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Question

I have a large string array which i store as an nparray named np_base: np.shape(np_base) Out[32]: (65000000, 1)

what i intend to do is to vertically slice the array in order to decompose it into multiple columns that i'll store later in an independant way, so i tried to loop over the row indexes and to append:

for i in range(65000000): INCDN.append(np.base[i, 0][0:5]) but this trhows out a memory error.

Could anybody please help me out with this issue, i've been searching for days for an alternative way to slice the string array.

Thanks,

Answer 1

There are many ways to apply a function to a numpy array one of which is the following:

np_truncated = np.vectorize(lambda x: x[:5])(np_base)

Your approach with iterativly appending a list is usally the least perfomed solution in most contexts.

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Alternatively, if you intent to work with many columns, you might want to use pandas .

import pandas as pd    
df = pd.DataFrame(np_base, columns=["Raw"])
truncated = df.Raw.str.slice(0,5)