def export_temporal_data(time_window, start_time, end_time):
fetched_results = get_all_stats()
ids = get_all_foursquare_ids()
venue_dic = {}
for r in ids.keys():
venue_dic[r] = []
cur_time = start_time
"""round time to nearest hour/day/week"""
if time_window == 'hour':
time_window = timedelta(hours=2)
cur_time = cur_time - timedelta(
minutes=cur_time.minute,
seconds=cur_time.second,
microseconds=cur_time.microsecond) + timedelta(hours=1)
elif time_window == 'day':
time_window = timedelta(days=1)
cur_time = cur_time - timedelta(
hours=cur_time.hour,
minutes=cur_time.minute,
seconds=cur_time.second,
microseconds=cur_time.microsecond) + timedelta(days=1)
elif time_window == 'week':
time_window = timedelta(weeks=1)
cur_time = cur_time - timedelta(
hours=cur_time.hour,
minutes=cur_time.minute,
seconds=cur_time.second,
microseconds=cur_time.microsecond) + timedelta(weeks=1)
data_type = 'checkinsCount'
time_list = []
time_list.append('Plaza/Time')
while cur_time > start_time and cur_time <= end_time:
print cur_time
time_list.append(cur_time.hour)
for id in venue_dic.keys():
sql = "select * from venue_stats where id = '" + id + "' and time between '" + str(
cur_time) + "' and '" + str(cur_time + time_window) + "'"
cursor = connect_to_mysql()
cursor.execute(sql)
res = cursor.fetchall()
if len(res) != 0:
tmp = [val[data_type] for val in res]
value = max(tmp) - min(tmp)
else:
value = 0
venue_dic[id].append(value)
cur_time += time_window
f = open('./temporal_2hour.csv', 'wt')
writer = csv.writer(f, quoting=csv.QUOTE_ALL)
writer.writerow(time_list)
for key in venue_dic.keys():
venue_dic[key].insert(0, ids[key])
writer.writerow(venue_dic[key])
print data_type
print time_list
for id in ids.keys():
print ids[id], venue_dic[id]
def main():
foursquare_ids = get_all_foursquare_ids()
print foursquare_ids
venues = {}
cursor = connect_to_mysql()
word_doc_freq = {}
docs = []
names = []
comments_count = []
for id in foursquare_ids:
sql = """select caption from plazas_instaphoto where caption is not NULL and foursquare_venue_id='""" + id + "'"
venue_name = foursquare_ids[id]
venues[venue_name] = {}
cursor.execute(sql)
res = cursor.fetchall()
doc = ""
for r in res:
comments = r['caption']
#comments = json.loads(r['caption'])
for sentence in comments:
#doc += sentence[1]
doc += sentence
docs.append(doc)
names.append(venue_name)
comments_count.append(len(res))
t = TFIDF()
res = t.compute_tfidf(docs)
for i in range(len(res)):
print 'Plaza name : ' + names[i].encode('utf-8', 'ignore')
print 'Comments for this Plaza : ' + str(comments_count[i])
print res[i]
def main():
foursquare_ids = get_all_foursquare_ids()
print foursquare_ids
venues = {}
cursor = connect_to_mysql()
word_doc_freq = {}
docs = []
names = []
comments_count = []
for id in foursquare_ids:
sql = """select caption from plazas_instaphoto where caption is not NULL and foursquare_venue_id='"""+id + "'"
venue_name = foursquare_ids[id]
venues[venue_name] = {}
cursor.execute(sql)
res = cursor.fetchall()
doc = ""
for r in res:
comments = r['caption']
#comments = json.loads(r['caption'])
for sentence in comments:
#doc += sentence[1]
doc += sentence
docs.append(doc)
names.append( venue_name )
comments_count.append( len(res) )
t = TFIDF()
res = t.compute_tfidf(docs)
for i in range(len(res) ):
print 'Plaza name : '+names[i].encode('utf-8','ignore')
print 'Comments for this Plaza : ' + str(comments_count[i])
print res[i]
def checkin_update():
"""Update all the checkin info for each foursquare venue in database"""
add_table_venue_stats()
venue_ids = get_all_foursquare_ids()
client = foursquare.Foursquare(config.foursquare_client_id, client_secret=config.foursquare_client_secret)
for venue_id in venue_ids:
#try:
print venue_id
venue_meta = client.venues(venue_id)
save_venue_stats(venue_meta, venue_id)
def instagram_test():
add_table_venue_photo_instagram()
crawler = VenuePhotoCrawlerInstagram()
foursquare_ids = get_all_foursquare_ids()
#fetched_ids = get_all_photo_fetched_venue_id_instagram()
for foursquare_id in foursquare_ids.keys():
"""NOTICE THIS IS TO AVOID REPEATING FETCHING"""
#if foursquare_id not in fetched_ids:
print foursquare_id, foursquare_ids[foursquare_id]
crawler.grab_photos(foursquare_id)
def instagram_test():
add_table_venue_photo_instagram()
crawler = VenuePhotoCrawlerInstagram()
foursquare_ids = get_all_foursquare_ids()
#fetched_ids = get_all_photo_fetched_venue_id_instagram()
for foursquare_id in foursquare_ids.keys():
"""NOTICE THIS IS TO AVOID REPEATING FETCHING"""
#if foursquare_id not in fetched_ids:
print foursquare_id, foursquare_ids[foursquare_id]
crawler.grab_photos(foursquare_id)
def main():
foursquare_ids = get_all_foursquare_ids()
