,m,1,1,1,0,0,0,0,1,0,1,yes,no,12.86969457,White-European,United States,no,11.81090159,Self,18 and more,1
315
+ 314,m,0,0,0,0,0,0,0,1,0,0,no,no,15.37977429,?,New Zealand,no,2.699439316,Self,18 and more,0
316
+ 315,m,1,0,1,1,1,0,0,1,1,1,no,no,42.89939647,White-European,United States,no,8.27323597,Parent,18 and more,1
317
+ 316,f,1,0,0,0,0,0,1,1,0,0,no,no,31.93818694,Asian,Jordan,no,7.192089823,Relative,18 and more,0
318
+ 317,f,1,0,0,0,0,1,0,1,0,1,yes,no,23.82980847,South Asian,Afghanistan,yes,4.550425249,Relative,18 and more,0
319
+ 318,f,0,0,0,0,0,0,0,1,0,0,yes,no,12.82718298,South Asian,AmericanSamoa,no,7.872617263,Self,18 and more,0
320
+ 319,m,1,0,1,0,1,1,1,1,1,0,no,no,68.00507033,Others,Jordan,no,8.560372176,Self,18 and more,1
321
+ 320,m,1,1,1,1,1,1,1,1,1,1,yes,no,31.6665334,White-European,United States,no,9.948601004,Self,18 and more,1
322
+ 321,m,1,0,0,1,1,0,0,1,0,0,no,no,24.21829393,Latino,United Kingdom,no,3.029855289,Self,18 and more,0
323
+ 322,m,0,0,1,0,1,0,0,1,0,0,yes,no,36.38011773,Middle Eastern ,Germany,no,2.009928568,Relative,18 and more,0
324
+ 323,f,1,0,0,0,0,0,1,1,0,0,no,no,18.06833783,Middle Eastern ,Ethiopia,no,11.39723584,?,18 and more,0
325
+ 324,f,1,0,1,0,1,1,0,0,0,1,yes,no,20.02135637,Latino,United Arab Emirates,no,6.172033882,Self,18 and more,0
326
+ 325,m,1,1,1,1,1,1,1,1,1,1,no,yes,39.62488238,White-European,United States,no,13.08977496,Self,18 and more,1
327
+ 326,m,1,0,0,0,0,1,0,1,1,0,no,no,27.62361603,Pasifika,Austria,no,9.073246593,Parent,18 and more,0
328
+ 327,f,1,0,1,1,1,0,1,0,0,1,no,no,17.02472387,Middle Eastern ,United Kingdom,yes,5.394525433,Relative,18 and more,0
329
+ 328,m,1,0,0,0,0,0,0,1,0,0,no,no,27.02340181,?,Jordan,no,0.551235469,Self,18 and more,0
330
+ 329,f,1,0,0,0,0,0,0,0,0,0,no,no,21.46375329,Middle Eastern ,Canada,no,4.972963749,Self,18 and more,0
331
+ 330,f,1,0,0,0,1,0,1,1,0,1,no,no,31.2896551,South Asian,United States,no,9.481809578,Relative,18 and more,0
332
+ 331,m,1,0,1,1,1,0,0,0,1,0,yes,no,12.83857004,Latino,Malaysia,no,7.04216097,Self,18 and more,0
333
+ 332,m,0,0,0,0,0,0,0,1,1,0,no,no,15.8295188,Middle Eastern ,Sri Lanka,no,6.626722769,Self,18 and more,0
334
+ 333,m,0,0,0,0,0,0,0,1,0,0,no,no,25.05091735,?,United States,no,0.836056486,Self,18 and more,0
335
+ 334,m,0,0,0,1,0,0,0,1,0,0,yes,no,15.29881605,White-European,United Arab Emirates,no,6.220675496,Self,18 and more,0
336
+ 335,m,0,0,0,0,0,0,0,1,0,0,yes,no,23.35035887,?,New Zealand,no,4.852378265,Self,18 and more,0
337
+ 336,f,0,1,0,0,0,0,0,0,1,1,no,no,16.77398843,Middle Eastern ,Jordan,no,3.91475096,Self,18 and more,0
338
+ 337,f,1,0,0,0,0,0,0,1,1,1,no,no,41.49551501,Middle Eastern ,Mexico,no,11.83752622,Self,18 and more,0
339
+ 338,f,1,0,0,0,1,0,0,0,0,0,yes,no,24.84610005,Black,New Zealand,no,9.470815192,Self,18 and more,0
340
+ 339,f,1,0,0,1,1,0,0,1,1,1,yes,no,28.82518176,Latino,United Kingdom,yes,9.172861611,Self,18 and more,0
341
+ 340,m,0,0,0,0,0,0,0,1,0,0,yes,no,23.42443608,?,United Arab Emirates,no,-0.578639469,Self,18 and more,0
342
+ 341,m,1,1,1,1,1,0,1,1,0,1,no,no,21.26872388,White-European,United States,no,12.09716243,Self,18 and more,1
343
+ 342,f,0,1,0,0,0,0,0,0,0,0,no,no,39.98092074,Middle Eastern ,United Arab Emirates,no,4.24837447,Self,18 and more,0
344
+ 343,f,1,0,1,1,1,0,0,1,0,1,no,no,29.68072364,Pasifika,United Kingdom,no,10.74172242,Self,18 and more,0
345
+ 344,m,0,0,0,0,1,0,0,1,0,0,no,no,16.33592748,Asian,United Arab Emirates,no,2.10827046,?,18 and more,0
346
+ 345,f,0,1,1,1,1,1,1,1,1,1,yes,no,14.24864659,White-European,United States,no,12.98104502,Self,18 and more,0
347
+ 346,m,0,0,0,1,1,0,0,1,0,0,no,yes,39.29122616,Pasifika,France,no,12.89944481,Relative,18 and more,0
348
+ 347,m,0,0,0,0,0,0,1,1,0,0,no,yes,40.5312181,?,New Zealand,no,5.498083364,Self,18 and more,0
349
+ 348,m,1,0,0,0,0,0,0,0,0,0,yes,no,32.24661514,Asian,New Zealand,no,6.474593814,Self,18 and more,0
350
+ 349,f,0,0,0,0,0,0,0,1,0,0,yes,no,43.20086314,?,India,no,8.236165183,Parent,18 and more,0
351
+ 350,f,1,1,0,1,1,0,1,1,0,1,no,no,26.8411853,White-European,Australia,no,12.35747827,Self,18 and more,0
352
+ 351,m,1,0,1,1,1,1,1,1,1,1,no,no,53.679868,Latino,United Kingdom,no,11.57253963,Self,18 and more,1
353
+ 352,m,1,0,0,0,1,0,0,1,0,0,no,no,13.82400342,?,New Zealand,no,9.651752567,Self,18 and more,1
354
+ 353,m,0,0,0,1,0,0,0,1,0,0,no,no,20.50981094,Asian,Russia,no,5.607472746,Self,18 and more,0
355
+ 354,f,1,0,0,0,0,0,0,0,0,1,no,no,17.19178706,?,India,no,3.342984522,Self,18 and more,0
356
+ 355,m,0,0,0,0,0,0,0,1,0,1,no,no,19.2414331,?,New Zealand,no,9.644356268,?,18 and more,0
357
+ 356,m,1,1,1,0,1,1,1,1,1,1,no,no,32.1208691,Black,Australia,no,12.28760237,Self,18 and more,1
358
+ 357,f,0,0,0,0,0,0,0,1,0,0,no,no,31.90788624,Pasifika,United Arab Emirates,no,1.185194016,Self,18 and more,0
359
+ 358,f,0,0,0,0,0,0,0,0,0,0,no,no,12.52876169,Middle Eastern ,China,no,2.552895746,Self,18 and more,0
360
+ 359,f,0,0,0,0,0,0,0,1,0,0,no,no,16.16648629,Asian,India,no,1.331991392,Self,18 and more,0
361
+ 360,f,1,1,1,1,1,0,0,1,0,1,no,no,28.44874139,Latino,United Kingdom,no,6.061296009,Self,18 and more,0
362
+ 361,m,1,1,1,1,0,1,0,1,0,1,no,no,29.6550994,Middle Eastern ,Jordan,no,11.96952899,Self,18 and more,0
363
+ 362,f,1,1,1,1,1,0,1,1,1,1,yes,no,49.18932273,White-European,Canada,no,12.91535092,Relative,18 and more,1
364
+ 363,f,1,0,0,0,0,0,0,0,0,0,no,no,27.02093489,Black,New Zealand,no,3.693445308,Self,18 and more,0
365
+ 364,m,0,0,0,0,0,0,0,0,0,1,no,no,21.37635914,?,Afghanistan,no,3.094386119,Self,18 and more,0
366
+ 365,m,1,0,1,0,0,0,0,1,0,0,no,yes,45.50121366,Middle Eastern ,India,no,3.644848604,Self,18 and more,0
367
+ 366,f,1,0,0,0,0,0,0,1,0,0,no,no,29.22416068,White-European,Jordan,yes,-1.365137187,Self,18 and more,0
368
+ 367,m,0,0,1,1,1,0,1,1,1,1,no,yes,62.55643314,Black,United States,no,12.10215808,Self,18 and more,1
369
+ 368,f,1,1,1,1,1,0,0,1,0,1,no,yes,18.40592409,Black,Armenia,no,11.30392493,Self,18 and more,0
370
+ 369,m,1,0,1,1,1,0,1,1,1,1,no,no,53.27325592,White-European,United States,no,9.629531019,Self,18 and more,1
371
+ 370,f,1,0,0,0,0,0,0,0,0,0,no,no,24.123863,Asian,United Arab Emirates,no,5.73739963,?,18 and more,0
372
+ 371,f,1,1,0,1,1,0,0,1,0,0,no,no,24.53218093,Asian,United States,no,6.914954875,Self,18 and more,0
373
+ 372,m,0,0,0,0,0,0,0,0,0,0,no,no,14.71882514,Middle Eastern ,Iraq,no,2.802334305,Self,18 and more,0
374
+ 373,m,1,0,0,1,1,0,0,1,0,1,no,no,20.71728983,White-European,India,no,11.81389184,Self,18 and more,0
375
