1 Determining Parameter Ranges for Scikit-learn's GridSearchCV

I asked this yesterday in /r/learnpython but with no responses so I am trying again here.

I am playing with Scikit-learn for the first time. I have a little bit of machine learning experience but am in no way an expert. One of the interesting tools I see is GridSearchCV so I don't have to manually try different combinations and permutations of parameters.

So following this as a tutorial and guide I can see how to implement the function. What I am curious is how do you know within what ranges do you try values for the different parameters.

For example if I am trying to train C in my SVM we can look at the SVC documents

But all it says is:

C : float, optional (default=1.0)

Penalty parameter C of the error term.

So I have no idea if I should be trying positive numbers, negative numbers, in [0.0, 1.0], if I should be trying 0.1, 0.01, 0.001, etc or if I should be going larger in trying 9, 99, 999, 9999.

Obviously I could enter in all those different numbers in the parmeter value of GridSearchCV (but there are literally infinite) so I am wondering if there is a more intuitive way to find the realistic ranges of values to try for different parameters?