Actuarial Table Calculator

Actuarial Table Calculator – Calculate Life Expectancy and Probabilities :root { –primary-color: #004a99; –success-color: #28a745; –background-color: #f8f9fa; –text-color: #333; –border-color: #ddd; –card-shadow: 0 4px 8px rgba(0,0,0,0.1); –input-border-radius: 5px; –button-border-radius: 5px; } body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; background-color: var(–background-color); color: var(–text-color); line-height: 1.6; margin: 0; padding: 20px; display: flex; justify-content: center; } .main-container { width: 100%; max-width: 1100px; background-color: #fff; padding: 30px; border-radius: 8px; box-shadow: var(–card-shadow); margin-top: 20px; } header { text-align: center; margin-bottom: 30px; padding-bottom: 20px; border-bottom: 1px solid var(–border-color); } h1 { color: var(–primary-color); margin-bottom: 10px; } .calculator-section { margin-bottom: 40px; padding: 30px; background-color: var(–background-color); border-radius: 8px; box-shadow: inset 0 2px 4px rgba(0,0,0,0.05); } .calculator-section h2 { color: var(–primary-color); text-align: center; margin-bottom: 20px; } .loan-calc-container { display: flex; flex-direction: column; gap: 20px; } .input-group { display: flex; flex-direction: column; gap: 5px; } .input-group label { font-weight: bold; color: var(–primary-color); } .input-group input[type="number"], .input-group select { padding: 12px 15px; border: 1px solid var(–border-color); border-radius: var(–input-border-radius); font-size: 1rem; transition: border-color 0.3s ease; } .input-group input[type="number"]:focus, .input-group select:focus { border-color: var(–primary-color); outline: none; } .input-group small { color: #6c757d; font-size: 0.85em; } .error-message { color: #dc3545; font-size: 0.85em; margin-top: 5px; display: none; /* Hidden by default */ } .error-message.visible { display: block; } .button-group { display: flex; justify-content: center; gap: 15px; margin-top: 25px; flex-wrap: wrap; } button { padding: 12px 25px; border: none; border-radius: var(–button-border-radius); cursor: pointer; font-size: 1rem; font-weight: bold; transition: background-color 0.3s ease, transform 0.2s ease; color: white; } button.primary { background-color: var(–primary-color); } button.primary:hover { background-color: #003b7a; transform: translateY(-2px); } button.success { background-color: var(–success-color); } button.success:hover { background-color: #218838; transform: translateY(-2px); } button.secondary { background-color: #6c757d; } button.secondary:hover { background-color: #5a6268; transform: translateY(-2px); } #results-container { margin-top: 30px; padding: 25px; background-color: var(–primary-color); color: white; border-radius: 8px; text-align: center; box-shadow: 0 2px 5px rgba(0,0,0,0.1); } #results-container h3 { margin-top: 0; color: white; font-size: 1.6em; } #main-result { font-size: 2.5em; font-weight: bold; margin-bottom: 15px; display: block; } .intermediate-results { display: flex; justify-content: space-around; flex-wrap: wrap; gap: 20px; margin-top: 20px; padding-top: 15px; border-top: 1px solid rgba(255,255,255,0.3); } .intermediate-results div { text-align: center; } .intermediate-results span { display: block; font-size: 1.8em; font-weight: bold; } .formula-explanation { margin-top: 15px; font-size: 0.9em; opacity: 0.8; } .chart-container, .table-container { margin-top: 40px; padding: 30px; background-color: #fff; border-radius: 8px; box-shadow: var(–card-shadow); } .chart-container h3, .table-container h3 { color: var(–primary-color); text-align: center; margin-bottom: 20px; } canvas { display: block; margin: 20px auto; max-width: 100%; height: auto !important; /* Override default canvas sizing */ } table { width: 100%; border-collapse: collapse; margin-top: 20px; } th, td { border: 1px solid var(–border-color); padding: 12px 15px; text-align: right; } th { background-color: var(–primary-color); color: white; font-weight: bold; text-align: center; } tr:nth-child(even) { background-color: #f2f2f2; } .article-content { margin-top: 50px; padding-top: 30px; border-top: 1px solid var(–border-color); } .article-content h2, .article-content h3 { color: var(–primary-color); margin-top: 30px; margin-bottom: 15px; } .article-content h2 { font-size: 2em; border-bottom: 2px solid var(–primary-color); padding-bottom: 5px; } .article-content h3 { font-size: 1.5em; } .article-content p, .article-content ul, .article-content ol { margin-bottom: 15px; } .article-content ul, .article-content ol { padding-left: 25px; } .article-content li { margin-bottom: 8px; } .article-content strong { color: var(–primary-color); } .faq-item { margin-bottom: 20px; padding: 15px; background-color: #eef; border-left: 5px solid var(–primary-color); border-radius: 5px; } .faq-item h4 { margin-top: 0; margin-bottom: 10px; color: var(–primary-color); font-size: 1.2em; } .faq-item p { margin-bottom: 0; } .internal-links { margin-top: 30px; padding: 20px; background-color: var(–background-color); border-radius: 8px; } .internal-links ul { list-style: none; padding: 0; } .internal-links li { margin-bottom: 10px; } .internal-links a { color: var(–primary-color); text-decoration: none; font-weight: bold; } .internal-links a:hover { text-decoration: underline; } .internal-links p { font-style: italic; color: #6c757d; font-size: 0.9em; margin-top: 5px; } /* Responsive adjustments */ @media (max-width: 768px) { .main-container { padding: 20px; } h1 { font-size: 1.8em; } button { width: 100%; padding: 12px 15px; } .button-group { flex-direction: column; align-items: center; } .intermediate-results { flex-direction: column; gap: 15px; } .intermediate-results div { padding-bottom: 10px; } #main-result { font-size: 2em; } }

