shreya-singh-tech

import spacy
import textstat
from textstat.textstat import textstatistics
import pandas as pd
import pysentiment2 as ps
import math
import re
from collections import Counter
import numpy as np

shreya-singh-tech

#program to calculate 9 incides

import spacy
import textstat
from textstat.textstat import textstatistics
#from textstat import legacy_round,neasy_word_set
import pandas as pd
import pysentiment2 as ps
import math
import re

shreya-singh-tech

# read csv data 
df1 = pd.read_csv('/Data_2010_Tsv_all.tsv', sep = '\t')

df1.reset_index(inplace=True)
df1 = df1.rename(columns = {'index':'id'})

value_length_list =[]
for index, row in df1.iterrows():
    value_length_list.append(len(str(row['value']).strip()))

shreya-singh-tech

#program to combine txt.tsv and sub.tsv
import pandas as pd 
   
# read csv data 
df1 = pd.read_csv('/combinedSub_Tsv.tsv', sep = '\t') 
df2 = pd.read_csv('/combinedTxt_Tsv.tsv', sep = '\t')
df1['aciks'] = df1['aciks'].astype(str)
df2_new = df2[['adsh', 'tag', 'series','class','value']].copy()
mask_df = df2_new['tag'].values == 'StrategyNarrativeTextBlock'
# new dataframe 

shreya-singh-tech

from selenium import webdriver
from selenium.webdriver.common.proxy import Proxy, ProxyType

boston_res_info = pd.read_csv("combined_reviews_info13001.csv", encoding='utf-8-sig')
rev_urls = boston_res_info['reviewer_profile'].tolist()

delays = [1,2,3]
delay = np.random.choice(delays)

#keep changing proxy list based on https://sslproxies.org/

shreya-singh-tech

#using random delay for time.sleep()
delays = [7, 4, 6, 2, 10, 19]
delay = np.random.choice(delays)

def get_review(url, res_name, res_address):
    binary = FirefoxBinary('/usr/bin/firefox')
    opts = webdriver.FirefoxOptions()
    opts.add_argument("--headless")
    driver = webdriver.Firefox(firefox_binary=binary, firefox_options=opts )
    driver.get(url)

shreya-singh-tech

def res_scraper(url):
	driver = webdriver.Firefox(options=fireFoxOptions)
	driver.get(url)
	
	t.sleep(1)
	page = driver.page_source
	soup = BeautifulSoup(page, 'lxml')
	soup2 = BeautifulSoup(page, 'html.parser')
	final_data = []

shreya-singh-tech

from bs4 import BeautifulSoup
import requests
from lxml import html  
import csv
import requests
from time import sleep
import re
import argparse
import sys
import pandas as pd