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Alex Rivera
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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?
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