Forced conversion of non-numeric numpy arrays with NAN replacement

Consider the array

x = np.array(['1', '2', 'a'])

Tying to convert to a float array raises an exception

x.astype(np.float)
ValueError: could not convert string to float: a

Does numpy provide any efficient way to coerce this into a numeric array, replacing non-numeric values with something like NAN?

Alternatively, is there an efficient numpy function equivalent to np.isnan, but which also tests for non-numeric elements like letters?