+ 374,f,1,1,1,1,1,1,0,1,1,1,yes,no,59.93790237,Middle Eastern ,Australia,no,13.27367122,Self,18 and more,1
376
+ 375,m,0,0,0,0,0,0,0,0,0,0,yes,no,28.80726462,Middle Eastern ,India,no,3.90914495,Self,18 and more,0
377
+ 376,f,1,0,0,0,1,0,1,0,0,0,no,no,17.17781586,Black,Tonga,no,5.203429944,Self,18 and more,0
378
+ 377,m,0,0,0,0,0,0,0,1,0,0,no,no,27.49343743,?,India,no,3.652764585,Self,18 and more,0
379
+ 378,f,1,0,0,0,1,0,1,0,0,1,yes,no,26.86271615,Asian,New Zealand,no,7.138836719,Self,18 and more,0
380
+ 379,f,0,0,0,0,0,0,0,0,0,1,no,yes,13.7767075,Black,Malaysia,yes,7.34186051,?,18 and more,0
381
+ 380,m,1,0,0,0,0,0,0,1,0,0,no,no,22.08052022,Middle Eastern ,Jordan,no,-1.351506465,Self,18 and more,0
382
+ 381,f,0,0,0,0,1,0,0,1,0,1,no,no,24.45652938,?,Czech Republic,no,9.288201929,Self,18 and more,0
383
+ 382,m,1,0,1,0,1,0,0,1,0,1,yes,no,17.45912374,White-European,United States,no,5.850855258,Self,18 and more,0
384
+ 383,f,0,0,0,0,0,0,0,0,0,0,no,no,24.12367143,Middle Eastern ,United Arab Emirates,no,4.879532866,Self,18 and more,0
385
+ 384,m,1,1,1,1,1,0,1,1,1,1,no,no,55.31824746,White-European,India,no,9.444737892,Self,18 and more,1
386
+ 385,f,1,1,1,1,1,1,1,1,1,1,yes,yes,42.33192443,White-European,United States,no,13.36258928,Self,18 and more,1
387
+ 386,f,1,0,0,1,0,0,1,1,0,1,yes,no,25.4680538,Asian,India,no,3.362363384,Health care professional,18 and more,0
388
+ 387,m,0,1,1,0,0,1,1,1,1,1,no,no,35.35945091,White-European,New Zealand,yes,9.665143723,Parent,18 and more,0
389
+ 388,f,0,0,0,0,0,0,0,0,0,0,no,no,27.18027983,?,United Arab Emirates,no,0.836639582,?,18 and more,0
390
+ 389,f,1,1,1,1,1,1,1,1,1,1,no,yes,54.73967471,White-European,United States,no,12.63225658,Relative,18 and more,1
391
+ 390,m,0,0,0,0,0,0,0,1,0,0,no,no,18.08361893,?,United Arab Emirates,no,0.268759344,Self,18 and more,0
392
+ 391,f,0,0,0,0,1,0,0,0,0,0,no,no,31.19787597,Asian,Belgium,no,4.368180022,?,18 and more,0
393
+ 392,m,0,0,0,0,0,0,0,0,0,0,yes,no,27.99924973,?,United Arab Emirates,no,2.942163053,?,18 and more,0
394
+ 393,m,0,0,0,0,0,0,1,1,0,1,no,no,20.37347736,?,New Zealand,no,5.183983433,Self,18 and more,0
395
+ 394,m,1,1,1,0,1,0,1,1,1,1,no,no,21.9272415,?,United States,no,7.964066134,Self,18 and more,0
396
+ 395,m,1,0,0,0,0,0,0,1,0,0,no,no,23.64302675,Middle Eastern ,Australia,no,3.730796128,Self,18 and more,0
397
+ 396,f,0,0,0,0,0,0,0,1,0,0,no,no,18.85460181,White-European,New Zealand,no,-0.114241635,Self,18 and more,0
398
+ 397,f,1,0,0,1,1,1,1,1,1,1,no,no,37.50376579,Pasifika,Australia,no,8.308822671,Parent,18 and more,0
399
+ 398,f,0,0,0,0,0,0,0,0,0,0,no,no,19.14520463,Asian,Ireland,no,4.381557274,Parent,18 and more,0
400
+ 399,f,1,0,0,0,0,0,0,0,0,0,no,no,23.0040436,Pasifika,India,no,4.238468468,?,18 and more,0
401
+ 400,f,0,1,1,1,1,1,1,1,1,1,yes,yes,35.04822411,White-European,United States,no,12.30776422,Self,18 and more,1
402
+ 401,f,1,1,1,1,1,1,1,1,1,1,no,yes,29.62630088,Asian,Netherlands,no,13.2763215,Self,18 and more,1
403
+ 402,m,0,0,0,0,0,0,0,0,0,0,yes,no,29.32415568,Middle Eastern ,Jordan,no,3.291464905,?,18 and more,0
404
+ 403,f,1,0,0,0,0,0,0,0,0,0,no,no,16.00881089,South Asian,India,no,-0.731327905,?,18 and more,0
405
+ 404,f,1,1,0,0,0,0,0,1,0,0,no,no,27.21368809,Black,Costa Rica,no,7.362717915,Self,18 and more,0
406
+ 405,f,1,1,1,1,1,1,0,1,1,1,no,no,33.71533635,Latino,United Kingdom,no,11.36037509,Self,18 and more,1
407
+ 406,m,0,0,0,0,0,0,0,1,0,0,yes,no,26.30897678,?,South Africa,no,6.478800441,Self,18 and more,0
408
+ 407,m,0,0,0,0,1,0,0,0,0,1,no,no,20.35515932,Middle Eastern ,Armenia,no,9.681837732,Self,18 and more,0
409
+ 408,m,0,0,0,0,0,0,0,1,0,0,no,no,17.6883325,?,India,no,2.942578753,Self,18 and more,0
410
+ 409,f,1,0,1,1,1,1,0,1,0,1,yes,no,27.88425018,Latino,Italy,no,10.71969383,Self,18 and more,1
411
+ 410,f,0,1,1,1,1,1,1,1,1,1,no,yes,71.3560697,White-European,United States,no,12.96966148,Self,18 and more,0
412
+ 411,m,1,1,1,0,1,1,1,0,1,1,no,yes,15.70727497,White-European,New Zealand,no,11.63895935,Self,18 and more,0
413
+ 412,f,1,1,1,1,1,0,0,1,1,1,no,no,63.75155625,?,United Kingdom,no,8.243807622,Self,18 and more,0
414
+ 413,f,0,1,0,1,0,0,0,1,0,0,no,no,21.48013904,?,Aruba,no,7.253067162,Parent,18 and more,1
415
+ 414,f,1,0,1,1,1,0,0,1,0,1,no,no,25.99219163,Hispanic,United States,no,0.24570513,Self,18 and more,1
416
+ 415,f,1,0,0,0,0,0,0,1,0,0,no,no,47.73008947,Asian,United Arab Emirates,no,4.216112344,Relative,18 and more,0
417
+ 416,f,1,1,1,0,1,0,1,1,1,0,no,no,15.36731189,Asian,Australia,no,7.663374849,Self,18 and more,1
418
+ 417,f,0,0,1,0,1,0,0,1,0,1,yes,no,45.61232401,White-European,New Zealand,no,7.75216827,Self,18 and more,0
419
+ 418,f,1,1,1,1,1,1,1,1,1,1,yes,yes,46.36992639,White-European,United States,no,13.20735144,Parent,18 and more,1
420
+ 419,f,0,0,0,1,1,0,0,1,1,1,no,no,18.878002,Asian,United States,no,4.092610809,Self,18 and more,1
421
+ 420,m,0,0,1,0,0,0,0,0,0,0,yes,yes,36.71172301,?,New Zealand,no,7.428460284,Self,18 and more,0
422
+ 421,m,0,0,0,0,0,0,0,1,0,0,yes,no,22.61521304,Asian,United Arab Emirates,no,1.919248623,Parent,18 and more,0
423
+ 422,f,0,1,1,1,1,1,1,1,1,1,yes,no,37.51947298,Middle Eastern ,United Kingdom,no,12.59111873,Self,18 and more,0
424
+ 423,f,1,1,1,1,1,1,0,1,0,1,no,no,25.11012862,White-European,Australia,no,2.020266979,Self,18 and more,1
425
+ 424,f,1,0,1,0,0,1,0,1,0,0,yes,yes,22.91816929,Middle Eastern ,United Arab Emirates,no,3.184134702,Self,18 and more,1
426
+ 425,m,0,1,0,0,0,0,0,0,0,0,no,no,23.1327722,Latino,New Zealand,no,0.094052114,?,18 and more,0
427
+ 426,m,0,0,1,1,1,0,0,1,0,1,no,no,42.06175986,White-European,Saudi Arabia,no,7.277024082,Self,18 and more,0
428
+ 427,m,1,0,0,0,1,0,0,1,0,1,yes,no,26.22617053,Middle Eastern ,India,no,9.972671946,Self,18 and more,0
429
+ 428,m,1,0,0,0,1,0,0,1,0,0,no,no,19.72333156,Others,New Zealand,no,-0.397115644,Self,18 and more,0
430
+ 429,f,0,0,1,1,1,0,0,1,0,0,no,no,19.33816764,?,Jordan,no,5.273476284,Self,18 and more,1
431
+ 430,m,1,0,0,1,0,0,0,0,0,0,no,no,26.0779911,South Asian,France,no,4.758367591,?,18 and more,0
432
+ 431,m,0,0,0,0,0,0,0,0,0,0,no,no,18.50849917,Asian,Afghanistan,no,1.253396324,Parent,18 and more,0
433
+ 432,f,1,1,1,1,1,1,1,1,1,1,no,yes,27.52895152,Asian,United States,no,13.04895122,Self,18 and more,1
434
+ 433,f,1,0,0,0,0,0,0,0,0,0,no,no,20.09622766,Others,Afghanistan,no,9.449537208,Self,18 and more,0
435
+ 434,m,1,0,1,1,1,1,1,1,1,0,yes,yes,62.61132166,White-European,United States,no,12.27861528,Self,18 and more,1
436
