python - Convert Bitstring (String of 1 and 0s) to numpy array -

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i have pandas dataframe containing 1 columns contains string of bits eg.'100100101'. want convert string numpy array.

how can that?

edit:

using

features = df.bit.apply(lambda x: np.array(list(map(int,list(x))))) #... model.fit(features, lables)

leads error on model.fit:

valueerror: setting array element sequence.

the solution works case came due marked answer:

for bitstring in input_table['bitstring'].values:     bits = np.array(map(int, list(bitstring)))     featurelist.append(bits) features = np.array(featurelist) #.... model.fit(features, lables)

for string s = "100100101", can convert numpy array @ least 2 different ways.

the first using numpy's fromstring method. bit awkward, because have specify datatype , subtract out "base" value of elements.

import numpy np  s = "100100101" = np.fromstring(s,'u1') - ord('0')  print  # [1 0 0 1 0 0 1 0 1]

where 'u1' datatype , ord('0') used subtract "base" value each element.

the second way converting each string element integer (since strings iterable), passing list np.array:

import numpy np  s = "100100101" b = np.array(map(int, s))  print b  # [1 0 0 1 0 0 1 0 1]

then

# see numpy array: print type(a)  # <type 'numpy.ndarray'> print a[0]     # 1 print a[1]     # 0 # ...

note second approach scales worse first length of input string s increases. small strings, it's close, consider timeit results strings of 90 characters (i used s * 10):

fromstring: 49.283392424 s map/array:   2.154540959 s

(this using default timeit.repeat arguments, minimum of 3 runs, each run computing time run 1m string->array conversions)


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