Created
June 20, 2015 07:28
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Japanese letter analysis for feature hashing
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# The script MUST contain a function named azureml_main | |
# which is the entry point for this module. | |
# | |
# The entry point function can contain up to two input arguments: | |
# Param<dataframe1>: a pandas.DataFrame | |
# Param<dataframe2>: a pandas.DataFrame | |
# coding: UTF-8 | |
def azureml_main(dataframe1 = None, dataframe2 = None): | |
import numpy as np | |
from pandas import Series, DataFrame | |
import pandas as pd | |
from sklearn.feature_extraction.text import CountVectorizer | |
dy, dx = dataframe1.shape | |
data = [0] * dy | |
namedata = dataframe1["name1"] | |
for y in range(0,dy): | |
line = namedata[y] | |
output_line = ''; | |
x = 0 | |
xe = len(line); | |
while x < xe: | |
if ord(line[x]) >= 128: | |
output_line = output_line + hex(ord(line[x])) + hex(ord(line[x+1])) + hex(ord(line[x+2])) + ' ' | |
x = x + 2 | |
else: | |
output_line = output_line + hex(ord(line[x])) + ' ' | |
x = x + 1 | |
data[y] = output_line | |
dataframe1["name_tx"] = Series(data) | |
# Return value must be of a sequence of pandas.DataFrame | |
return dataframe1, |
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