HW4 Deception (V2)

STEP 1: Get Data

In [2]:
import os
def get_data(file, path):
    f=open(path+file)
    data = f.read()
    f.close()
    return data
    
def get_data_from_files(path):
    results = [get_data(file, path) for file in os.listdir(path)]
    return results

# pos = get_data_from_files('../pos_cornell//')
# neg = get_data_from_files('../neg_cornell/')
pos = get_data_from_files('../hw4_lie_false/')
neg = get_data_from_files('../hw4_lie_true/')

STEP 1b -- turn it into neg/pos df then merge df

In [3]:
import pandas as pd
neg_df = pd.DataFrame(neg)
pos_df = pd.DataFrame(pos)
pos_df['PoN'] = 'P'
neg_df['PoN'] = 'N'
all_df = neg_df.append(pos_df)
all_df.reset_index(drop=True,inplace=True)
all_df
Out[3]:
0 PoN
0 ? N
1 Twin Trees Cicero NY HUGE salad bar and high q... N
2 The worst restaurant that I have ever eaten in... N
3 ? N
4 I have been to a Asian restaurant in New York ... N
... ... ...
87 Mikes Pizza High Point NY Service was very slo... P
88 After I went shopping with some of my friend w... P
89 I entered the restaurant and a waitress came b... P
90 Carlos Plate Shack was the worst dining experi... P
91 Olive Oil Garden was very disappointing. I exp... P

92 rows × 2 columns

In [24]:
from collections import Counter
from nltk.sentiment.util import *
from nltk.tokenize import casual_tokenize
all_df['pos'] = all_df.apply(lambda x: nltk.pos_tag(Counter(casual_tokenize(x[0]))),axis=1)

def get_pos_list(tuples):
#     print(tuples)
    return [t[1] for t in tuples]
    
all_df['pos_count'] = all_df.apply(lambda x: get_pos_list(x['pos']),axis=1)
all_df['pos_str'] = all_df.apply(lambda x: ' '.join(x['pos_count']),axis=1)

# all_df['pos_no_sw'] = all_df.apply(lambda x: nltk.pos_tag(x['no_sw']),axis=1)
In [32]:
mylist = all_df['pos_str'].tolist()
In [38]:
' '.join(mylist)
Out[38]:
'. NNP NNP NNP NNP NNP NN NN CC JJ NN JJ NNS . DT NN VBZ RB JJ JJ JJ NNP NN TO VB DT JJ NN NN IN RB RB IN PRP VBP VBN IN DT JJ NNS DT JJ NN IN PRP$ NNS JJ VB NN NN DT JJS NN IN PRP VBP RB VBN IN VBZ RB DT NN VBD NNP CC NN . VBD DT NN NN VBD JJ NN WRB DT NN VBD PRP$ NN IN NN PRP VBD RB JJ : CC WRB VBD NN IN WDT VBD RB NN IN NN RB JJ TO IN NN VBD DT NN RB VBP VB NN FW VB DT RB IN VBG JJ NN . PRP VBP VBN TO DT JJ NN IN NNP NNP NN . DT NN VBZ VBN IN NNP CC NNP WRB VBP JJ NNS NN VBN NNP NN VBD JJ NN IN PRP IN NNP NN WDT VBD NN DT JJS NN PRP VBP VBN TO VBZ WRB VBD NNP IN PRP$ NNS DT NN RB RB JJ . NNP JJ VBD JJ RB RB . NN CC JJ WDT VBZ PRP VB VB IN RBR NNS RB VBG VBG IN PDT DT JJ IN VBG NN RB DT NN VBD RB JJ DT NNS IN PRP DT NN CC VBD RB . NN VBD JJ PRP VBD RB IN JJ NN NN VBD JJ NN NN DT NN IN NNP NNP VBD DT JJ NN . 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