+ 435,m,1,1,1,1,0,0,0,1,1,1,yes,no,24.12553692,Black,Australia,no,10.21445717,Self,18 and more,0
437
+ 436,m,1,0,1,1,1,1,1,1,1,1,yes,no,23.80967704,South Asian,United States,no,13.23101706,Self,18 and more,1
438
+ 437,f,1,0,0,0,0,0,1,1,0,0,no,no,27.17141621,Asian,Sri Lanka,no,5.677578058,Self,18 and more,0
439
+ 438,f,0,0,0,1,1,0,1,0,0,1,no,no,14.64496199,Black,New Zealand,no,-0.637978548,Self,18 and more,0
440
+ 439,m,0,0,1,1,1,1,1,1,0,1,yes,yes,18.1293108,White-European,Hong Kong,no,9.415300732,Self,18 and more,1
441
+ 440,m,0,0,0,0,0,0,0,1,0,0,no,no,20.39207733,?,United Arab Emirates,no,4.779981236,Self,18 and more,0
442
+ 441,f,1,1,1,1,1,1,1,1,1,1,yes,yes,35.79293299,White-European,United States,no,13.1838067,Self,18 and more,1
443
+ 442,f,0,0,0,1,0,0,0,1,0,1,yes,yes,41.36860529,White-European,New Zealand,yes,6.052666568,Relative,18 and more,0
444
+ 443,m,0,0,0,0,1,0,1,1,0,0,no,no,38.40680094,?,India,yes,6.928087239,Relative,18 and more,0
445
+ 444,f,1,0,0,0,0,0,0,0,0,0,no,no,31.70883972,Asian,India,no,5.862623736,Self,18 and more,0
446
+ 445,m,1,0,1,0,0,0,0,1,0,0,no,no,29.36037187,Turkish,Austria,no,5.413757058,Self,18 and more,0
447
+ 446,f,1,1,1,1,1,1,1,1,1,1,yes,no,44.77318337,Hispanic,United States,no,13.24973082,Self,18 and more,1
448
+ 447,f,0,0,0,0,0,0,0,0,0,0,no,no,33.94300046,?,New Zealand,no,4.797745538,Self,18 and more,0
449
+ 448,m,1,1,0,0,1,0,1,1,1,1,no,yes,26.1659676,?,France,no,5.106865272,Self,18 and more,1
450
+ 449,f,0,0,0,0,0,0,0,0,0,0,no,no,14.27922507,?,Brazil,no,7.398362069,Self,18 and more,0
451
+ 450,m,0,1,0,0,0,0,0,1,0,0,no,no,27.60839705,Black,New Zealand,no,-0.843331801,?,18 and more,0
452
+ 451,m,1,0,0,0,0,0,0,1,0,0,no,yes,12.14264103,Latino,Afghanistan,no,-0.053714599,?,18 and more,0
453
+ 452,f,1,0,0,1,1,0,1,1,1,1,no,no,32.20423469,Middle Eastern ,United Kingdom,no,10.28273974,Self,18 and more,0
454
+ 453,f,0,0,0,0,0,0,0,0,0,1,no,no,18.84329479,South Asian,Jordan,no,9.825040248,Self,18 and more,0
455
+ 454,f,1,0,1,1,1,1,0,1,1,1,no,yes,21.32558768,White-European,United States,no,12.69722854,Self,18 and more,1
456
+ 455,f,0,1,1,0,1,0,0,1,0,0,no,no,25.81976021,Others,New Zealand,no,0.737685691,Parent,18 and more,0
457
+ 456,f,1,1,1,1,1,1,1,1,1,1,no,yes,41.84811585,White-European,United States,no,13.072258,Self,18 and more,1
458
+ 457,m,0,0,0,0,0,0,0,1,0,0,no,no,14.40240138,?,India,no,8.086719943,Self,18 and more,0
459
+ 458,m,0,0,0,1,0,0,0,1,0,1,no,no,24.22036485,White-European,New Zealand,no,10.83556394,Self,18 and more,0
460
+ 459,m,1,0,1,0,1,0,0,0,0,0,no,no,21.56342103,?,India,no,5.027273131,Self,18 and more,0
461
+ 460,m,1,0,0,0,0,0,0,0,0,0,no,no,47.96276884,Middle Eastern ,Australia,no,3.738368667,Self,18 and more,0
462
+ 461,m,0,0,0,0,1,0,0,1,0,0,yes,no,12.65425437,?,New Zealand,no,9.760875492,Self,18 and more,0
463
+ 462,f,0,1,0,0,0,0,0,1,0,1,no,no,18.92173852,Pasifika,Serbia,no,7.140389152,Self,18 and more,0
464
+ 463,f,1,0,0,0,0,0,0,1,0,1,yes,no,32.61509975,Asian,Jordan,no,5.777347423,Self,18 and more,0
465
+ 464,m,0,1,1,1,0,1,1,1,1,1,no,no,26.92375026,Asian,Russia,no,12.81794677,Self,18 and more,1
466
+ 465,m,0,0,0,0,0,0,0,0,0,0,no,no,39.38579107,Middle Eastern ,United Arab Emirates,no,3.120465052,Parent,18 and more,0
467
+ 466,f,0,0,0,0,0,0,0,1,0,0,no,no,16.50360662,Middle Eastern ,Bahamas,no,4.708005825,Self,18 and more,0
468
+ 467,m,0,0,0,0,0,0,0,1,0,0,no,no,15.95961571,?,South Africa,no,3.386411362,?,18 and more,0
469
+ 468,f,0,0,0,0,1,0,1,1,0,0,no,no,40.0526163,?,India,no,3.424795878,Self,18 and more,0
470
+ 469,f,1,0,1,1,1,0,0,1,1,0,no,no,48.11471037,White-European,United States,no,7.690646922,Self,18 and more,1
471
+ 470,m,1,1,1,1,1,1,1,1,1,1,yes,no,28.70467543,White-European,United States,no,10.55592026,Self,18 and more,1
472
+ 471,f,1,1,1,1,1,1,1,1,0,1,no,no,28.30261772,Latino,Austria,no,7.310344773,Self,18 and more,1
473
+ 472,m,1,0,0,0,0,0,1,0,0,1,no,no,27.22430953,Asian,United Kingdom,no,2.131516361,Parent,18 and more,0
474
+ 473,f,1,0,1,1,1,1,0,1,1,1,yes,no,35.5579975,Latino,United Kingdom,no,9.481148679,Self,18 and more,1
475
+ 474,f,1,0,0,0,0,0,0,0,0,0,no,no,24.59416695,Middle Eastern ,Philippines,no,10.7975561,Self,18 and more,0
476
+ 475,m,1,0,0,1,1,0,0,1,0,0,yes,no,23.988549,White-European,United States,no,2.244135741,Self,18 and more,0
477
+ 476,m,1,1,0,0,1,0,0,1,1,1,yes,no,33.25859799,White-European,Australia,no,0.850671254,Self,18 and more,0
478
+ 477,m,0,0,0,0,0,0,1,1,0,0,no,no,31.74017364,Asian,Iran,no,3.974648664,Self,18 and more,0
479
+ 478,m,0,1,0,0,0,0,0,1,1,0,no,no,27.26622279,?,Kazakhstan,no,6.893227395,Self,18 and more,0
480
+ 479,m,0,0,1,1,1,0,0,0,0,0,no,no,17.10192393,Asian,Costa Rica,no,8.62753184,Self,18 and more,0
481
+ 480,f,0,0,0,0,0,0,0,1,0,0,no,no,17.61761346,Pasifika,United Arab Emirates,no,11.36327022,Self,18 and more,0
482
+ 481,f,1,0,0,0,1,0,0,1,0,1,no,no,12.76969932,Black,Kazakhstan,no,9.007282599,Self,18 and more,0
483
+ 482,f,1,0,1,0,1,0,0,1,0,0,no,no,28.64516606,?,United States,no,6.893716452,Self,18 and more,0
484
+ 483,f,0,0,0,0,0,0,0,0,0,0,no,no,20.63988618,?,Ecuador,no,7.054498882,Self,18 and more,0
485
+ 484,f,1,0,0,0,0,0,0,0,0,0,no,no,26.33027826,Middle Eastern ,United Arab Emirates,no,11.36501162,Self,18 and more,0
486
+ 485,f,0,0,0,0,0,0,0,1,0,0,yes,no,28.96044414,?,Belgium,no,5.416194369,Self,18 and more,0
487
+ 486,m,1,1,0,0,1,1,0,0,1,1,no,no,16.51915492,Black,Spain,no,6.540470503,Self,18 and more,0
488
+ 487,m,0,0,0,0,0,0,0,0,0,0,no,no,38.92086202,Asian,United Arab Emirates,no,4.684038484,Self,18 and more,0
489
+ 488,m,1,0,0,0,0,0,0,1,0,0,yes,yes,12.88899428,Hispanic,Viet Nam,no,3.687846531,Self,18 and more,0
490
+ 489,f,1,1,1,1,1,1,0,1,1,1,no,no,31.67681913,?,United States,no,12.22045421,Self,18 and more,1
491
+ 490,m,0,0,0,0,0,0,0,1,0,0,no,yes,26.55083095,Black,Russia,no,8.384898353,Self,18 and more,0
492
+ 491,f,1,0,1,1,1,0,1,1,1,1,no,no,16.80623143,Asian,Italy,no,7.888463301,Self,18 and more,0
493
+ 492,m,1,1,1,1,1,0,1,0,1,1,no,no,22.65097981,White-European,Romania,no,12.38114961,Self,18 and more,1
494
+ 493,f,0,0,0,0,0,0,0,0,0,1,no,no,14.91975497,?,United Arab Emirates,no,3.884064981,Self,18 and more,0
495
+ 494,m,0,1,0,0,0,0,0,1,0,0,no,no,43.52066788,Others,Iran,no,5.283778686,Parent,18 and more,0
496
+ 495,f,0,0,0,0,0,0,0,1,0,0,no,no,18.55221155,Middle Eastern ,United Arab Emirates,no,0.136623352,Self,18 and more,0
497
+ 496,m,1,0,1,1,0,1,1,1,0,0,no,no,14.86917251,White-European,United Kingdom,no,9.601139453,Parent,18 and more,1
498
