I have a csv file like that
Meme1, Meme2, Meme3, Meme4, Meme5, Meme6 Meme1, Meme2, Meme3, Meme99, Meme5, Meme6 Meme5, Meme2, Meme2, Meme4, Meme10, Meme6 Meme99, Meme3, Meme4, Meme4, Meme5, Meme6
I want like that
00000001, 00000010, 00000011, 00000100, 00000101, 00000110 00000001, 00000010, 01100011, 00000100, 00000101, 00000110 00000100, 00000010, 00000010, 00000100, 00001010, 00000110
means every integer should be converted to binary and word meme should be deleted
I am trying but cannot do:( import pandas as pd import csv import numpy as np dataset = pd.read_csv('datsetcoma.txt') reader = csv.DictReader(dataset) print (reader) # print back the headers for row in reader: if row.is_integer: b=np.binary_repr(10, width=8) print (b)
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Answer
You can also try this:
import pandas as pd import numpy as np import io # example taken from @ifly6 df = pd.read_csv(io.StringIO('''Meme1, Meme2, Meme3, Meme4, Meme5, Meme6 Meme1, Meme2, Meme3, Meme99, Meme5, Meme6 Meme5, Meme2, Meme2, Meme4, Meme10, Meme6 Meme99, Meme3, Meme4, Meme4, Meme5, Meme6'''), header=None) df.apply(lambda x: x.apply(lambda y: bin(int(y.replace('Meme', '')))[2:].zfill(8) ) ) #output 0 1 2 3 4 5 0 00000001 00000010 00000011 00000100 00000101 00000110 1 00000001 00000010 00000011 01100011 00000101 00000110 2 00000101 00000010 00000010 00000100 00001010 00000110 3 01100011 00000011 00000100 00000100 00000101 00000110