Body Weight Percentile Calculator

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Body Weight Percentile Calculator

A free tool to understand your child's growth trajectory relative to other children of the same age and sex.

Body Weight Percentile Calculator

Enter age in whole months.
Enter weight in kilograms.
Select Sex Male Female
Your Results

Weight for Age Z-score:

Median Weight for Age: kg

Standard Deviation: kg

Percentiles indicate the percentage of children at or below a given weight for their age and sex. This is calculated using WHO (World Health Organization) growth charts data which relies on Z-scores.
Results copied to clipboard!
Weight-for-Age Percentiles Comparison

What is Body Weight Percentile?

The body weight percentile calculator is a valuable tool designed to help parents, guardians, and healthcare professionals understand how a child's weight compares to other children of the same age and sex. It doesn't measure health in isolation but provides context within established growth standards. Understanding a child's {primary_keyword} is crucial for monitoring healthy development and identifying potential growth concerns early on. This {primary_keyword} is a key indicator, especially during infancy and early childhood when rapid growth is expected.

A child's {primary_keyword} is determined by comparing their weight to a reference population of children. For example, if a child is in the 75th percentile for weight, it means they weigh more than 75% of children of the same age and sex, and less than 25%. This information is typically derived from growth charts developed by organizations like the World Health Organization (WHO) or national health bodies. It's important to remember that percentiles are not absolute measures of health; a child can be healthy at various percentiles. A {primary_keyword} should be interpreted alongside other growth metrics like height and head circumference.

Who should use it:

  • Parents and guardians tracking their child's growth.
  • Pediatricians and healthcare providers assessing a child's nutritional status and development.
  • Caregivers looking for reassurance or insights into growth patterns.

Common Misconceptions:

  • Percentiles are rankings, not targets: A child doesn't need to be at the 50th percentile to be healthy. Consistent growth along their own percentile curve is often more important than hitting a specific number.
  • Weight percentile is not the whole story: It should be considered with height percentile and BMI percentile for a comprehensive view.
  • Sudden jumps or drops are always concerning: While rapid changes warrant attention, gradual shifts within a percentile range can be normal.

Body Weight Percentile Formula and Mathematical Explanation

The calculation of body weight percentile relies on established growth data, typically from the World Health Organization (WHO) or similar health authorities. These organizations provide standardized growth charts that map weight-for-age, length-for-age, and other metrics for children from birth to a certain age. The core of the calculation involves determining a Z-score, which then allows us to find the corresponding percentile.

The Z-score represents how many standard deviations a child's measurement is away from the median (50th percentile) measurement for their age and sex. The formula for the Z-score is:

Z = (X – M) / SD

Where:

  • Z is the Z-score.
  • X is the child's measured weight.
  • M is the median weight for the child's age and sex (from growth charts).
  • SD is the standard deviation of weight for the child's age and sex (from growth charts).

Once the Z-score is calculated, it is used to find the corresponding percentile. This is typically done by referencing a standard normal distribution (or Gaussian distribution) table or using statistical functions. For example, a Z-score of 0 corresponds to the 50th percentile, a Z-score of approximately 1.645 corresponds to the 90th percentile, and a Z-score of approximately -1.645 corresponds to the 10th percentile. The calculator uses pre-computed lookups based on the WHO growth standards to find the percentile from the Z-score.

Variables Table:

Variable Meaning Unit Typical Range
Child's Age Age of the child at the time of measurement. Months 0 – 60 (for WHO charts, varies by chart)
Child's Weight (X) The measured weight of the child. Kilograms (kg) 0.5 – 30 (typical range for ages 0-5)
Sex Biological sex of the child (Male/Female). Categorical Male, Female
Median Weight (M) The median weight for the specific age and sex from growth standards. Kilograms (kg) Varies significantly by age and sex
Standard Deviation (SD) The standard deviation of weight for the specific age and sex from growth standards. Kilograms (kg) Varies significantly by age and sex
Z-score Number of standard deviations the child's weight is from the median. Unitless Typically -3 to +3, but can extend further
Percentile The percentage of children at or below this child's weight for their age and sex. Percentage (%) 0 – 100

Practical Examples (Real-World Use Cases)

Understanding the {primary_keyword} requires looking at real-world scenarios. Here are a couple of examples:

Example 1: Tracking a 12-Month-Old Boy's Weight

A parent brings their 12-month-old son for a regular check-up. The child weighs 10.5 kg and is male.