+ 497,m,0,0,0,0,0,0,0,0,0,0,no,no,19.25641523,?,New Zealand,no,1.651385643,Self,18 and more,0
499
+ 498,f,1,1,1,1,1,1,0,1,0,1,no,yes,22.3696796,White-European,Cyprus,no,12.95596589,Self,18 and more,1
500
+ 499,f,0,0,0,0,0,0,0,1,1,1,yes,no,33.01259387,White-European,Jordan,no,5.851810302,Self,18 and more,0
501
+ 500,m,1,0,0,0,0,0,0,1,0,0,no,no,24.15741484,?,New Zealand,no,2.681468273,Self,18 and more,0
502
+ 501,f,1,1,0,0,0,0,0,1,0,1,no,no,67.41174403,Asian,United States,no,6.963076452,Self,18 and more,0
503
+ 502,f,1,0,0,0,0,0,1,0,0,0,no,no,21.55418788,Pasifika,Brazil,no,8.66095379,Self,18 and more,0
504
+ 503,f,0,0,0,1,1,0,1,1,1,0,no,no,24.44399463,Pasifika,South Africa,no,5.726659629,Self,18 and more,0
505
+ 504,f,0,0,0,0,0,0,0,0,0,0,no,no,13.87320354,Middle Eastern ,Afghanistan,no,7.396045276,Self,18 and more,0
506
+ 505,f,0,0,0,0,1,0,0,1,0,0,yes,no,25.30884824,South Asian,United Arab Emirates,no,8.947422892,Self,18 and more,0
507
+ 506,f,0,1,0,0,0,0,0,0,1,0,no,no,20.462625,White-European,United Arab Emirates,no,10.02665843,Self,18 and more,0
508
+ 507,f,1,0,0,1,0,0,0,1,0,0,no,no,11.79157315,Middle Eastern ,Australia,no,5.699756948,Self,18 and more,0
509
+ 508,m,1,1,1,1,1,1,0,1,1,1,no,yes,18.58263362,White-European,Armenia,no,11.64561512,Self,18 and more,1
510
+ 509,m,1,0,0,1,1,0,0,1,0,0,no,no,21.72161031,South Asian,China,no,1.807569102,Self,18 and more,0
511
+ 510,f,1,1,1,1,1,0,1,1,1,1,yes,yes,16.86475024,White-European,Spain,no,9.485197553,Self,18 and more,1
512
+ 511,f,0,0,1,1,1,1,1,1,1,0,yes,no,21.18039464,Black,United States,no,7.175429475,Self,18 and more,0
513
+ 512,f,1,0,0,1,1,0,1,1,1,1,no,no,28.39483372,White-European,United Arab Emirates,no,11.77900624,Self,18 and more,0
514
+ 513,f,1,1,1,1,1,1,0,1,1,1,no,yes,49.43439359,Latino,United Kingdom,no,12.21654553,Self,18 and more,1
515
+ 514,f,1,0,1,1,1,1,1,0,1,0,yes,yes,33.96043139,White-European,United Arab Emirates,no,12.68886365,Self,18 and more,1
516
+ 515,f,1,0,0,0,1,0,0,1,0,0,no,no,14.80201297,?,United States,no,6.840066215,?,18 and more,0
517
+ 516,m,1,1,1,0,1,0,0,1,0,1,yes,yes,24.32227986,Asian,Bahamas,no,7.727729298,Self,18 and more,0
518
+ 517,f,1,1,1,1,1,1,0,1,1,1,yes,no,24.04626135,Black,New Zealand,no,12.55137788,Self,18 and more,1
519
+ 518,f,1,1,1,1,1,0,1,1,1,1,no,no,16.49474382,White-European,Austria,no,11.43269455,Self,18 and more,1
520
+ 519,m,1,1,1,1,1,1,1,1,1,1,no,no,37.84456589,White-European,United States,yes,12.20785986,Self,18 and more,1
521
+ 520,f,1,1,1,1,1,1,1,1,1,1,no,no,27.67536663,White-European,United States,no,13.10683218,Self,18 and more,1
522
+ 521,f,0,0,0,0,0,0,0,0,0,0,no,no,39.95680615,Asian,Brazil,no,3.553688051,Parent,18 and more,0
523
+ 522,f,1,0,1,1,1,1,1,1,1,1,yes,yes,24.95784588,White-European,United Kingdom,no,6.501704297,Self,18 and more,0
524
+ 523,m,0,0,0,0,0,0,0,1,0,1,no,no,69.18521211,White-European,United States,no,2.487216742,Self,18 and more,0
525
+ 524,m,0,0,0,1,0,0,0,1,0,1,no,no,12.68882004,White-European,France,no,2.192714583,Self,18 and more,0
526
+ 525,f,0,1,0,0,0,0,0,1,0,0,no,no,28.75761551,Black,United Arab Emirates,no,5.107533601,Self,18 and more,0
527
+ 526,f,0,0,0,0,0,0,0,1,0,0,no,no,17.20033928,Middle Eastern ,United Arab Emirates,no,1.25410481,Self,18 and more,0
528
+ 527,m,0,0,0,1,1,0,0,0,0,0,no,no,33.49453904,?,Kazakhstan,no,9.799758683,Self,18 and more,0
529
+ 528,f,1,1,1,1,1,1,1,1,1,1,no,no,23.75933805,White-European,United Kingdom,no,11.06965621,Self,18 and more,1
530
+ 529,m,1,1,1,1,1,1,1,1,1,1,yes,no,32.73950568,White-European,United States,no,12.90378653,Self,18 and more,1
531
+ 530,m,0,0,0,0,0,0,0,0,0,0,no,no,29.24703151,?,New Zealand,no,4.573765832,Self,18 and more,0
532
+ 531,f,0,0,0,0,0,0,0,0,0,1,yes,yes,29.1090159,Asian,Jordan,no,1.82880096,Self,18 and more,0
533
+ 532,m,1,0,1,0,1,0,1,1,0,1,no,no,14.78618617,?,United Arab Emirates,yes,3.653084638,?,18 and more,0
534
+ 533,m,1,0,0,0,1,0,0,1,0,0,yes,no,29.8900979,?,New Zealand,no,9.507900334,Parent,18 and more,0
535
+ 534,f,1,0,0,1,1,1,1,1,1,1,yes,no,19.2906371,Others,Ireland,no,7.007598776,Self,18 and more,1
536
+ 535,f,0,0,1,1,1,0,0,0,1,1,no,yes,28.49001339,White-European,United States,no,12.55470746,Self,18 and more,1
537
+ 536,f,1,1,1,1,1,1,1,1,1,1,yes,yes,31.07938808,White-European,United States,no,13.30546091,Self,18 and more,1
538
+ 537,m,0,0,1,0,0,0,0,1,0,1,yes,no,25.15268641,?,New Zealand,no,5.993903211,Self,18 and more,0
539
+ 538,m,1,0,1,0,1,1,0,1,1,1,no,yes,25.55980006,White-European,United States,no,12.16208237,Self,18 and more,1
540
+ 539,f,1,0,0,1,0,1,0,1,0,0,no,no,19.83386928,Asian,Mexico,no,5.543136742,Self,18 and more,0
541
+ 540,f,1,0,0,1,0,0,0,1,0,1,no,no,25.62275359,White-European,New Zealand,no,11.02925089,Self,18 and more,1
542
+ 541,m,0,0,1,0,0,0,0,1,0,0,no,no,39.88924895,White-European,United States,no,6.286347677,Self,18 and more,0
543
+ 542,m,1,0,0,0,1,0,0,1,0,1,yes,no,18.45070775,Others,Egypt,no,7.412813177,Self,18 and more,0
544
+ 543,f,1,0,0,0,0,0,1,1,0,0,yes,no,25.18548225,Asian,Egypt,no,7.789261955,Self,18 and more,0
545
+ 544,f,0,0,0,0,0,0,0,0,0,1,no,no,15.49881136,Middle Eastern ,New Zealand,no,7.113329578,Self,18 and more,0
546
+ 545,m,0,0,0,0,0,0,0,0,0,0,no,no,28.63366323,Middle Eastern ,Ethiopia,no,6.889617395,Self,18 and more,0
547
+ 546,m,0,0,0,0,0,0,0,1,0,0,no,no,25.25364327,?,India,no,5.693868475,?,18 and more,0
548
+ 547,m,0,0,0,0,0,0,0,0,0,0,no,no,23.73521,?,Jordan,no,2.062233051,Self,18 and more,0
549
+ 548,f,0,0,0,0,1,0,0,0,0,0,no,no,39.82562563,Asian,Germany,no,4.207514189,Self,18 and more,0
550
+ 549,f,1,0,0,0,1,0,1,1,1,1,no,no,27.63221244,Latino,Bangladesh,no,7.727519307,Self,18 and more,0
551
+ 550,f,1,1,0,0,0,0,0,1,0,1,no,no,27.88412337,Hispanic,Oman,no,6.528725726,Self,18 and more,0
552
+ 551,f,1,0,1,1,1,1,1,1,1,1,no,yes,64.49177551,White-European,United States,no,13.3470969,Self,18 and more,1
553
+ 552,m,0,1,0,1,1,1,1,1,0,1,no,yes,29.19566621,Middle Eastern ,United States,no,5.31052325,Parent,18 and more,0
554
+ 553,m,1,0,0,0,0,0,0,1,0,0,yes,no,59.62775131,Asian,Aruba,no,1.754276914,Self,18 and more,0
555
+ 554,m,1,0,0,1,1,0,0,1,1,0,no,no,26.13549399,Asian,New Zealand,no,4.862571408,Self,18 and more,0
556
+ 555,m,0,0,0,0,0,0,0,1,0,0,no,no,30.76696105,Others,United States,no,6.727457312,Self,18 and more,0
557
+ 556,f,1,0,0,0,0,0,0,0,0,0,no,no,33.22188797,Middle Eastern ,New Zealand,no,10.73274893,Self,18 and more,0
558
+ 557,m,1,1,0,1,0,0,0,1,1,0,no,no,28.30806267,White-European,United Kingdom,no,7.671166337,Self,18 and more,0
