Partial Derivative Calculator

Calculate partial derivatives ∂f/∂x and ∂f/∂y of multivariable functions numerically. Includes gradient, Hessian matrix, and directional derivatives.

Partial derivative value (numerical approx.)
f(x,y) at given point
Extended More scenarios, charts & detailed breakdown
∂f/∂x (numerical approx.)
Professional Full parameters & maximum detail

Second-Order Partials & Hessian

∂²f/∂x² (numerical approx.)
∂²f/∂y² (numerical approx.)
∂²f/∂x∂y (numerical approx.)
Hessian determinant fxx·fyy − fxy²

Directional Derivative

Directional derivative D_u f

How to Use This Calculator

  1. Enter f(x,y) (e.g. x^2 + x*y + y^2).
  2. Enter the x and y values at which to evaluate.
  3. Select ∂f/∂x or ∂f/∂y.
  4. Use the Gradient tab to get both partial derivatives and magnitude.
  5. The Professional tab computes the full Hessian matrix and directional derivative.

Formula

∂f/∂x ≈ (f(x+h,y) − f(x−h,y)) / (2h)  |  |∇f| = √((∂f/∂x)² + (∂f/∂y)²)

Example

f(x,y) = x²y, at (2,3): ∂f/∂x = 2xy = 12, ∂f/∂y = x² = 4. |∇f| = √(144+16) ≈ 12.649.

Frequently Asked Questions

  • The partial derivative ∂f/∂x measures how f(x,y) changes when x changes and y is held constant. It is computed numerically as (f(x+h,y)−f(x−h,y))/(2h).
  • The gradient ∇f = (∂f/∂x, ∂f/∂y) is a vector pointing in the direction of steepest ascent. Its magnitude |∇f| is the rate of steepest increase.
  • The Hessian H is the 2×2 matrix of second partial derivatives: [[fxx, fxy],[fxy, fyy]]. Its determinant det(H) = fxx·fyy − fxy² is used in the second derivative test to classify critical points.
  • The directional derivative D_u f = ∇f · u gives the rate of change of f in the direction of unit vector u = (dx, dy). It equals |∇f|cos(θ) where θ is the angle between ∇f and u.
  • The current tool handles f(x,y). For f(x,y,z), use the Triple Integral Calculator tab which accepts 3-variable expressions.

Related Calculators

Sources & References (5)
  1. Partial Derivatives — Paul's Online Math Notes — Lamar University
  2. MIT OCW 18.02 Multivariable Calculus — MIT
  3. Multivariable Calculus — Khan Academy
  4. Partial Derivative — Wolfram MathWorld — Wolfram MathWorld
  5. Stewart's Multivariable Calculus (reference) — Cengage / Stewart