How to replace the character with a dictionary value in the numpy array?
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How to replace the character with a dictionary value in the numpy array?
I want to replace characters in a numpy array to specific values in dictionary. For example I want to replace 6837 to fhcg in the same array format.
This is what I tried
import numpy
val=numpy.array([["6837"],["7628"],["3804"],["3031"],["9848"],["8481"],["1220"],["7701"],["7934"]])
d={'1':'a','2':'b','3':'c','4':'d','5':'e','6':'f','7':'g','8':'h','9':'i','0':'x'}
rep = [d[v] for v in val]
new_val= ' '.join(rep)
But its giving this error
TypeError: unhashable type: 'numpy.ndarray'
Your val array is 2d, so you have to be careful how you iterate on it.
In [255]: val.shape
Out[255]: (9, 1)
Let's define a little function that converts one string; the conversion is character by character - it's a pure string operation.
def foo(astr):
return ''.join([d[v] for v in astr])
We could use this in a list comprehension or other iterator. But this is one case where np.vectorize does a nice job.
In [257]: f = np.vectorize(foo)
In [258]: f(val)
Out[258]:
array([['fhcg'],
['gfbh'],
['chxd'],
['cxca'],
['ihdh'],
['hdha'],
['abbx'],
['ggxa'],
['gicd']],
dtype='<U4')
It does iterate on the array, so doesn't offer much of a speed advantage, but it takes care of 'broadcasting', handling the 2d array without extra work on our part.
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