Map a NumPy array of strings to integers
You can use np.unique with the return_inverse argument:
>>> lookupTable, indexed_dataSet = np.unique(dataSet, return_inverse=True)>>> lookupTablearray(['george', 'greg', 'kevin'], dtype='<U21')>>> indexed_dataSetarray([2, 1, 0, 2])If you like, you can reconstruct your original array from these two arrays:
>>> lookupTable[indexed_dataSet]array(['kevin', 'greg', 'george', 'kevin'], dtype='<U21')If you use pandas, lookupTable, indexed_dataSet = pd.factorize(dataSet) will achieve the same thing (and potentially be more efficient for large arrays).
np.searchsorted does the trick:
dataSet = np.array(['kevin', 'greg', 'george', 'kevin'], dtype='U21'), lut = np.sort(np.unique(dataSet)) # [u'george', u'greg', u'kevin']ind = np.searchsorted(lut,dataSet) # array([[2, 1, 0, 2]])