Inputs:

  • Child's Age: 12 months
  • Child's Weight: 10.5 kg
  • Child's Sex: Male

Calculation (simulated): Using WHO growth data for a 12-month-old male, the median weight (M) is approximately 9.6 kg, and the standard deviation (SD) is about 1.0 kg. The Z-score would be (10.5 – 9.6) / 1.0 = +0.9. This Z-score corresponds to approximately the 81.6th percentile.

Outputs:

  • Primary Result: 81.6th Percentile
  • Weight for Age Z-score: +0.9
  • Median Weight for Age: 9.6 kg
  • Standard Deviation: 1.0 kg

Interpretation: This child weighs more than about 81.6% of 12-month-old boys. This is within a healthy range, indicating good growth, and the consistent trend along this percentile is more important than the specific number. This {primary_keyword} suggests robust weight gain.

Example 2: Assessing a 24-Month-Old Girl's Weight

A 24-month-old girl measures 13.0 kg and is female.

Inputs:

  • Child's Age: 24 months
  • Child's Weight: 13.0 kg
  • Child's Sex: Female

Calculation (simulated): For a 24-month-old female, the median weight (M) is around 11.7 kg, with an SD of about 1.2 kg. The Z-score is (13.0 – 11.7) / 1.2 = +1.08. This Z-score translates to approximately the 86th percentile.

Outputs:

  • Primary Result: 86th Percentile
  • Weight for Age Z-score: +1.08
  • Median Weight for Age: 11.7 kg
  • Standard Deviation: 1.2 kg

Interpretation: This child's weight is higher than approximately 86% of 24-month-old girls. This percentile also suggests healthy growth. The healthcare provider would confirm if this aligns with the child's height percentile and overall development. Consistent tracking of this child's {primary_keyword} over time is key.

How to Use This Body Weight Percentile Calculator

Our {primary_keyword} calculator is designed for ease of use, providing quick insights into your child's growth. Follow these simple steps:

  1. Enter Child's Age: Input the child's exact age in months. For example, if the child is 3 years old, enter 36 months.
  2. Enter Child's Weight: Provide the child's most recent weight measurement in kilograms. Ensure the unit is correct.
  3. Select Child's Sex: Choose either 'Male' or 'Female' from the dropdown menu. This is crucial as growth patterns differ between sexes.
  4. Click 'Calculate Percentile': Once all fields are filled, press the button. The calculator will process the data using standard growth charts.

How to Read Results:

  • Primary Result (Percentile): This is the main output, showing your child's position relative to others. A higher percentile means a heavier child for their age and sex; a lower percentile means a lighter child.
  • Weight for Age Z-score: A statistical measure indicating how many standard deviations from the average the child's weight is.
  • Median Weight for Age: The weight of the average child (50th percentile) at that specific age and sex.
  • Standard Deviation: A measure of the typical spread of weights around the median for that age and sex.

Decision-Making Guidance:

A single percentile number is just a snapshot. Focus on the overall growth trend. Is the child consistently following a percentile curve? Has there been a sudden, unexplained jump or drop? Discuss these results with your pediatrician. They can provide personalized advice based on the child's complete health profile, including their height, activity level, and family history. This {primary_keyword} calculator is a supplementary tool, not a diagnostic one.

Key Factors That Affect Body Weight Percentile Results

While the calculator provides a percentile based on age, sex, and weight, several underlying factors influence these results and a child's overall growth trajectory. Understanding these can provide a more nuanced perspective:

  1. Genetics: A child's inherent genetic makeup plays a significant role in their growth potential. Some children are naturally predisposed to being larger or smaller than average. This is a fundamental factor influencing their position on the {primary_keyword} charts.
  2. Nutrition and Diet: The quality and quantity of food a child consumes directly impact weight gain. Adequate intake of essential nutrients supports healthy growth, while deficiencies or excessive intake can lead to deviations in weight percentiles.
  3. Physical Activity Level: An active child burns more calories, which can influence their weight relative to their height. A very sedentary child might gain weight differently than a highly active one, even with similar caloric intake.
  4. Health Conditions: Certain medical conditions, such as thyroid issues, gastrointestinal problems, or chronic illnesses, can significantly affect a child's appetite, nutrient absorption, and metabolism, thereby influencing their weight and percentile.
  5. Prematurity and Birth Weight: Premature babies often have different growth curves initially. While they may "catch up," their starting point and early growth patterns can influence their percentile ranking for some time.
  6. Sleep Patterns: Sufficient and quality sleep is crucial for growth hormone release and overall metabolic regulation, which can indirectly affect weight gain and thus the {primary_keyword}.
  7. Feeding Practices: Breastfeeding or formula feeding, introduction of solids, and portion sizes can all influence a baby's or toddler's weight gain trajectory in the crucial early months and years.

