# The script MUST include the following function,
# which is the entry point for this module:
# Param<dataframe1>: a pandas.DataFrame
# Param<dataframe2>: a pandas.DataFrame
def azureml_main(dataframe1 = None, dataframe2 = None):
# import required packages
import pandas as pd
import nltk
import numpy as np
# tokenize the review text and store the word corpus
word_dict = {}
token_list = []
nltk.download(info_or_id='punkt', download_dir='C:/users/client/nltk_data')
nltk.download(info_or_id='maxent_treebank_pos_tagger', download_dir='C:/users/client/nltk_data')
for text in dataframe1["tweet_text"]:
tokens = nltk.word_tokenize(text.decode('utf8'))
tagged = nltk.pos_tag(tokens)
# convert feature vector to dataframe object
dataframe_output = pd.DataFrame(tagged, columns=['Output'])
return [dataframe_output]