This example involves transcendental functions (sin, exp) and the chain rule, then evaluates the partial derivative at a specific point—skills beyond simple polynomial differentiation.
Problem: Given g(x, y) = x² sin(y) + eˣʸ, find ∂g/∂x and evaluate it at the point (1, 0).
Step 1: Treat y as a constant and differentiate with respect to x. The first term x² sin(y) differentiates to 2x sin(y).
∂x∂(x2siny)=2xsiny
Step 2: For the second term eˣʸ, use the chain rule. Since y is constant, the derivative of xy with respect to x is y.
∂x∂(exy)=yexy
Step 3: Combine the results to get the full partial derivative.
∂x∂g=2xsiny+yexy
Step 4: Evaluate at (1, 0): substitute x = 1 and y = 0. Note sin(0) = 0 and e⁰ = 1.
∂x∂g(1,0)=2(1)sin(0)+0⋅e0=0+0=0
Answer: ∂g/∂x = 2x sin(y) + y eˣʸ, which equals 0 at the point (1, 0).
Frequently Asked Questions
What is the difference between a partial derivative and an ordinary derivative?
An ordinary derivative applies to a function of a single variable and measures its total rate of change. A partial derivative applies to a function of two or more variables and measures the rate of change with respect to one variable while holding all others constant. The notation switches from d to ∂ to signal this distinction.
When do you use partial derivatives?
You use partial derivatives whenever a quantity depends on more than one variable and you want to understand how it changes with respect to just one of them. They appear throughout physics (e.g., heat equations, wave equations), economics (e.g., marginal cost with multiple inputs), machine learning (gradient descent), and engineering.
Can you take the partial derivative of a function with respect to a variable that doesn't appear in it?
Yes. If the function does not actually depend on that variable, the partial derivative with respect to it is simply zero. For example, if f(x, y) = 3x², then ∂f/∂y = 0 because x² has no y-dependence.
Partial Derivative vs. Ordinary (Total) Derivative
Partial Derivative
Ordinary (Total) Derivative
Number of variables
Function of two or more variables
Function of one variable
Notation
∂f/∂x (curly d)
df/dx or f′(x)
What stays fixed
All variables except the one being differentiated are held constant
Nothing else to hold constant—there is only one variable
Differentiation rules
Same rules (power, product, chain, etc.), but other variables act as constants
Standard single-variable differentiation rules
Typical course
Multivariable calculus (Calculus III)
Single-variable calculus (Calculus I)
Why It Matters
Partial derivatives are the foundation of multivariable calculus. You will encounter them when computing gradients, finding tangent planes to surfaces, optimizing functions of several variables (like in economics or machine learning), and solving partial differential equations in physics and engineering. Mastering them is essential before studying topics such as the chain rule for multivariable functions, Lagrange multipliers, and vector calculus.
Common Mistakes
Mistake: Treating the other variables as if they also change (differentiating y with respect to x as 1 or dy/dx instead of 0).
Correction: When computing ∂f/∂x, every variable except x is a constant. The derivative of y with respect to x is 0, not 1 and not dy/dx. Only use implicit differentiation (dy/dx) when you are told y depends on x.
Mistake: Using the ordinary derivative symbol d instead of the partial derivative symbol ∂.
Correction: The curly-d notation ∂ signals that other variables are being held constant. Using d can imply a total derivative, which has a different meaning (it accounts for how all variables change). Always use ∂ for partial derivatives.
Related Terms
Derivative — Single-variable version of the same concept
Function — Partial derivatives operate on multivariable functions