559
+ 558,m,0,0,0,1,0,0,0,1,0,1,no,no,16.91663828,White-European,India,no,6.020545888,Self,18 and more,0
560
+ 559,f,0,1,0,0,0,0,0,1,0,1,no,no,20.35027844,?,New Zealand,no,0.688994763,Self,18 and more,0
561
+ 560,f,1,0,0,0,0,0,0,1,0,1,yes,no,45.23752251,?,Costa Rica,no,2.743173797,?,18 and more,0
562
+ 561,f,1,1,0,1,1,0,1,1,0,1,no,no,25.94274099,South Asian,Saudi Arabia,yes,9.778755741,Parent,18 and more,0
563
+ 562,f,1,0,1,1,0,0,0,1,0,1,no,yes,27.96351288,?,France,no,8.581273571,Self,18 and more,0
564
+ 563,f,0,0,0,0,0,0,0,1,0,0,yes,no,46.24912105,Middle Eastern ,South Africa,no,5.782914613,Self,18 and more,0
565
+ 564,f,1,0,1,1,1,0,0,0,0,1,no,no,14.23128228,White-European,United States,no,9.704232363,Self,18 and more,1
566
+ 565,f,1,0,0,0,1,0,1,1,1,1,yes,no,11.79083405,Latino,Netherlands,no,9.593745261,Self,18 and more,0
567
+ 566,f,1,0,1,1,1,1,1,1,1,1,yes,no,55.88994948,White-European,Netherlands,no,9.212422768,Self,18 and more,1
568
+ 567,f,1,0,0,0,0,0,0,1,0,1,no,no,25.93838143,Asian,India,no,1.672875939,Self,18 and more,0
569
+ 568,f,1,0,0,1,1,0,0,1,0,0,no,no,23.6973814,?,Saudi Arabia,no,8.559973792,Relative,18 and more,0
570
+ 569,f,1,0,1,1,1,1,1,1,1,1,no,yes,15.95119764,White-European,United States,no,12.50596588,Self,18 and more,1
571
+ 570,m,0,0,0,0,0,0,0,0,0,0,no,no,16.10917192,Middle Eastern ,New Zealand,no,1.44270273,Self,18 and more,0
572
+ 571,m,0,0,0,0,0,0,0,0,0,0,no,no,25.9729348,Middle Eastern ,South Africa,no,2.00345701,Self,18 and more,0
573
+ 572,m,1,1,1,0,0,0,1,1,0,0,yes,no,57.85843038,White-European,United States,no,-0.349414994,Self,18 and more,0
574
+ 573,f,1,1,1,1,1,0,1,1,1,1,no,no,24.75130724,White-European,United States,no,10.12069538,Parent,18 and more,1
575
+ 574,f,0,0,0,1,0,0,0,1,0,1,yes,no,24.8442215,Latino,New Zealand,no,5.04311731,Relative,18 and more,0
576
+ 575,f,1,1,0,1,1,1,0,1,1,0,yes,no,23.51316509,Asian,Armenia,no,12.079312,Self,18 and more,0
577
+ 576,m,1,0,0,1,0,0,1,0,0,0,yes,no,22.4782168,Latino,United Kingdom,no,5.444609358,Self,18 and more,0
578
+ 577,f,1,1,0,0,1,1,0,1,0,1,no,no,28.39885554,White-European,United Arab Emirates,no,6.567288576,Self,18 and more,0
579
+ 578,m,0,0,0,0,0,0,0,1,0,0,no,no,19.33142065,Pasifika,India,no,5.48397178,Parent,18 and more,0
580
+ 579,m,0,0,0,1,1,0,0,0,0,0,no,no,44.13291635,?,Australia,no,8.257198393,Self,18 and more,0
581
+ 580,m,1,0,0,0,0,0,0,0,0,0,no,no,27.70375139,Asian,United Arab Emirates,no,4.534432171,Self,18 and more,0
582
+ 581,f,1,0,0,1,1,1,0,1,0,1,no,no,13.89784984,Asian,Canada,no,13.10280362,Relative,18 and more,1
583
+ 582,f,1,1,1,1,1,1,0,1,1,1,no,no,10.95228869,Latino,United States,no,9.787006383,Self,18 and more,1
584
+ 583,m,1,1,1,0,1,0,1,1,1,1,yes,no,42.15462533,Latino,Sri Lanka,no,6.42437464,Self,18 and more,1
585
+ 584,f,0,1,1,1,1,0,1,0,1,0,no,yes,21.76023807,Hispanic,United States,no,12.67898436,Self,18 and more,1
586
+ 585,m,0,0,0,0,1,0,0,1,0,0,no,no,21.17428599,?,Bolivia,no,7.435090712,Self,18 and more,0
587
+ 586,f,1,0,0,0,0,0,0,0,0,0,yes,no,27.20462751,?,United Arab Emirates,no,1.067502884,Self,18 and more,0
588
+ 587,m,1,0,0,0,1,0,0,1,0,1,no,no,23.78138492,White-European,New Zealand,no,12.28327873,Relative,18 and more,0
589
+ 588,m,1,0,0,1,1,0,0,0,0,0,no,yes,31.45372689,Black,India,no,11.5842652,Self,18 and more,0
590
+ 589,f,1,1,1,1,1,1,1,1,1,1,yes,yes,50.28178664,White-European,United States,no,12.77857904,Self,18 and more,1
591
+ 590,f,1,0,0,1,1,0,0,1,0,1,no,no,17.29337751,South Asian,United States,no,11.92760166,Self,18 and more,0
592
+ 591,m,1,1,0,0,0,0,0,1,0,1,no,no,21.35559283,Asian,Afghanistan,no,-0.404589887,Self,18 and more,0
593
+ 592,f,1,1,1,1,1,1,0,1,1,0,no,yes,27.18013388,?,United States,no,12.29586985,Parent,18 and more,1
594
+ 593,f,1,1,1,1,1,0,1,1,1,1,no,yes,29.31198078,White-European,United States,no,9.205064641,Self,18 and more,1
595
+ 594,f,1,1,1,1,1,1,1,1,1,1,no,yes,54.80676402,White-European,United States,no,13.04400888,Self,18 and more,1
596
+ 595,f,1,1,1,1,1,1,1,1,1,1,no,yes,41.75294745,White-European,Armenia,no,12.6449137,Self,18 and more,1
597
+ 596,m,0,0,0,1,1,0,0,1,1,1,no,no,54.55295512,Asian,India,no,9.500792744,Self,18 and more,1
598
+ 597,f,0,1,0,1,0,0,0,1,0,1,no,no,56.94291339,White-European,Italy,no,11.5758213,Self,18 and more,0
599
+ 598,m,0,0,0,0,0,0,0,1,0,0,yes,no,14.3808953,Latino,Brazil,no,5.134490401,?,18 and more,0
600
+ 599,f,0,0,0,1,1,0,0,1,0,1,no,no,13.89971779,White-European,Netherlands,no,7.796625171,Self,18 and more,0
601
+ 600,f,1,0,0,0,1,0,0,1,0,0,no,no,15.49096467,Asian,New Zealand,no,6.854388624,Self,18 and more,0
602
+ 601,f,1,0,0,1,0,1,0,1,1,1,yes,no,69.0322209,Latino,Canada,no,7.36682023,Self,18 and more,1
603
+ 602,m,1,0,0,0,0,0,0,1,0,0,no,no,19.73541874,White-European,United Kingdom,no,3.84324425,Self,18 and more,0
604
+ 603,f,1,0,0,0,0,1,0,1,1,0,yes,no,37.48423402,Black,New Zealand,no,9.622188908,Self,18 and more,0
605
+ 604,f,1,1,0,1,1,0,0,1,1,1,no,no,30.86535776,White-European,United Kingdom,no,11.4434956,Self,18 and more,1
606
+ 605,f,0,0,0,0,0,0,1,1,0,0,no,no,24.6096008,Middle Eastern ,Jordan,no,6.599539089,Self,18 and more,0
607
+ 606,m,1,1,1,1,1,0,1,0,1,0,yes,no,24.99099448,White-European,United Kingdom,no,7.829824786,Self,18 and more,1
608
+ 607,f,1,0,0,0,0,0,0,0,0,0,no,no,23.96639949,Asian,India,no,6.918480339,Self,18 and more,0
609
+ 608,m,0,0,0,0,0,0,0,1,0,0,no,no,42.35750256,White-European,United States,no,0.474457095,Self,18 and more,0
610
+ 609,f,1,0,0,1,1,0,0,0,0,0,no,no,25.85706958,?,Jordan,no,8.190612388,Self,18 and more,0
611
+ 610,f,0,0,0,0,0,0,0,0,0,0,no,no,26.54569019,?,India,no,0.231494445,Self,18 and more,0
612
+ 611,f,0,0,0,1,1,0,1,0,0,0,no,no,18.5060405,Asian,Sri Lanka,no,7.641468463,Self,18 and more,0
613
+ 612,m,0,0,0,0,0,0,0,1,0,0,no,no,52.05262676,?,Philippines,no,6.596557339,Self,18 and more,0
614
+ 613,m,1,0,0,0,0,0,0,0,0,0,no,no,12.23744796,?,New Zealand,no,1.219167262,Self,18 and more,0
615
+ 614,f,1,0,1,1,0,1,0,0,1,1,no,no,38.86414425,Black,Sweden,no,12.36754381,Relative,18 and more,0
616
+ 615,f,1,0,0,0,0,0,0,1,0,0,yes,no,30.52737617,Latino,United Kingdom,no,9.729908834,Self,18 and more,0
617
+ 616,f,1,0,0,0,1,0,0,1,1,0,no,no,28.98353924,Latino,AmericanSamoa,no,8.523430303,Self,18 and more,0
618
+ 617,f,1,0,1,0,0,0,0,1,0,1,no,no,18.6681171,?,Afghanistan,no,3.291574377,Self,18 and more,0
619
+ 618,f,0,0,0,1,0,0,0,0,0,0,yes,no,30.22623836,White-European,United Kingdom,no,6.773785527,Self,18 and more,0
620