Actuarial Table Calculator

Estimate life expectancy, survival rates, and mortality probabilities based on age and gender.

Actuarial Probability Calculator

Enter your current age in whole years.
Male Female Select your gender for more accurate probabilities.
US 2019 Period Life Table (Example) Custom (Advanced) Choose a standard table or define your own probabilities.

Your Actuarial Projections

Calculations based on selected actuarial table data.
Survival Probability
Mortality Probability
Remaining Life Expectancy

Life Expectancy vs. Age

Projected life expectancy at different ages based on selected gender and table.

Actuarial Data Table (Sample for Selected Age)

Age Death Probability (qx) Survival Probability (px) Life Expectancy (ex)
Key actuarial metrics for a range of ages.

What is an Actuarial Table?

An **actuarial table calculator** is a tool designed to help individuals and professionals understand the probabilities associated with human life, primarily focusing on mortality and life expectancy. At its core, an actuarial table (also known as a life table or mortality table) is a statistical compilation that lists the number of deaths, deaths per 100,000 people, survival rates, and life expectancy for individuals at each age. These tables are fundamental to the insurance industry, pension planning, and public health research.

Who should use it? Anyone involved in financial planning, life insurance underwriting, actuarial science, demography, or even individuals curious about their own potential lifespan will find an **actuarial table calculator** invaluable. It demystifies complex actuarial data, making it accessible for decision-making regarding retirement savings, insurance coverage, and long-term financial goals.

Common Misconceptions: A frequent misunderstanding is that actuarial tables predict an individual's exact lifespan. This is incorrect. Actuarial tables provide probabilities and averages for large populations, not definitive predictions for a single person. Individual lifespans are influenced by a multitude of factors beyond statistical averages, including lifestyle, genetics, and unforeseen events. Another misconception is that actuarial tables are static; they are regularly updated to reflect changes in mortality trends, medical advancements, and societal factors.

Actuarial Table Calculator Formula and Mathematical Explanation

The calculations performed by an **actuarial table calculator** are derived directly from the data presented in standard actuarial tables, which are themselves built upon complex statistical models and extensive population data. While the calculator doesn't compute the entire table from scratch, it interpolates and extracts key figures based on user inputs.

