Convert nominal to numeric variables?
Clustering on categories is not something sklearn can do by default. And assigning sequential values to categories like that certainly won't help - clustering tends to work based on distance, by assigning 0, 1, 2 to Yes, No, Don't Know like that, you are suggesting Yes is 'closer' to No than it is to Don't Know.

I highly recommend having a look at k-modes, a clustering algorithm for categorical data. Essentially it optimises according to how common the set of categories are within the cluster (modes, rather than the means of values). E.g. may find green people carriers (5/6/7 pax) in a cluster, and red sports cars (2/4 pax). 

There is a Python library here, which also has links to some papers describing the algorithm. There is also k-prototypes, which clusters with combined numerical and catagorical data.