+ 619,m,1,0,0,0,0,0,0,1,0,0,no,no,18.12602,?,New Zealand,no,-0.170045428,Self,18 and more,0
621
+ 620,m,1,1,1,1,1,0,1,1,1,1,yes,no,42.09629473,White-European,Netherlands,no,12.24371017,Self,18 and more,1
622
+ 621,m,0,0,0,0,0,0,0,1,0,0,no,no,24.52767093,?,United Arab Emirates,no,2.130976794,Self,18 and more,0
623
+ 622,f,0,0,0,0,1,0,1,1,0,0,no,no,24.92729016,?,Philippines,no,9.098205273,Self,18 and more,0
624
+ 623,f,1,0,0,0,0,0,0,1,1,1,no,no,23.35073121,Asian,Ukraine,no,5.783773856,Self,18 and more,0
625
+ 624,f,0,0,0,0,1,0,0,1,1,1,no,no,21.98276372,Middle Eastern ,United States,no,6.652098657,Self,18 and more,0
626
+ 625,m,0,0,0,0,0,0,0,1,0,0,no,no,37.65198552,Black,New Zealand,no,5.672398711,Self,18 and more,0
627
+ 626,m,1,0,0,0,0,0,0,1,0,0,no,no,13.44764893,Asian,Azerbaijan,no,5.544080018,Self,18 and more,0
628
+ 627,f,1,1,0,0,0,0,0,1,0,1,no,no,53.78743071,Others,Afghanistan,no,-0.539411533,Self,18 and more,0
629
+ 628,m,0,0,0,0,0,0,0,1,0,0,no,no,33.94529149,Hispanic,Italy,no,4.812774143,?,18 and more,0
630
+ 629,m,1,0,1,1,1,0,1,1,0,1,yes,yes,28.65883617,White-European,United States,no,12.93573614,Self,18 and more,0
631
+ 630,f,1,1,1,1,1,1,0,1,1,1,yes,no,18.7139055,White-European,Malaysia,no,12.78373492,Self,18 and more,1
632
+ 631,m,0,0,0,0,0,0,0,1,0,0,no,no,22.64481055,Middle Eastern ,United Arab Emirates,no,6.846036607,Self,18 and more,0
633
+ 632,m,1,0,0,0,0,0,0,1,0,0,no,no,25.19521667,Others,Jordan,no,6.845378712,Self,18 and more,0
634
+ 633,m,0,0,0,0,0,0,0,0,0,0,no,no,31.38962252,?,United Arab Emirates,no,-1.404134059,?,18 and more,0
635
+ 634,m,0,0,0,0,0,0,0,0,0,0,no,no,22.77013398,Middle Eastern ,United Arab Emirates,no,4.816072476,Self,18 and more,0
636
+ 635,f,1,0,1,1,1,1,1,1,1,1,no,yes,34.09807492,White-European,United States,no,13.32200826,Self,18 and more,1
637
+ 636,m,0,0,0,0,0,0,0,0,0,0,no,no,16.1038529,Asian,United Arab Emirates,no,7.072826956,Self,18 and more,0
638
+ 637,f,0,0,0,0,0,0,0,0,0,0,no,no,31.45293115,Asian,New Zealand,no,1.740625145,?,18 and more,0
639
+ 638,f,0,0,0,1,1,0,0,1,0,0,no,no,17.42385035,Asian,Iran,no,4.737493157,Self,18 and more,0
640
+ 639,f,1,1,1,1,0,0,0,1,0,1,no,no,15.7291792,White-European,Australia,no,9.008934607,Others,18 and more,1
641
+ 640,m,1,0,0,0,1,1,0,1,0,1,no,no,27.55458916,Middle Eastern ,United States,no,2.636108909,Self,18 and more,0
642
+ 641,m,0,0,0,0,0,0,0,0,0,0,no,no,35.31536559,Asian,United Arab Emirates,no,2.728218172,?,18 and more,0
643
+ 642,f,1,1,1,1,1,1,0,1,0,1,no,yes,19.39516203,Middle Eastern ,Malaysia,yes,10.20781396,Parent,18 and more,1
644
+ 643,f,1,1,1,0,0,0,0,1,0,0,no,no,22.24054605,White-European,Afghanistan,no,0.890902457,Self,18 and more,0
645
+ 644,f,0,0,0,0,0,0,0,0,0,0,no,no,27.00058499,Asian,Saudi Arabia,no,4.72749834,Self,18 and more,0
646
+ 645,f,1,1,1,0,0,0,1,0,1,1,no,no,29.09439056,White-European,United States,no,12.47688865,Self,18 and more,0
647
+ 646,m,0,0,0,0,0,0,0,0,0,0,no,no,25.85604329,White-European,United Arab Emirates,no,6.2152431,?,18 and more,0
648
+ 647,m,1,0,0,0,0,1,0,1,1,1,no,no,38.053128,?,United States,no,11.90920715,Self,18 and more,0
649
+ 648,f,0,0,0,0,0,0,0,0,0,0,no,no,25.15887799,Middle Eastern ,United States,no,7.502335477,?,18 and more,0
650
+ 649,m,0,0,0,0,0,0,0,1,0,0,no,no,25.05584845,Asian,New Zealand,no,7.242232292,?,18 and more,0
651
+ 650,m,0,0,0,0,0,0,0,1,0,0,yes,no,19.92111561,?,Kazakhstan,no,6.083884241,?,18 and more,0
652
+ 651,m,0,0,0,0,0,0,0,1,0,0,no,no,22.71783533,Asian,Italy,no,4.22227595,Relative,18 and more,0
653
+ 652,f,1,0,1,1,0,0,0,1,1,1,yes,yes,47.50947766,White-European,United Kingdom,no,6.74334294,Self,18 and more,0
654
+ 653,f,1,1,1,1,1,0,0,0,1,1,no,no,36.62670705,South Asian,United States,no,12.87978205,Self,18 and more,0
655
+ 654,m,1,0,0,0,0,0,0,1,0,0,no,no,21.75388979,?,United Arab Emirates,no,5.811801114,Self,18 and more,0
656
+ 655,f,0,0,0,0,0,0,0,1,0,0,no,no,30.0080822,South Asian,United States,no,9.011822317,Others,18 and more,0
657
+ 656,f,0,1,0,1,0,1,1,1,1,1,no,yes,30.89414025,White-European,United States,no,13.19516422,Parent,18 and more,1
658
+ 657,f,1,0,1,1,1,1,0,1,1,0,no,no,37.22073251,White-European,India,no,9.642188369,Self,18 and more,1
659
+ 658,m,0,1,1,1,1,1,1,1,1,1,no,no,12.64242609,Middle Eastern ,United States,no,11.68465468,Self,18 and more,1
660
+ 659,f,1,1,1,1,1,0,1,1,1,1,no,no,29.44305461,White-European,United Kingdom,no,12.8865951,Self,18 and more,0
661
+ 660,m,0,1,0,0,0,0,0,1,0,0,yes,no,16.50210964,White-European,Australia,no,5.495601387,Self,18 and more,0
662
+ 661,m,0,0,0,0,0,0,0,1,0,0,no,no,48.45204622,?,Australia,no,0.585036872,?,18 and more,0
663
+ 662,m,0,0,0,0,1,0,1,1,0,1,no,no,71.68068207,Latino,India,no,13.30013275,Self,18 and more,0
664
+ 663,f,1,1,1,1,1,1,0,1,1,1,no,yes,23.82198722,Latino,United States,no,12.858418,Self,18 and more,1
665
+ 664,f,0,0,1,0,1,0,0,1,0,0,no,no,62.61455773,White-European,India,no,11.59525701,Self,18 and more,0
666
+ 665,f,0,0,0,0,1,0,1,1,1,0,no,no,66.53320759,Latino,New Zealand,no,9.91329515,Parent,18 and more,0
667
+ 666,m,0,0,0,0,0,0,0,1,0,0,no,no,20.98300489,?,New Zealand,no,5.034762553,Self,18 and more,0
668
+ 667,m,1,0,0,0,1,0,0,1,0,1,no,no,22.81436453,?,United Arab Emirates,no,10.85828892,?,18 and more,0
669
+ 668,m,0,0,0,1,1,0,0,1,1,1,no,no,28.38670182,?,Argentina,no,8.033251223,Self,18 and more,0
670
+ 669,f,1,0,1,1,1,0,0,1,1,1,yes,yes,20.53986415,White-European,United Arab Emirates,no,8.54195461,Self,18 and more,1
671
+ 670,f,0,0,1,1,0,1,0,1,1,1,no,no,22.15781669,White-European,Canada,no,11.24167701,Self,18 and more,1
672
+ 671,m,0,1,0,0,0,0,0,1,0,1,no,no,12.95082394,Middle Eastern ,India,no,6.074312114,Self,18 and more,0
673
+ 672,f,1,0,0,1,1,0,0,1,0,0,no,no,27.68259645,White-European,India,no,7.314045347,Self,18 and more,0
674
+ 673,f,0,0,0,0,0,0,0,0,0,0,no,no,28.61497378,Asian,India,no,2.819953175,Relative,18 and more,0
675
+ 674,m,1,0,0,0,0,0,0,0,0,0,no,no,13.14904621,Black,United Arab Emirates,no,6.587371377,Self,18 and more,0
676
+ 675,f,1,0,0,1,0,0,0,1,0,0,yes,no,16.84333863,?,Canada,no,2.604970148,Self,18 and more,0
677
+ 676,m,1,0,0,0,1,0,1,0,0,1,yes,no,29.43706753,Asian,France,no,10.12164295,Self,18 and more,0
678
+ 677,f,1,0,1,1,1,0,1,1,0,1,no,no,24.52725575,White-European,Brazil,no,12.70987011,Self,18 and more,0
679
+ 678,f,1,1,1,1,1,1,0,1,1,1,no,no,18.05636448,Asian,Australia,no,13.12453857,Self,18 and more,1
680
+ 679,m,0,0,0,0,0,0,0,1,0,0,no,no,25.60377858,Asian,Jordan,no,1.653584599,?,18 and more,0
681