The core components derived from actuarial tables include:

  • Mortality Probability (qₓ): This is the probability that an individual aged 'x' will die before reaching age 'x+1'. It's a fundamental metric found directly in the table.
  • Survival Probability (pₓ): This is the probability that an individual aged 'x' will survive to age 'x+1'. It's the complement of mortality probability: pₓ = 1 - qₓ.
  • Life Expectancy (eₓ): This represents the average number of additional years an individual aged 'x' is expected to live. It's calculated by summing the probabilities of surviving each future year, weighted by the number of years lived in that interval. The exact formula for life expectancy at age x (eₓ) is: eₓ = Σᵢ₀ (₁₀₀ * ⁿPₓ) / ₁₀₀ * ₐqₓ Where:
    • ⁿPₓ is the probability that a person aged x will survive for n years.
    • ⁿqₓ is the probability that a person aged x will die within n years.
    • The sum is taken over all future years until the last possible age.
    For practical calculator use, often the remaining life expectancy is presented, derived from the table.

Variables Table

Variable Meaning Unit Typical Range
x Current Age Years 0+
qₓ Probability of Dying within the next year Proportion (0 to 1) 0.0001 to 0.15 (varies greatly with age)
pₓ Probability of Surviving the next year Proportion (0 to 1) 0.85 to 0.9999 (varies greatly with age)
eₓ Life Expectancy at age x Years 0 to 90+ (decreases with age)
Gender Biological Sex Category Male, Female

Practical Examples (Real-World Use Cases)

Example 1: Retirement Planning for Sarah

Scenario: Sarah is a 45-year-old female. She's reviewing her retirement savings and wants to understand the projected timeline for her finances. She uses the **actuarial table calculator** with the US 2019 Period Life Table.

Inputs:

  • Current Age: 45
  • Gender: Female
  • Actuarial Table: US 2019 Period Life Table

Outputs (from calculator):

  • Main Result (Remaining Life Expectancy): Approximately 37.5 years
  • Survival Probability (to age 46): ~0.996
  • Mortality Probability (at age 45): ~0.004
  • Projected Retirement Age (e.g., if retiring at 65): She might expect to live for ~17.5 years in retirement.

Interpretation: This data suggests Sarah should plan her retirement finances to potentially cover nearly four decades, with a significant portion likely falling within her retirement years. This emphasizes the need for robust long-term savings and investment strategies.

Example 2: Life Insurance Needs for John

Scenario: John is a 30-year-old male with a young family. He's evaluating how much life insurance coverage he might need. He uses the **actuarial table calculator**.

Inputs:

  • Current Age: 30
  • Gender: Male
  • Actuarial Table: US 2019 Period Life Table

Outputs (from calculator):

  • Main Result (Remaining Life Expectancy): Approximately 47.2 years
  • Survival Probability (to age 31): ~0.997
  • Mortality Probability (at age 30): ~0.003
  • Probability of reaching age 65 (approx. retirement): ~0.85

Interpretation: While the probability of dying soon is low, the remaining life expectancy is quite long. John needs to consider insurance that provides coverage throughout his potential working years and into retirement, ensuring his family's financial security for a substantial period. The calculator helps quantify the 'long tail' risk.

How to Use This Actuarial Table Calculator

Using the **actuarial table calculator** is straightforward. Follow these steps to get your actuarial insights:

  1. Enter Current Age: Input your current age in whole years into the "Current Age" field.
  2. Select Gender: Choose "Male" or "Female" from the dropdown menu. This is crucial as mortality rates differ significantly between genders.
  3. Choose Actuarial Table: Select a standard table (like the US 2019 Period Life Table) or input custom data if you have specific probabilities. The calculator defaults to a common reference table.
  4. Click Calculate: Press the "Calculate" button.

How to Read Results:

  • Main Result (Remaining Life Expectancy): This large, highlighted number indicates the average number of years you are expected to live from your current age, based on the selected table and gender.
  • Survival Probability: The chance (as a decimal) that you will live to see your next birthday.
  • Mortality Probability: The chance (as a decimal) that you will die before your next birthday.
  • Chart and Table: Review the dynamic chart and table for a broader view of life expectancy and mortality across different ages.

