Senior Data Scientist, MassMutual
Lecturer, UC Berkeley MIDS
--
PhD Applied Math, Computational Story Lab, UVM
MS Applied Math, UVM
BS Math, Virginia Tech
visWidth = width - 160
dataFilteredGender = data.filter(d => d.Gender === selectedGender)
dataFilteredGender2 = data.filter(d => d.Gender === selectedGender2)
processedData = {
// Filter for selected year and age
const yearData = dataFilteredGender.filter(d => d.Year === selectedYear && d.Age >= currentAge);
// Calculate survival probabilities
let survivalProb = 1.0;
const probabilities = [];
yearData.forEach(row => {
probabilities.push({
Age: row.Age,
Probability: survivalProb,
Type: "Survival Probability"
});
survivalProb *= (1 - row['q(x)']);
});
// Calculate death probability density
const deathProbs = probabilities.map(d => d.Probability);
const ages = probabilities.map(d => d.Age);
const density = gradient(deathProbs.map(p => -p), ages);
const deathProbabilities = ages.map((age, i) => ({
Age: age,
Probability: density[i],
Type: "Death Probability Density 1"
}));
const yearData2 = dataFilteredGender2.filter(d => d.Year === selectedYear2 && d.Age >= currentAge2);
// Calculate survival probabilities
survivalProb = 1.0;
const probabilities2 = [];
yearData2.forEach(row => {
probabilities2.push({
Age: row.Age,
Probability: survivalProb,
Type: "Survival Probability"
});
survivalProb *= (1 - row['q(x)']);
});
// Calculate death probability density
const deathProbs2 = probabilities2.map(d => d.Probability);
const ages2 = probabilities2.map(d => d.Age);
const density2 = gradient(deathProbs2.map(p => -p), ages2);
const deathProbabilities2 = ages2.map((age, i) => ({
Age: age,
Probability: density2[i],
Type: "Death Probability Density 2"
}));
// Combine both sets of data
return [...deathProbabilities, ...deathProbabilities2];
}
processedDataSurvival = {
// Filter for selected year and age
const yearData = dataFilteredGender.filter(d => d.Year === selectedYear && d.Age >= currentAge);
// Calculate survival probabilities
let survivalProb = 1.0;
const probabilities = [];
yearData.forEach(row => {
probabilities.push({
Age: row.Age,
Probability: survivalProb,
Type: "Survival Probability 1"
});
survivalProb *= (1 - row['q(x)']);
});
const yearData2 = dataFilteredGender2.filter(d => d.Year === selectedYear2 && d.Age >= currentAge2);
// Calculate survival probabilities
survivalProb = 1.0;
const probabilities2 = [];
yearData2.forEach(row => {
probabilities2.push({
Age: row.Age,
Probability: survivalProb,
Type: "Survival Probability 2"
});
survivalProb *= (1 - row['q(x)']);
});
// Combine both sets of data
return [...probabilities, ...probabilities2];
}
// Function to calculate gradient
function gradient(values, domain) {
// Calculate central differences
const deltas = Array(values.length);
// Forward difference for first point
deltas[0] = (values[1] - values[0]) / (domain[1] - domain[0]);
// Central differences for middle points
for (let i = 1; i < values.length - 1; i++) {
deltas[i] = (values[i + 1] - values[i - 1]) / (domain[i + 1] - domain[i - 1]);
}
// Backward difference for last point
const last = values.length - 1;
deltas[last] = (values[last] - values[last - 1]) / (domain[last] - domain[last - 1]);
return deltas;
}
genders = {
return [...new Set(data.map(d => d.Gender))].sort();
}
years = {
return [...new Set(dataFilteredGender.map(d => d.Year))].sort();
}
visWidthMin = Math.max(visWidth, 500)
spec = {
const baseSpec = {
"width": visWidthMin,
"height": .4*visWidthMin,
"data": {"values": processedData},
"encoding": {
"x": {"field": "Age", "type": "quantitative", "title": "Age"}
},
"config": {
"legend": {"orient": "top", "layout": {"top": {"anchor": "middle"}}, "title": null}
},
"layer": [
{
// Death probability density
"mark": {"type": "line"},
"encoding": {
"y": {
"field": "Probability",
"type": "quantitative",
"title": "Death Probability Density",
"axis": {"format": "%"},
"scale": {"zero": true}
},
"color": {"field": "Type", "type": "nominal"},
"tooltip": [
{"field": "Age", "type": "quantitative", "title": "Age"},
{"field": "Probability", "type": "quantitative", "title": "Probability", "format": ".2%"},
{"field": "Type", "type": "nominal"}
]
}
},
],
"resolve": {
"scale": {
"y": "independent" // Make y-scales independent
}
}
};
return baseSpec;
}
spec2 = {
const baseSpec = {
"width": visWidthMin,
"height": .4*visWidthMin,
"data": {"values": processedDataSurvival},
"encoding": {
"x": {"field": "Age", "type": "quantitative", "title": "Age"}
},
"config": {
"legend": {"orient": "top", "layout": {"top": {"anchor": "middle"}}, "title": null}
},
"layer": [
{
// Survival probability line
"mark": "line",
"encoding": {
"y": {
"field": "Probability",
"type": "quantitative",
"title": "Survival Probability",
"axis": {"format": "%"}
},
"color": {
"field": "Type",
"type": "nominal",
},
"tooltip": [
{"field": "Age", "type": "quantitative", "title": "Age"},
{"field": "Probability", "type": "quantitative", "title": "Probability", "format": ".1%"},
{"field": "Type", "type": "nominal"}
]
}
},
],
"resolve": {
"scale": {
"y": "independent" // Make y-scales independent
}
}
};
return baseSpec;
}
data = FileAttachment("all.json").json()
embed = require("vega-embed@6")
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