+ 680,m,0,0,0,1,1,0,0,1,1,0,no,no,46.74226968,White-European,Sri Lanka,no,6.496949408,Self,18 and more,0
682
+ 681,m,0,0,0,0,0,0,0,1,0,0,no,no,18.84460222,Middle Eastern ,New Zealand,no,-1.371819245,Self,18 and more,0
683
+ 682,f,0,1,0,0,1,0,0,0,0,0,yes,no,31.33228909,White-European,India,no,2.863281284,Self,18 and more,0
684
+ 683,m,1,0,0,1,1,1,1,1,1,1,yes,yes,21.75953085,Asian,United States,no,10.67377402,Self,18 and more,1
685
+ 684,f,1,0,1,1,0,1,1,0,1,1,yes,no,28.04131476,Latino,India,no,12.58481841,Self,18 and more,1
686
+ 685,m,1,1,0,1,1,1,1,1,1,1,yes,yes,52.33927013,White-European,United States,no,12.23598858,Self,18 and more,1
687
+ 686,m,1,0,0,0,0,0,0,1,0,0,no,no,29.12475515,Asian,Australia,no,5.865060722,Relative,18 and more,0
688
+ 687,m,1,1,0,1,1,0,1,0,0,0,yes,no,17.85655211,White-European,United States,no,5.667709899,Self,18 and more,0
689
+ 688,m,1,0,1,1,1,0,1,1,1,0,no,yes,22.1894618,White-European,New Zealand,no,12.69158468,Self,18 and more,0
690
+ 689,f,0,0,0,0,0,0,0,1,0,0,no,no,23.99379689,?,New Zealand,no,10.37649024,Self,18 and more,0
691
+ 690,f,1,1,1,1,1,0,1,1,1,1,yes,no,24.45063324,White-European,United Kingdom,no,11.85101145,Self,18 and more,1
692
+ 691,f,0,0,0,0,0,0,0,1,0,0,no,no,28.54050329,Middle Eastern ,United Arab Emirates,no,-0.424699406,Self,18 and more,0
693
+ 692,f,1,0,1,0,0,0,0,1,0,0,yes,no,24.58667973,Asian,United Kingdom,no,8.043349911,Self,18 and more,0
694
+ 693,m,0,0,0,0,0,0,0,1,0,0,no,no,28.1411368,Asian,United Arab Emirates,no,5.603798965,Self,18 and more,0
695
+ 694,m,1,0,0,0,0,0,0,1,0,0,no,no,18.3372629,Middle Eastern ,United Arab Emirates,no,3.550727828,Self,18 and more,0
696
+ 695,m,0,0,0,0,0,0,0,1,0,0,no,no,28.53744157,?,United Arab Emirates,no,0.88459756,Self,18 and more,0
697
+ 696,m,0,0,0,0,0,0,0,0,0,0,no,no,17.34310145,Asian,New Zealand,no,6.070682947,?,18 and more,0
698
+ 697,f,1,0,0,0,0,0,0,1,0,0,no,no,19.0113239,Asian,United States,no,11.33068753,Self,18 and more,0
699
+ 698,f,1,0,0,1,0,0,0,1,0,1,no,no,12.03510973,Middle Eastern ,United States,no,8.126190489,Self,18 and more,0
700
+ 699,f,1,1,1,1,1,1,1,1,1,1,yes,yes,32.58726065,White-European,United States,no,12.66673146,Self,18 and more,1
701
+ 700,m,0,1,0,1,1,0,0,1,0,0,no,no,23.68543099,Black,Bahamas,no,8.232475864,?,18 and more,0
702
+ 701,f,1,1,0,1,1,0,0,1,1,1,yes,no,41.19614552,White-European,Mexico,no,8.176131023,Self,18 and more,0
703
+ 702,m,1,1,0,1,1,1,0,1,0,1,no,no,35.67135635,Asian,India,no,11.8484224,Self,18 and more,1
704
+ 703,m,1,0,1,1,1,1,0,1,1,1,yes,yes,17.0144967,White-European,United Kingdom,no,12.89314417,Self,18 and more,1
705
+ 704,f,1,1,1,1,1,1,1,1,1,1,no,yes,37.27590789,White-European,Australia,no,12.86200491,Self,18 and more,1
706
+ 705,m,0,0,0,0,0,0,0,0,0,0,no,no,23.95534317,Asian,Nicaragua,no,3.88418964,?,18 and more,0
707
+ 706,m,1,1,1,1,1,1,1,1,1,1,yes,yes,19.74274144,White-European,United States,no,9.590124513,Self,18 and more,1
708
+ 707,f,0,0,0,0,0,0,0,1,0,0,no,no,21.18868502,Asian,United Arab Emirates,no,3.469013965,Self,18 and more,0
709
+ 708,m,1,0,0,0,0,0,0,1,0,0,yes,no,25.11728489,White-European,New Zealand,no,3.012778809,Self,18 and more,0
710
+ 709,m,0,1,0,0,0,0,0,0,0,0,yes,no,39.92918019,Others,United States,no,7.266477967,Self,18 and more,0
711
+ 710,m,0,0,0,0,0,0,0,0,0,1,no,no,13.06948226,?,United States,no,5.933911907,Self,18 and more,0
712
+ 711,m,1,0,0,0,0,0,0,1,1,1,no,no,34.2908246,Middle Eastern ,Viet Nam,no,12.52690699,Self,18 and more,0
713
+ 712,f,0,1,0,0,0,0,0,1,0,0,no,no,22.28181212,Middle Eastern ,New Zealand,no,5.941500175,Self,18 and more,0
714
+ 713,m,1,0,1,1,1,0,1,1,0,1,yes,no,54.78051233,?,United Kingdom,no,11.28121048,Self,18 and more,1
715
+ 714,m,1,0,1,1,1,1,0,1,1,1,no,no,20.49104374,Asian,United States,no,13.06573621,Self,18 and more,1
716
+ 715,m,1,0,0,0,0,0,0,1,0,0,no,no,22.61154807,Asian,Afghanistan,no,2.971121778,?,18 and more,0
717
+ 716,f,0,0,0,0,0,0,0,0,0,1,yes,no,24.00236983,Others,New Zealand,no,1.900813399,Self,18 and more,1
718
+ 717,f,1,0,1,1,1,1,1,0,1,1,no,no,24.91819746,Black,United Kingdom,yes,5.940763009,Parent,18 and more,1
719
+ 718,f,1,1,0,0,1,0,0,0,0,0,no,no,45.03945117,Asian,France,no,6.382275401,Parent,18 and more,0
720
+ 719,f,1,0,1,1,1,1,1,0,1,1,yes,no,11.06017591,White-European,Australia,no,12.08646347,Self,18 and more,1
721
+ 720,f,0,0,0,1,0,0,1,1,0,0,no,no,63.23366513,White-European,Netherlands,yes,6.661191713,Self,18 and more,0
722
+ 721,f,0,0,0,0,0,0,0,0,0,0,no,no,18.90427553,?,India,no,5.214310194,Self,18 and more,0
723
+ 722,f,0,1,0,0,0,0,0,0,0,0,no,no,35.45799034,Middle Eastern ,Niger,no,0.267053097,Health care professional,18 and more,0
724
+ 723,m,1,1,1,1,1,1,0,1,1,1,yes,no,62.02633694,White-European,United States,no,12.69487778,Self,18 and more,1
725
+ 724,m,0,0,1,1,1,0,0,1,0,1,no,no,13.38282021,?,Bolivia,no,8.836612609,?,18 and more,0
726
+ 725,f,1,1,0,1,1,1,1,1,1,1,no,no,23.2418793,White-European,Australia,no,13.18758905,Self,18 and more,1
727
+ 726,f,0,0,0,0,0,0,0,1,0,0,no,no,29.82519294,?,United States,no,6.610906059,Self,18 and more,0
728
+ 727,m,1,1,0,1,1,0,1,1,1,1,no,no,11.35116102,White-European,Pakistan,no,9.345115604,Self,18 and more,1
729
+ 728,f,1,0,0,0,0,0,0,0,0,0,no,no,28.33023531,Black,Philippines,no,2.031080732,Self,18 and more,0
730
+ 729,f,1,1,0,0,0,0,0,0,0,0,no,no,12.94801424,South Asian,Ukraine,no,1.883014214,Self,18 and more,0
731
+ 730,f,1,0,1,1,1,0,0,0,1,1,no,no,17.91973945,Black,New Zealand,no,9.886209523,Self,18 and more,1
732
+ 731,f,1,0,0,0,0,0,0,1,0,0,no,no,22.88957212,?,India,no,0.407256609,Parent,18 and more,0
733
+ 732,m,1,0,0,1,1,0,1,1,1,0,no,yes,13.1545696,Asian,United States,no,1.990277974,Self,18 and more,1
734
+ 733,m,1,1,1,1,1,0,1,1,1,1,no,yes,24.2634694,Others,Bolivia,no,12.21641163,Self,18 and more,1
735
+ 734,m,1,1,1,1,1,0,1,1,0,1,yes,no,46.57007587,Latino,Sri Lanka,no,12.99063558,Self,18 and more,1
736
+ 735,m,1,1,1,1,1,1,1,1,1,1,no,yes,17.90321284,White-European,United States,no,10.50155882,Self,18 and more,1
737
+ 736,m,0,0,0,1,1,0,0,1,0,0,no,no,21.75123467,Middle Eastern ,Canada,no,6.764455797,Self,18 and more,0
738
+ 737,m,0,0,0,0,1,1,0,1,0,1,no,no,20.90950447,White-European,United States,no,0.373984541,Self,18 and more,0
739
+ 738,m,0,0,0,0,0,0,0,0,0,0,no,no,18.99191402,Middle Eastern ,India,no,6.677639256,Self,18 and more,0
740
+ 739,m,0,0,0,0,0,0,0,1,0,0,no,no,50.53524958,?,India,no,2.569904621,Relative,18 and more,0
741
+ 740,m,1,0,1,1,1,0,0,1,1,0,no,no,34.88603695,Asian,United States,no,11.96038573,Self,18 and more,1