Frequently Asked Questions (FAQ)

What is the ideal body weight percentile for a child?

There isn't one single "ideal" percentile. Children grow differently. The most important factor is that the child is growing consistently along their own percentile curve, or following a trajectory that is healthy for them. Your pediatrician is the best resource for determining what's healthy for your child.

Is a high weight percentile bad?

Not necessarily. A high {primary_keyword} (e.g., above the 90th percentile) means the child is heavier than most others of the same age and sex. It warrants monitoring and discussion with a healthcare provider to ensure it's part of healthy, consistent growth and not indicative of being overweight, especially when considered alongside height.

Is a low weight percentile bad?

Similarly, a low {primary_keyword} (e.g., below the 10th percentile) means the child is lighter than most others. This can be normal for some children, but it should be evaluated by a doctor to rule out any underlying issues like malnutrition or growth problems.

How often should I check my child's percentile?

Regular pediatric check-ups are the best time. Typically, these occur frequently in infancy and toddlerhood, and then annually. Your doctor will track the {primary_keyword} and other growth metrics over time.

Can a child's percentile change over time?

Yes, a child's percentile can change, especially during rapid growth phases or if there are significant changes in diet, health, or activity. However, rapid or drastic shifts are usually monitored closely by healthcare providers.

What's the difference between weight percentile and BMI percentile?

Weight percentile compares a child's weight to others of the same age and sex. BMI percentile compares a child's Body Mass Index (BMI) – a ratio of weight to height – to others of the same age and sex. BMI percentile is often considered a better indicator of body fatness and potential weight concerns.

Does this calculator use WHO or CDC growth charts?

This calculator is designed to align with WHO (World Health Organization) growth standards, which are widely used for infants and children up to age 5 globally. For older children, CDC charts might be more commonly used.

What if my child's age is not an exact month?

For best results, use the exact age in months. If you have a fractional age (e.g., 12 months and 2 weeks), it's generally acceptable to round to the nearest full month or use the lower full month for calculation. For precise medical assessments, always consult your pediatrician.

Disclaimer: This calculator is for informational purposes only and does not constitute medical advice. Always consult with a qualified healthcare professional for any health concerns or before making any decisions related to your child's health or treatment.