Decision-Making Guidance: Use these projections as a planning tool. For instance, if your remaining life expectancy is long, you might need to extend your retirement savings duration or ensure adequate long-term care coverage. Conversely, understanding mortality probabilities can inform life insurance decisions.

Key Factors That Affect Actuarial Table Results

While actuarial tables provide robust statistical data, several real-world factors influence individual outcomes and can cause deviations from the averages:

  1. Lifestyle Choices: Diet, exercise, smoking habits, alcohol consumption, and engagement in risky behaviors significantly impact mortality rates and life expectancy. A healthy lifestyle generally correlates with longer life.
  2. Genetics and Family History: Predispositions to certain diseases passed down through families can affect an individual's lifespan, even if they maintain a healthy lifestyle.
  3. Healthcare Access and Quality: The availability and quality of medical care, including preventative services, screenings, and treatments for chronic conditions, play a vital role in survival rates.
  4. Socioeconomic Status: Factors like income, education, and occupation are often correlated with health outcomes. Higher socioeconomic status can provide access to better nutrition, safer living conditions, and superior healthcare.
  5. Environmental Factors: Exposure to pollution, hazardous working conditions, or areas prone to natural disasters can negatively impact health and longevity.
  6. Medical Advancements: Breakthroughs in medicine and public health initiatives continuously improve treatments and disease prevention, leading to gradual increases in life expectancy over time, reflected in updated actuarial tables.
  7. Inflation and Economic Conditions: While not directly impacting lifespan, inflation affects the purchasing power of savings needed to support an individual throughout their projected lifespan, especially during retirement.
  8. Interest Rates and Investment Returns: These affect the growth of savings intended to fund a longer lifespan, making financial planning crucial.

Frequently Asked Questions (FAQ)

Q1: Does the actuarial table calculator predict my exact lifespan?

A: No. It provides statistical probabilities and average life expectancy based on population data. Individual lifespans vary greatly.

Q2: How often are actuarial tables updated?

A: Standard actuarial tables are typically updated every few years (e.g., annually or biennially) to reflect current mortality trends and demographic changes.

Q3: Why is gender a factor in life expectancy?

A: Statistically, women tend to live longer than men across most populations due to a combination of biological, genetic, and lifestyle factors. Actuarial tables reflect these observed differences.

Q4: Can I use this calculator for my child?

A: Yes, you can input your child's age. Remember that life expectancy calculations are most reliable for adults, as childhood mortality rates are typically very low but still present.

Q5: What is the difference between period life tables and cohort life tables?

A: Period life tables (like the US 2019 example) measure mortality rates for a specific calendar year. Cohort life tables track a group of people born in the same year throughout their entire lives, accounting for future mortality improvements.

Q6: How does "Remaining Life Expectancy" differ from total life expectancy?

A: Total life expectancy at birth is the average number of years a newborn is expected to live. Remaining life expectancy at age 'x' is the average number of additional years a person currently aged 'x' is expected to live.

Q7: Can I input custom mortality rates?

A: The calculator includes an option for "Custom" tables, though implementing full custom table data input requires advanced understanding and may not be available in all versions. The core function relies on standard tables.

Q8: How does this relate to annuity calculations?

A: Actuarial tables are crucial for pricing annuities. They help determine the payout structure based on the annuitant's life expectancy, ensuring the annuity provider can meet its obligations.

