How many folds on cross validation
The number of folds is nothing you can really calculate. It is more a parameter you choose by good judgement. Typically used values are between 5 and 10, but you can even go up to the so-called leave-one-out cross validation, in which each fold consists of all but one observation. The arguments that guide your decision are typically the following:
- computational cost: the more folds you use, the more computations you need. 
- variance: the more folds you use, the higher the variance of the cross validation result
- bias: the more folds you use, the smaller the bias of the cross validation result.

In your case, depending on the exact context in which you want to apply cross validation, you will probably want to choose between 5 and 10 folds. 

For more details, you might want to consult Kohavi's 1995 paper on cross validation.