Understanding transition from full derivative to partial

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SUMMARY

This discussion clarifies the distinction between full derivatives and partial derivatives in the context of transitioning from Cartesian to cylindrical and spherical coordinates. The key point is that while implicit differentiation can yield the same result for independent variables, this equivalence breaks down when variables are dependent. The example provided with the function f(x,y) = xy illustrates that when y is treated as a constant, the partial derivative matches the full derivative, but this is not the case when y is a function of x, such as y = x^3. Thus, the relationship between full and partial derivatives is contingent on the independence of the variables involved.

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  • Understanding of partial derivatives and full derivatives
  • Familiarity with implicit differentiation techniques
  • Basic knowledge of Cartesian, cylindrical, and spherical coordinate systems
  • Experience with multivariable calculus concepts
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  • Learn about the chain rule in the context of partial derivatives
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TheCanadian
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I was looking over a derivation to find the laplacian from cartesian to cylindrical and spherical coordinates here: http://skisickness.com/2009/11/20/

Everything seems fine, but there is an instance (I have attached a screenshot) where implicit differentiation is done to find $$ \frac {\partial \phi}{\partial x} $$ by finding $$ \frac {d\phi}{dx} $$ implicitly and then equating this to $$ \frac {\partial \phi}{\partial x} $$ It seems like they are two separate equations. In this instance, x was independent of y, but in a future scenario, if x and y were dependent (e.g. y = kx), then the implicit differentiation would give a different result, right? In that case, would this approach work to still give $$ \frac {d\phi}{dx} = \frac {\partial \phi}{\partial x} {\text ?}$$

I understand the strategy based on the above equation (in the link) where they are trying to find each respective partial derivative to go from cartesian to cylindrical coordinates, but equating the full derivative to the partial derivative seems a little off. It looks like it works in this particular case because x and y are independent, but if they were dependent, would this approach work?
 

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It might help to look at a really simple example, like ## f(x,y)=xy ##. Then implicit differentiation wrt ## x ## gives ## df = ydx ##. But this change in ## f ## assumes ## y ## is held constant, so a better way to write it might be ## (df)_y = y (dx) ##. Then "dividing through by ## dx ##" just yields ##\frac{\partial f}{\partial x} = y##. If ## y ## doesn't depend on ## x ## then ##\frac{dy}{dx}=0 ##, so that ## \frac{df}{dx}=\frac{\partial f}{\partial x}+\frac{\partial f}{\partial y}\frac{dy}{dx}=\frac{\partial f}{\partial x}=y##.

An important thing to keep in mind is that partial derivatives don't "care" about functional relationships that may exist between the arguments. Let's take the previous example but suppose that ## y ## depends on ## x ## this time as, say, ## y = x^3 ##. We would still have ## \frac{\partial f}{\partial x} = y ##. On the other hand, we would now write ## \frac{df}{dx} = \frac{\partial f}{\partial x}+\frac{\partial f}{\partial y}\frac{dy}{dx} = y + 3x^3 = 4x^3. ## Because ## \frac{\partial f}{\partial x} = y = x^3 ##, we no longer have ## \frac{\partial f}{\partial x}=\frac{df}{dx}##.
 
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