// Dummy data for US 2019 Period Life Table (simplified for demonstration) // In a real-world scenario, this would be much more extensive and accurate. var us_2019_expectancy = { male: { ages: [0, 1, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110], q_x: [0.00586, 0.00251, 0.00187, 0.00142, 0.00126, 0.00154, 0.00215, 0.00298, 0.00415, 0.00576, 0.00794, 0.01092, 0.01505, 0.02088, 0.02912, 0.04070, 0.05692, 0.07947, 0.11140, 0.15517, 0.21545, 0.30000, 0.40000, 0.50000], // qx for each age e_x: [74.2, 73.8, 72.9, 69.9, 65.0, 60.1, 55.3, 50.6, 46.0, 41.5, 37.0, 32.7, 28.5, 24.5, 20.6, 17.0, 13.6, 10.5, 7.8, 5.5, 3.6, 2.2, 1.2, 0.5] // ex for each age }, female: { ages: [0, 1, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110], q_x: [0.00496, 0.00214, 0.00160, 0.00117, 0.00105, 0.00125, 0.00166, 0.00222, 0.00304, 0.00417, 0.00570, 0.00773, 0.01060, 0.01455, 0.01995, 0.02717, 0.03805, 0.05321, 0.07421, 0.10405, 0.14500, 0.20500, 0.29000, 0.40000], // qx for each age e_x: [79.1, 78.8, 77.9, 74.9, 70.0, 65.1, 60.3, 55.6, 50.9, 46.3, 41.8, 37.4, 33.1, 29.0, 25.0, 21.2, 17.6, 14.2, 11.1, 8.4, 6.1, 4.1, 2.6, 1.5] // ex for each age } }; var chartInstance = null; function getActuarialData(age, gender, tableData) { var data = tableData[gender]; if (!data) return { q_x: NaN, p_x: NaN, e_x: NaN }; var ages = data.ages; var qx_values = data.q_x; var ex_values = data.e_x; // Find the index for the given age var lowerIndex = -1; for (var i = 0; i < ages.length; i++) { if (ages[i] <= age) { lowerIndex = i; } else { break; } } if (lowerIndex === -1) { // Age is younger than the table starts return { q_x: qx_values[0], p_x: 1 – qx_values[0], e_x: ex_values[0] }; } if (lowerIndex === ages.length – 1) { // Age is older than or equal to the last age in the table return { q_x: qx_values[lowerIndex], p_x: 1 – qx_values[lowerIndex], e_x: ex_values[lowerIndex] }; } // Linear interpolation for q_x and e_x var lowerAge = ages[lowerIndex]; var upperAge = ages[lowerIndex + 1]; var lowerQx = qx_values[lowerIndex]; var upperQx = qx_values[lowerIndex + 1]; var lowerEx = ex_values[lowerIndex]; var upperEx = ex_values[lowerIndex + 1]; var ageDiff = upperAge – lowerAge; var ageOffset = age – lowerAge; var interpolatedQx = lowerQx + ((upperQx – lowerQx) / ageDiff) * ageOffset; var interpolatedEx = lowerEx + ((upperEx – lowerEx) / ageDiff) * ageOffset; // Ensure interpolated values are within valid ranges (0 to 1 for probabilities) interpolatedQx = Math.max(0, Math.min(1, interpolatedQx)); var interpolatedPx = 1 – interpolatedQx; interpolatedPx = Math.max(0, Math.min(1, interpolatedPx)); return { q_x: interpolatedQx, p_x: interpolatedPx, e_x: interpolatedEx }; } function validateInput(id, min, max, message) { var input = document.getElementById(id); var errorElement = document.getElementById(id + "Error"); var value = parseFloat(input.value); errorElement.classList.remove("visible"); input.style.borderColor = "var(–border-color)"; if (input.value.trim() === "") { errorElement.innerText = "This field cannot be empty."; errorElement.classList.add("visible"); input.style.borderColor = "#dc3545"; return false; } if (isNaN(value)) { errorElement.innerText = "Please enter a valid number."; errorElement.classList.add("visible"); input.style.borderColor = "#dc3545"; return false; } if (value max) { errorElement.innerText = message; errorElement.classList.add("visible"); input.style.borderColor = "#dc3545"; return false; } return true; } function calculateActuarial() { var currentAge = parseInt(document.getElementById("currentAge").value); var gender = document.getElementById("gender").value; var selectedTable = document.getElementById("lifeExpectancyTable").value; var isValid = true; isValid &= validateInput("currentAge", 0, 120, "Age must be between 0 and 120."); if (!isValid) { document.getElementById("results-container").style.display = "none"; return; } var tableData = us_2019_expectancy; // Default to US 2019 // Add logic here if custom table data needs to be loaded/processed var data = getActuarialData(currentAge, gender, tableData); var mainResultElement = document.getElementById("main-result"); var survivalProbElement = document.getElementById("survivalProb"); var mortalityProbElement = document.getElementById("mortalityProb"); var remainingLifeExpElement = document.getElementById("remainingLifeExp"); var resultsContainer = document.getElementById("results-container"); if (isNaN(data.e_x) || isNaN(data.p_x) || isNaN(data.q_x)) { mainResultElement.innerText = "Error"; survivalProbElement.innerText = "-"; mortalityProbElement.innerText = "-"; remainingLifeExpElement.innerText = "-"; resultsContainer.style.backgroundColor = "#dc3545"; // Indicate error } else { mainResultElement.innerText = data.e_x.toFixed(1); survivalProbElement.innerText = data.p_x.toFixed(3); mortalityProbElement.innerText = data.q_x.toFixed(3); remainingLifeExpElement.innerText = data.e_x.toFixed(1); // For this simplified calc, same as main result resultsContainer.style.backgroundColor = "var(–primary-color)"; // Reset to success color resultsContainer.style.display = "block"; } updateChartAndTable(gender, tableData); } function resetCalculator() { document.getElementById("currentAge").value = "30"; document.getElementById("gender").value = "male"; document.getElementById("lifeExpectancyTable").value = "us_2019_expectancy"; // Clear errors document.getElementById("currentAgeError").innerText = ""; document.getElementById("currentAgeError").classList.remove("visible"); document.getElementById("genderError").innerText = ""; document.getElementById("genderError").classList.remove("visible"); document.getElementById("lifeExpectancyTableError").innerText = ""; document.getElementById("lifeExpectancyTableError").classList.remove("visible"); calculateActuarial(); // Recalculate with default values document.getElementById("results-container").style.display = "none"; // Hide results until calculation } function copyResults() { var mainResult = document.getElementById("main-result").innerText; var survivalProb = document.getElementById("survivalProb").innerText; var mortalityProb = document.getElementById("mortalityProb").innerText; var remainingLifeExp = document.getElementById("remainingLifeExp").innerText; var age = document.getElementById("currentAge").value; var gender = document.getElementById("gender").value; var selectedTable = document.getElementById("lifeExpectancyTable").value; if (mainResult === "–") { alert("No results to copy yet. Please perform a calculation first."); return; } var resultsText = "Actuarial Projection Results:\n\n" + "Age: " + age + "\n" + "Gender: " + gender.charAt(0).toUpperCase() + gender.slice(1) + "\n" + "Table: " + selectedTable + "\n\n" + "——————————\n" + "Remaining Life Expectancy: " + mainResult + " years\n" + "Survival Probability (to next age): " + survivalProb + "\n" + "Mortality Probability (at current age): " + mortalityProb + "\n" + "——————————\n"; try { navigator.clipboard.writeText(resultsText).then(function() { // Success feedback (optional) var copyButton = document.querySelector('button.success'); copyButton.innerText = 'Copied!'; setTimeout(function() { copyButton.innerText = 'Copy Results'; }, 2000); }).catch(function(err) { console.error('Failed to copy text: ', err); alert('Failed to copy results. Please copy manually.'); }); } catch (e) { alert('Clipboard API not available. Please copy manually.'); } } function updateChartAndTable(gender, tableData) { var chartAgeLimit = 90; // Limit for chart visualization var chartDataPoints = 15; // Number of data points for the chart // Update Table var tableBody = document.querySelector("#actuarialTable tbody"); tableBody.innerHTML = "; // Clear existing rows var selectedAge = parseInt(document.getElementById("currentAge").value); var