from subprocess import check_output

import sqlite3

import numpy as np
import pandas as pd
import sqlite3
import nltk
import numpy as np
from sklearn.feature_extraction.text import CountVectorizer
import scipy
from subprocess import check_output
print(check_output(['ls', '../input']).decode('utf8'))
con = sqlite3.connect('../input/database.sqlite')
cur = con.cursor()
sqlString = ' \n            SELECT complaint_id, product, consumer_complaint_narrative, company\n            FROM consumer_complaints\n            WHERE product = "Mortgage" AND \n                            consumer_complaint_narrative != ""\n            '
cur.execute(sqlString)
complaints = cur.fetchall()
con.close()