742
+ 741,m,1,0,0,0,0,0,0,1,0,0,no,no,18.4379935,Asian,Jordan,no,4.026584312,?,18 and more,0
743
+ 742,f,1,0,0,0,0,0,0,0,0,1,no,no,28.46828198,White-European,United Arab Emirates,no,8.837014057,Self,18 and more,0
744
+ 743,f,0,0,1,0,0,0,0,1,0,0,yes,no,20.4634476,Latino,United Arab Emirates,no,8.434125874,Self,18 and more,0
745
+ 744,f,1,0,1,1,1,0,0,1,0,1,no,no,17.2001964,Middle Eastern ,Italy,yes,9.929483959,Self,18 and more,0
746
+ 745,f,1,0,1,0,0,0,0,1,1,1,yes,no,18.4241769,White-European,Iran,no,6.465976443,Self,18 and more,0
747
+ 746,f,1,1,1,1,1,1,0,1,1,1,yes,no,21.0231266,White-European,United Kingdom,no,9.472175772,Self,18 and more,1
748
+ 747,m,1,0,0,0,1,0,0,1,0,1,yes,no,27.57733856,South Asian,Russia,no,5.716146112,Self,18 and more,0
749
+ 748,m,1,0,0,0,0,0,0,1,0,0,no,no,28.42463843,White-European,Russia,no,9.274546745,Self,18 and more,0
750
+ 749,f,0,0,1,1,0,1,0,1,0,1,no,no,44.10109235,White-European,New Zealand,no,3.434722319,Self,18 and more,0
751
+ 750,m,0,0,1,1,1,1,1,1,0,0,yes,no,28.95224942,White-European,United States,no,9.885100778,Self,18 and more,0
752
+ 751,f,0,0,0,0,0,0,0,1,0,0,yes,no,26.86995049,Asian,United States,no,4.783133275,Relative,18 and more,0
753
+ 752,m,0,0,0,0,0,0,0,0,0,0,no,no,19.74198448,Middle Eastern ,Germany,yes,6.438968444,Health care professional,18 and more,0
754
+ 753,m,1,0,0,1,0,0,0,1,0,0,no,no,23.43507261,Asian,Angola,no,7.177985393,Self,18 and more,0
755
+ 754,m,1,0,0,1,1,0,0,1,0,0,yes,no,30.67846275,?,Spain,no,6.153399306,Self,18 and more,0
756
+ 755,f,1,1,1,1,1,1,1,1,1,1,no,no,23.89542479,White-European,New Zealand,no,12.95415229,Self,18 and more,0
757
+ 756,m,1,1,0,0,1,1,0,1,1,1,yes,no,14.45454475,Asian,United States,no,12.00896778,Self,18 and more,1
758
+ 757,f,1,1,1,1,1,1,0,1,1,1,yes,yes,62.92074643,White-European,Australia,no,13.24206967,Self,18 and more,1
759
+ 758,m,1,1,0,0,0,0,0,1,0,0,no,no,18.34957017,Asian,Austria,no,4.08931523,Self,18 and more,0
760
+ 759,m,1,0,1,0,0,0,1,1,1,0,no,no,29.277243,?,Kazakhstan,no,3.690942379,Self,18 and more,0
761
+ 760,m,1,0,0,0,0,0,0,1,0,0,no,no,16.28524309,Middle Eastern ,Australia,no,-1.798714718,Self,18 and more,0
762
+ 761,f,0,0,0,0,0,0,0,1,0,0,no,no,21.6019814,Hispanic,Sri Lanka,no,1.601867922,?,18 and more,0
763
+ 762,f,1,1,1,1,0,0,0,1,1,0,no,no,19.97847816,White-European,United States,no,6.672158756,Self,18 and more,0
764
+ 763,m,1,0,0,0,0,0,0,0,0,0,no,yes,29.27161357,Middle Eastern ,New Zealand,no,0.502550325,Self,18 and more,0
765
+ 764,m,1,1,1,0,1,0,0,0,0,0,no,no,43.62625747,Black,United States,no,7.72826799,Relative,18 and more,0
766
+ 765,f,0,1,0,1,1,0,0,1,0,1,no,yes,28.10136823,White-European,New Zealand,yes,11.48566321,Self,18 and more,1
767
+ 766,m,0,1,0,0,0,0,0,1,0,0,yes,no,20.98186716,Middle Eastern ,United States,no,-0.853256785,Self,18 and more,0
768
+ 767,f,1,0,0,1,0,0,0,1,0,0,no,no,15.09052497,Asian,Jordan,no,7.536892962,Self,18 and more,0
769
+ 768,m,1,0,0,0,0,0,0,1,0,0,no,no,19.4801396,?,United Arab Emirates,no,0.59078224,Self,18 and more,0
770
+ 769,f,0,0,1,0,0,0,0,1,1,1,no,yes,30.70537622,Middle Eastern ,United Arab Emirates,no,7.445830332,Self,18 and more,1
771
+ 770,m,1,1,1,1,1,1,0,1,1,0,no,no,25.71545925,Others,Afghanistan,no,6.895935384,Self,18 and more,0
772
+ 771,m,1,1,0,1,1,0,0,1,0,0,no,no,53.89137595,White-European,Philippines,no,11.14816099,Self,18 and more,0
773
+ 772,f,0,0,0,0,0,0,1,1,0,0,yes,no,19.13036361,Middle Eastern ,United States,no,7.54687508,Self,18 and more,0
774
+ 773,f,1,0,1,1,1,1,1,1,1,1,yes,yes,51.06141566,White-European,United States,no,9.685235692,Self,18 and more,1
775
+ 774,f,0,0,0,0,1,0,0,1,0,0,no,no,27.32150965,?,United Kingdom,no,3.090932348,Self,18 and more,0
776
+ 775,m,1,0,1,1,1,0,1,1,0,1,no,no,55.27876787,White-European,Spain,no,11.9122956,Self,18 and more,0
777
+ 776,m,1,0,0,1,1,0,1,0,1,0,no,no,44.87586807,White-European,Austria,no,5.218856312,Relative,18 and more,0
778
+ 777,m,1,0,0,0,0,1,1,1,0,1,no,no,54.09464439,South Asian,Canada,no,6.12019472,Self,18 and more,0
779
+ 778,f,1,1,1,1,1,1,1,1,1,1,no,yes,27.79945741,others,France,no,13.21578899,Relative,18 and more,1
780
+ 779,f,1,1,1,1,1,1,1,1,1,1,no,no,53.3231657,White-European,Australia,no,13.30593843,Self,18 and more,1
781
+ 780,f,0,0,0,0,0,0,1,1,0,1,yes,no,22.42243059,White-European,United Kingdom,no,3.751886987,Relative,18 and more,0
782
+ 781,f,1,1,1,1,1,1,1,1,1,1,no,yes,18.00918051,White-European,United Kingdom,no,13.34315242,Self,18 and more,1
783
+ 782,m,0,0,0,0,1,0,0,0,0,0,no,no,32.16281477,White-European,Afghanistan,no,8.920739758,Relative,18 and more,0
784
+ 783,f,0,0,0,0,0,0,0,0,0,0,no,no,17.89826171,?,United Arab Emirates,no,3.136957044,Self,18 and more,0
785
+ 784,m,0,0,0,0,0,0,0,0,0,0,no,no,16.69477428,Middle Eastern ,New Zealand,no,2.845171537,Self,18 and more,0
786
+ 785,m,1,0,0,0,0,0,0,1,0,0,no,no,14.83218125,South Asian,United States,no,7.011832026,Self,18 and more,0
787
+ 786,f,1,0,1,1,0,0,0,1,0,1,no,no,15.12771801,White-European,Australia,no,3.342516258,Self,18 and more,0
788
+ 787,m,1,1,1,1,1,0,1,1,1,1,yes,yes,38.52697981,White-European,United States,no,12.77838613,Self,18 and more,1
789
+ 788,f,0,0,0,0,0,0,0,1,0,0,no,no,31.09996355,?,India,no,1.901898986,?,18 and more,0
790
+ 789,m,1,1,0,1,1,0,0,1,1,1,no,no,58.41167865,Middle Eastern ,Jordan,no,-0.308400086,Self,18 and more,0
791
+ 790,m,0,0,0,0,0,0,0,0,0,0,no,no,59.60787077,?,Russia,no,4.658414883,Self,18 and more,0
792
+ 791,m,0,0,0,0,0,0,0,0,0,1,no,no,36.82751862,Asian,United Arab Emirates,no,2.287008829,?,18 and more,0
793
+ 792,f,0,0,0,0,0,0,0,1,0,0,no,no,17.82050033,Black,United Arab Emirates,no,1.105997498,Self,18 and more,0
794
+ 793,m,1,0,0,0,1,0,0,1,0,1,no,no,21.62956024,?,Mexico,no,7.003726856,Self,18 and more,0
795
+ 794,f,1,0,0,0,0,0,1,0,0,0,no,no,16.30397208,Hispanic,Brazil,no,7.728627902,Self,18 and more,0
796
+ 795,m,0,0,1,1,1,1,1,1,1,0,no,no,24.36141607,Pasifika,Viet Nam,no,11.28052229,Self,18 and more,0
797
+ 796,f,1,1,1,1,1,1,1,1,1,1,no,yes,42.08490685,White-European,United States,no,13.3908679,Self,18 and more,1
798
+ 797,f,1,1,0,0,1,0,0,0,1,1,no,no,17.66929077,Asian,New Zealand,no,9.454200875,Self,18 and more,0
799
+ 798,m,0,0,0,0,0,0,1,0,1,1,yes,no,18.24255728,White-European,Jordan,no,6.80550928,Self,18 and more,1
800
+ 799,f,1,1,1,1,1,1,0,1,1,1,no,yes,19.24147315,Middle Eastern ,United States,no,3.682732169,Relative,18 and more,0
801
+ 800,f,1,0,0,1,1,0,0,1,1,1,no,no,32.17009804,Asian,New Zealand,no,12.06016768,Self,18 and more,0