ageStep = Math.floor(chartAgeLimit / chartDataPoints); if (ageStep === 0) ageStep = 1; // Ensure step is at least 1 var agesToDisplay = []; var currentAgeForTable = 0; while(currentAgeForTable <= chartAgeLimit && agesToDisplay.length 0 && selectedAge 0 && !agesToDisplay.includes(chartAgeLimit)) { agesToDisplay.push(chartAgeLimit); agesToDisplay.sort(function(a, b){return a – b}); } for (var i = 0; i < agesToDisplay.length; i++) { var age = agesToDisplay[i]; if (age < 0) continue; var data = getActuarialData(age, gender, tableData); if (!isNaN(data.q_x) && !isNaN(data.p_x) && !isNaN(data.e_x)) { var row = tableBody.insertRow(); row.insertCell(0).textContent = age; row.insertCell(1).textContent = data.q_x.toFixed(4); row.insertCell(2).textContent = data.p_x.toFixed(4); row.insertCell(3).textContent = data.e_x.toFixed(1); } } // Update Chart var ctx = document.getElementById('lifeExpectancyChart').getContext('2d'); var chartAges = []; var lifeExpectancyData = []; var mortalityData = []; var currentAgeForChart = 0; while(currentAgeForChart <= chartAgeLimit && chartAges.length 0 && selectedAge <= chartAgeLimit && !chartAges.includes(selectedAge)) { chartAges.push(selectedAge); var data = getActuarialData(selectedAge, gender, tableData); lifeExpectancyData.push(data.e_x); mortalityData.push(data.q_x * 1000); chartAges.sort(function(a, b){return a – b}); // Reorder corresponding data arrays var sortedIndices = chartAges.map(function(_, i) { return i; }).sort(function(a, b) { return chartAges[a] chartAges[b] ? 1 : 0; }); chartAges = sortedIndices.map(function(i) { return chartAges[i]; }); lifeExpectancyData = sortedIndices.map(function(i) { return lifeExpectancyData[i]; }); mortalityData = sortedIndices.map(function(i) { return mortalityData[i]; }); } if (chartInstance) { chartInstance.destroy(); } chartInstance = new Chart(ctx, { type: 'line', data: { labels: chartAges.map(String), // Ensure labels are strings datasets: [{ label: 'Life Expectancy (Years)', data: lifeExpectancyData, borderColor: 'var(–primary-color)', backgroundColor: 'rgba(0, 74, 153, 0.1)', fill: false, tension: 0.1, yAxisID: 'y-axis-1' }, { label: 'Mortality Rate (per 1000)', data: mortalityData, borderColor: '#dc3545', backgroundColor: 'rgba(220, 53, 69, 0.1)', fill: false, tension: 0.1, yAxisID: 'y-axis-2' }] }, options: { responsive: true, maintainAspectRatio: true, scales: { x: { title: { display: true, text: 'Age (Years)' } }, 'y-axis-1': { type: 'linear', position: 'left', title: { display: true, text: 'Life Expectancy (Years)' }, grid: { drawOnChartArea: true, }, ticks: { beginAtZero: false, callback: function(value, index, values) { return value.toFixed(1); } } }, 'y-axis-2': { type: 'linear', position: 'right', title: { display: true, text: 'Mortality Rate (per 1000)' }, grid: { drawOnChartArea: false, // Only draw grid lines for the primary y-axis }, ticks: { beginAtZero: true, callback: function(value, index, values) { return value.toFixed(0); } } } }, plugins: { legend: { position: 'top', }, tooltip: { mode: 'index', intersect: false, } }, hover: { mode: 'nearest', intersect: true } } }); } // Initialize calculator on page load document.addEventListener('DOMContentLoaded', function() { calculateActuarial(); // Add basic event listeners for input changes to trigger real-time updates document.getElementById("currentAge").addEventListener("input", calculateActuarial); document.getElementById("gender").addEventListener("change", calculateActuarial); document.getElementById("lifeExpectancyTable").addEventListener("change", calculateActuarial); }); // Chart.js CDN – required for the canvas chart. In a production environment, consider bundling. // For this self-contained HTML, we need to include it. var script = document.createElement('script'); script.src = 'https://cdn.jsdelivr.net/npm/chart.js@3.7.0/dist/chart.min.js'; document.head.appendChild(script);

Leave a Comment