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Carlos Sandoval Olascoaga cesandoval

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"moduleid","temperature","relative_humidity","voc","nox","pm1","pm25","pm4","pm10","timestamp"
"868050040248441","39.08499908447266","22.44000053405762",0,0,"2","2.099999904632568","2.099999904632568","2.099999904632568","2023-08-01 14:13:56"
"868050040248441","39.31000137329102","21.04999923706055",0,0,"2.299999952316284","2.400000095367432","2.400000095367432","2.400000095367432","2023-08-01 14:44:28"
"868050040248441","38.90999984741211","21.54999923706055",0,0,"2.700000047683716","3.200000047683716","3.5","3.599999904632568","2023-08-01 15:14:58"
"868050040248441","38.86000061035156","22.63999938964844",0,0,"2.900000095367432","3","3","3","2023-08-01 15:45:29"
"868050040248441","37.5","21.45999908447266",0,0,"1.899999976158142","2","2","2","2023-08-01 16:16:00"
"868050040248441","38.07500076293945","20.70000076293945",0,0,"2.900000095367432","3","3","3","2023-08-01 16:46:30"
"868050040248441","37.67499923706055","21.45999908447266",0,0,"2.099999904632568","2.799999952316284","3.299999952316284","3.5","202
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sprite
from __future__ import print_function, unicode_literals
import random
import logging
import os
os.environ['NLTK_DATA'] = os.getcwd() + '/nltk_data'
from textblob import TextBlob
from config import FILTER_WORDS
city rats
Brookline 40
Boston 90
Cambridge 30
Somerville 60
Watertown 75
Medford 10
Chelsea 55
date rate
Jan 2005 5.3
Feb 2005 5.4
Mar 2005 5.2
Apr 2005 5.2
May 2005 5.1
Jun 2005 5.0
Jul 2005 5.0
Aug 2005 4.9
Sep 2005 5.0
Jan 2005 5.3
Feb 2005 5.4
Mar 2005 5.2
Apr 2005 5.2
May 2005 5.1
Jun 2005 5.0
Jul 2005 5.0
Aug 2005 4.9
Sep 2005 5.0
city rats
Brookline 60
Boston 20
Cambridge 50
Somerville 90
Watertown 60
Medford 40
Chelsea 10
Brookline 40
Boston 90
Cambridge 30
Somerville 60
Watertown 75
Medford 10
Chelsea 55
city rats_2015 coffee_2015 rats_2016 coffee_2016
Somerville 60 40 40 60
Cambridge 30 90 80 100
Boston 90 120 10 30
Brookline 40 50 60 30
Chelsea 10 10 100 120