// WHO Growth Data – Simplified Lookup Table (approximate values for demonstration) // This is a highly simplified representation. Real-world data is more complex and uses LMS parameters. // Structure: { age_in_months: { male: { median: W, sd: SD }, female: { median: W, sd: SD } } } var whoGrowthData = { 0: { male: { median: 3.5, sd: 0.4 }, female: { median: 3.3, sd: 0.4 } }, 1: { male: { median: 4.5, sd: 0.5 }, female: { median: 4.2, sd: 0.5 } }, 2: { male: { median: 5.5, sd: 0.6 }, female: { median: 5.2, sd: 0.6 } }, 3: { male: { median: 6.4, sd: 0.6 }, female: { median: 6.0, sd: 0.6 } }, 4: { male: { median: 7.1, sd: 0.7 }, female: { median: 6.7, sd: 0.7 } }, 5: { male: { median: 7.7, sd: 0.7 }, female: { median: 7.2, sd: 0.7 } }, 6: { male: { median: 8.2, sd: 0.7 }, female: { median: 7.7, sd: 0.7 } }, 7: { male: { median: 8.7, sd: 0.8 }, female: { median: 8.2, sd: 0.8 } }, 8: { male: { median: 9.1, sd: 0.8 }, female: { median: 8.6, sd: 0.8 } }, 9: { male: { median: 9.5, sd: 0.8 }, female: { median: 9.0, sd: 0.8 } }, 10: { male: { median: 9.8, sd: 0.9 }, female: { median: 9.4, sd: 0.9 } }, 11: { male: { median: 10.1, sd: 0.9 }, female: { median: 9.7, sd: 0.9 } }, 12: { male: { median: 10.3, sd: 1.0 }, female: { median: 10.0, sd: 1.0 } }, 18: { male: { median: 11.5, sd: 1.1 }, female: { median: 11.1, sd: 1.1 } }, 24: { male: { median: 12.4, sd: 1.3 }, female: { median: 11.9, sd: 1.2 } }, 30: { male: { median: 13.3, sd: 1.4 }, female: { median: 12.7, sd: 1.3 } }, 36: { male: { median: 14.1, sd: 1.5 }, female: { median: 13.5, sd: 1.4 } }, 48: { male: { median: 15.7, sd: 1.7 }, female: { median: 15.0, sd: 1.6 } }, 60: { male: { median: 17.1, sd: 1.9 }, female: { median: 16.4, sd: 1.8 } } }; // Function to interpolate median and SD if age is not directly in the lookup function getGrowthDataForAge(ageInMonths, sex) { var dataPoints = []; var ages = Object.keys(whoGrowthData).map(Number).sort(function(a, b){ return a – b; }); for (var i = 0; i = ages[i] && ageInMonths <= ages[i+1]) { dataPoints.push({ age: ages[i], median: whoGrowthData[ages[i]][sex].median, sd: whoGrowthData[ages[i]][sex].sd }); dataPoints.push({ age: ages[i+1], median: whoGrowthData[ages[i+1]][sex].median, sd: whoGrowthData[ages[i+1]][sex].sd }); break; } } if (dataPoints.length < 2) { // If age is outside the defined range, return closest available data if (ageInMonths ages[ages.length – 1]) return whoGrowthData[ages[ages.length – 1]][sex]; return null; // Should not happen with age checks } // Linear interpolation var age1 = dataPoints[0].age; var median1 = dataPoints[0].median; var sd1 = dataPoints[0].sd; var age2 = dataPoints[1].age; var median2 = dataPoints[1].median; var sd2 = dataPoints[1].sd; var fraction = (ageInMonths – age1) / (age2 – age1); var interpolatedMedian = median1 + fraction * (median2 – median1); var interpolatedSd = sd1 + fraction * (sd2 – sd1); return { median: interpolatedMedian, sd: interpolatedSd }; } // Function to get percentile from Z-score (using approximation or lookup) // This is a simplified approximation. A more accurate method would use CDF of normal distribution. function getPercentileFromZScore(zScore) { if (isNaN(zScore)) return "N/A"; // Basic approximation for common ranges: if (zScore < -3.0) return 0; if (zScore < -2.0) return 2.28; // ~2.5th percentile if (zScore < -1.645) return 5; // 5th percentile if (zScore < -1.0) return 15.87; // ~16th percentile if (zScore < -0.5) return 30.85; // ~31st percentile if (zScore < 0) return 50 – ( (0 – zScore) * 15.87 ); // Approaching 50th if (zScore < 0.5) return 50 + ( zScore * 15.87 ); // Approaching 50th if (zScore < 1.0) return 69.15; // ~69th percentile if (zScore < 1.645) return 84.13; // ~84th percentile if (zScore < 2.0) return 97.72; // ~97.5th percentile if (zScore < 3.0) return 99.73; // ~99.7th percentile return 100; // For more accuracy, a lookup table or statistical function is needed. // Example of a more precise mapping using Z-table values: // var zTable = { /* … load z-table values … */ }; // return zTable[zScore.toFixed(2)] || 'N/A'; } var chartInstance = null; // Global variable to hold chart instance function updateChart(age, sex, weight) { var canvas = document.getElementById('growthChart'); var ctx = canvas.getContext('2d'); // Destroy previous chart if it exists if (chartInstance) { chartInstance.destroy(); } var data = []; var labels = []; var ages = Object.keys(whoGrowthData).map(Number).sort(function(a, b){ return a – b; }); for (var i = 0; i < ages.length; i++) { var currentAge = ages[i]; labels.push(currentAge + 'm'); var growthData = getGrowthDataForAge(currentAge, sex); if (growthData) { var zScore = (weight – growthData.median) / growthData.sd; // Using current weight for all points is illustrative var percentile = getPercentileFromZScore(zScore); data.push(percentile); } else { data.push(null); // Handle missing data } } // Add the child's actual data point labels.push(age + 'm (Child)'); var childGrowthData = getGrowthDataForAge(age, sex); var childZScore = childGrowthData ? (weight – childGrowthData.median) / childGrowthData.sd : NaN; var childPercentile = getPercentileFromZScore(childZScore); data.push(childPercentile); // Define Percentile Lines var percentile3 = getPercentileFromZScore(-1.645); // Approx 5th var percentile5 = getPercentileFromZScore(-1.282); // Approx 10th var percentile50 = 50; // 50th var percentile90 = getPercentileFromZScore(1.282); // Approx 90th var percentile95 = getPercentileFromZScore(1.645); // Approx 95th chartInstance = new Chart(ctx, { type: 'line', data: { labels: labels, datasets: [ { label: 'Child\'s Weight Percentile', data: data.map(function(val, index) { return index === data.length – 1 ? val : null; }), // Only plot the last point (child's actual) borderColor: '#004a99', backgroundColor: 'rgba(0, 74, 153, 0.2)', fill: false, pointRadius: 6, pointHoverRadius: 8, tension: 0.1 }, { label: '5th Percentile', data: Array(labels.length).fill(percentile5), borderColor: 'rgba(255, 99, 132, 0.5)', borderDash: [5, 5], backgroundColor: 'rgba(255, 99, 132, 0.1)', fill: false, pointRadius: 0, tension: 0.1 }, { label: '10th Percentile', data: Array(labels.length).fill(percentile10), borderColor: 'rgba(255, 159, 64, 0.5)', borderDash: [5, 5], backgroundColor: 'rgba(255, 159, 64, 0.1)', fill: false, pointRadius: 0, tension: 0.1 }, { label: '50th Percentile (Median)', data: Array(labels.length).fill(percentile50), borderColor: 'rgba(75, 192, 192, 0.7)', borderDash: [2, 2], backgroundColor: 'rgba(75, 192, 192, 0.1)', fill: false, pointRadius: 0, tension: 0.1 }, { label: '90th Percentile', data: Array(labels.length).fill(percentile90), borderColor: 'rgba(153, 102, 255, 0.5)', borderDash: [5, 5], backgroundColor: 'rgba(153, 102, 255, 0.1)', fill: false, pointRadius: 0, tension: 0.1 }, { label: '95th Percentile', data: Array(labels.length).fill(percentile95), borderColor: 'rgba(255, 206, 86, 0.5)', borderDash: [5, 5], backgroundColor: 'rgba(255, 206, 86, 0.1)', fill: false, pointRadius: 0, tension: 0.1 } ] }, options: { responsive: true, maintainAspectRatio: true, scales: { x: { title: { display: true, text: 'Age (Months)' } }, y: { title: { display: true, text: 'Percentile' }, min: 0, max: 100, ticks: { callback: function(value) { if (value % 10 === 0) return value; } } } }, plugins: { tooltip: { callbacks: { label: function(context) { var label = context.dataset.label || ''; if (label) { label += ': '; } if (context.parsed.y !== null) { label += context.parsed.y.toFixed(1) + '%'; } return label; } } }, legend: { position: 'top', } } } }); } function validateInput(id, errorId, min, max, fieldName, isNumber) { var input = document.getElementById(id); var errorDiv = document.getElementById(errorId); var value = input.value.trim(); var isValid = true; if (value === "") { errorDiv.textContent = fieldName + " is required."; isValid = false; } else if (isNumber) { var numValue = parseFloat(value); if (isNaN(numValue)) { errorDiv.textContent = fieldName + " must be a number."; isValid = false; } else if (min !== null && numValue max) { errorDiv.textContent = fieldName + " cannot be greater than " + max + (fieldName.toLowerCase().includes('weight') ? ' kg' : ' months') + "."; isValid = false; } } if (isValid) { errorDiv.textContent = ""; input.style.borderColor = "#ced4da"; // Reset border color errorDiv.style.display = 'none'; } else { input.style.borderColor = "#dc3545"; // Highlight error border errorDiv.style.display = 'block'; } return isValid; } function validateAge() { return validateInput('childAge', 'ageError', 0, 120, 'Age', true); // Max age 10 years = 120 months } function validateWeight() { return validateInput('childWeight', 'weightError', 0.1, 50, 'Weight', true); // Max weight 50 kg (a bit over typical range for safety) } function validateSex() { var select = document.getElementById('childSex'); var errorDiv = document.getElementById('sexError'); var isValid = true; if (select.value === "") { errorDiv.textContent = "Sex is required."; isValid = false; } else { errorDiv.textContent = ""; } if (isValid) { select.style.borderColor = "#ced4da"; errorDiv.style.display = 'none'; } else { select.style.borderColor = "#dc3545"; errorDiv.style.display = 'block'; } return isValid; } function calculatePercentile() { var isValidAge = validateAge(); var isValidWeight = validateWeight(); var isValidSex = validateSex(); if (!isValidAge || !isValidWeight || !isValidSex) { return; } var age = parseFloat(document.getElementById('childAge').value); var weight = parseFloat(document.getElementById('childWeight').value); var sex = document.getElementById('childSex').value; var growthData = getGrowthDataForAge(age, sex); if (!growthData) { document.getElementById('primaryResult').textContent = "Data unavailable for this age."; document.getElementById('zScoreResult').textContent = "N/A"; document.getElementById('medianWeightResult').textContent = "N/A"; document.getElementById('stdDevResult').textContent = "N/A"; document.getElementById('resultsContainer').style.display = 'block'; document.getElementById('copyResultsBtn').style.display = 'inline-block'; updateChart(age, sex, weight); // Try to update chart even with limited data return; } var medianWeight = growthData.median; var stdDev = growthData.sd; var zScore = (weight – medianWeight) / stdDev; var percentile = getPercentileFromZScore(zScore); document.getElementById('primaryResult').textContent = percentile.toFixed(1) + "th Percentile"; document.getElementById('zScoreResult').textContent = zScore.toFixed(2); document.getElementById('medianWeightResult').textContent = medianWeight.toFixed(2); document.getElementById('stdDevResult').textContent = stdDev.toFixed(2); document.getElementById('resultsContainer').style.display = 'block'; document.getElementById('copyResultsBtn').style.display = 'inline-block'; updateChart(age, sex, weight); } function resetCalculator() { document.getElementById('childAge').value = ""; document.getElementById('childWeight').value = ""; document.getElementById('childSex').value = ""; document.getElementById('ageError').textContent = ""; document.getElementById('weightError').textContent = ""; document.getElementById('sexError').textContent = ""; document.getElementById('childAge').style.borderColor = "#ced4da"; document.getElementById('childWeight').style.borderColor = "#ced4da"; document.getElementById('childSex').style.borderColor = "#ced4da"; document.getElementById('resultsContainer').style.display = 'none'; document.getElementById('copyResultsBtn').style.display = 'none'; // Clear chart (optional, or reset to default view) var canvas = document.getElementById('growthChart'); var ctx = canvas.getContext('2d'); if (chartInstance) { chartInstance.destroy(); chartInstance = null; } ctx.clearRect(0, 0, canvas.width, canvas.height); // Clear canvas content } function copyResults() { var percentile = document.getElementById('primaryResult').textContent; var zScore = document.getElementById('zScoreResult').textContent; var medianWeight = document.getElementById('medianWeightResult').textContent; var stdDev = document.getElementById('stdDevResult').textContent; var age = document.getElementById('childAge').value; var weight = document.getElementById('childWeight').value; var sex = document.getElementById('childSex').value; var resultsText = "Body Weight Percentile Calculation Results:\n\n"; resultsText += "Key Inputs:\n"; resultsText += "- Age: " + age + " months\n"; resultsText += "- Weight: " + weight + " kg\n"; resultsText += "- Sex: " + sex + "\n\n"; resultsText += "Key Outputs:\n"; resultsText += "- Body Weight Percentile: " + percentile + "\n"; resultsText += "- Weight for Age Z-score: " + zScore + "\n"; resultsText += "- Median Weight for Age: " + medianWeight + "\n"; resultsText += "- Standard Deviation: " + stdDev + "\n"; resultsText += "\nSource: WHO Growth Standards (Approximation)"; // Use a temporary textarea to copy text var textArea = document.createElement("textarea"); textArea.value = resultsText; textArea.style.position = "fixed"; textArea.style.left = "-9999px"; document.body.appendChild(textArea); textArea.focus(); textArea.select(); try { var successful = document.execCommand('copy'); var msg = successful ? 'Results copied to clipboard!' : 'Copying text command was unsuccessful'; var feedback = document.querySelector('.copy-feedback'); feedback.textContent = msg; feedback.style.display = 'block'; setTimeout(function() { feedback.style.display = 'none'; }, 3000); } catch (err) { console.error('Fallback: Oops, unable to copy', err); var feedback = document.querySelector('.copy-feedback'); feedback.textContent = 'Failed to copy. Please copy manually.'; feedback.style.display = 'block'; setTimeout(function() { feedback.style.display = 'none'; }, 3000); } document.body.removeChild(textArea); } // Initial setup for chart library (Chart.js) – requires CDN or local file // For this pure HTML output, we assume Chart.js is available globally. // In a real WordPress environment, you would enqueue this script properly. // For demonstration purposes, if running locally without Chart.js, it will fail. // Add this to your HTML if you are testing this standalone: // // Ensure chart is updated on initial load if default values are set (not implemented here) // Or trigger calculation on page load if defaults are desired. <!– –>

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