print foursquare_ids
venues = {}
cursor = connect_to_mysql()
word_doc_freq = {}
global_word_freq = {}
for id in foursquare_ids:
sql = (
"""select comments from venue_photo_instagram where comments is not NULL and foursquare_venue_id='"""
+ id
+ "'"
)
venue_name = foursquare_ids[id]
venues[venue_name] = {}
cursor.execute(sql)
res = cursor.fetchall()
# comments = []
for r in res:
comments = json.loads(r["comments"])
for sentence in comments:
words = tokenize(sentence[1])
for word in words:
if word in global_word_freq:
global_word_freq[word] += 1
else:
global_word_freq[word] = 1
if word in venues[venue_name]:
venues[venue_name][word] += 1
else:
venues[venue_name][word] = 1
for w in venues[venue_name].keys():
if w in word_doc_freq:
word_doc_freq[w] += 1
else:
word_doc_freq[w] = 1
# comments.append( json.loads(r['comments']) )
# print venues[venue_name]
too_common_word = []
for word in sorted(global_word_freq.items(), key=lambda tup: tup[1], reverse=True)[:300]:
too_common_word.append(word[0])
print too_common_word
for venue_name in venues.keys():
word_score = []
words = venues[venue_name]
for word in words:
score = words[word] / (1 + math.log(word_doc_freq[word]))
if word not in too_common_word:
word_score.append((word, score, words[word]))
print venue_name
print sorted(word_score, key=lambda tup: tup[1], reverse=True)[0:20]
def export_temporal_data(time_window, start_time, end_time):
fetched_results = get_all_stats()
ids = get_all_foursquare_ids()
venue_dic = {}
for r in ids.keys():
venue_dic[r] = []
cur_time = start_time
"""round time to nearest hour/day/week"""
if time_window == 'hour':
time_window = timedelta(hours=2)
cur_time = cur_time - timedelta(minutes=cur_time.minute, seconds=cur_time.second, microseconds = cur_time.microsecond) + timedelta(hours=1)
elif time_window == 'day':
time_window = timedelta(days=1)
cur_time = cur_time - timedelta(hours = cur_time.hour, minutes=cur_time.minute, seconds=cur_time.second, microseconds = cur_time.microsecond) + timedelta(days=1)
elif time_window == 'week':
time_window = timedelta(weeks=1)
cur_time = cur_time - timedelta(hours = cur_time.hour, minutes=cur_time.minute, seconds=cur_time.second, microseconds = cur_time.microsecond)+timedelta(weeks=1)
data_type = 'checkinsCount'
time_list = []
time_list.append('Plaza/Time')
while cur_time > start_time and cur_time <= end_time:
print cur_time
time_list.append(cur_time.hour)
for id in venue_dic.keys():
sql = "select * from venue_stats where id = '" + id + "' and time between '" + str(cur_time) + "' and '" + str(cur_time+time_window) +"'"
cursor = connect_to_mysql()
cursor.execute(sql)
res = cursor.fetchall()
if len(res) != 0:
tmp = [val[data_type] for val in res ]
value = max(tmp) - min(tmp)
else:
value = 0
venue_dic[id].append( value )
cur_time+= time_window
f = open('./temporal_2hour.csv', 'wt')
writer = csv.writer(f, quoting=csv.QUOTE_ALL)
writer.writerow( time_list)
for key in venue_dic.keys():
venue_dic[key].insert(0, ids[key])
writer.writerow( venue_dic[key] )
print data_type
print time_list
for id in ids.keys():
print ids[id], venue_dic[id]
def main():
foursquare_ids = get_all_foursquare_ids()
print foursquare_ids
venues = {}
cursor = connect_to_mysql()
word_doc_freq = {}
global_word_freq = {}
for id in foursquare_ids:
sql = """select comments from plazas_instaphoto where comments is not NULL and foursquare_venue_id='""" + id + "'"
venue_name = foursquare_ids[id]
venues[venue_name] = {}
cursor.execute(sql)
res = cursor.fetchall()
for r in res:
comments = json.loads(r['comments'])
for sentence in comments:
words = tokenize(sentence[1])
for word in words:
if word in global_word_freq:
global_word_freq[word] += 1
else:
global_word_freq[word] = 1
if word in venues[venue_name]:
venues[venue_name][word] += 1
else:
venues[venue_name][word] = 1
for w in venues[venue_name].keys():
if w in word_doc_freq:
word_doc_freq[w] += 1
else:
word_doc_freq[w] = 1
too_common_word = set()
for word in sorted(global_word_freq.items(),
key=lambda tup: tup[1],
reverse=True)[:300]:
too_common_word.add(word[0])
for venue_name in venues.keys():
word_score = []
words = venues[venue_name]
for word in words:
score = words[word] / (1 + math.log(word_doc_freq[word]))
if word not in too_common_word:
word_score.append((word, score, words[word]))
print venue_name
print sorted(word_score, key=lambda tup: tup[1], reverse=True)[0:20]
def main():
foursquare_ids = get_all_foursquare_ids()
print foursquare_ids
venues = {}
cursor = connect_to_mysql()
word_doc_freq = {}
global_word_freq = {}
for id in foursquare_ids:
sql = """select caption from plazas_instaphoto where caption is not NULL and foursquare_venue_id='"""+id + "'"
venue_name = foursquare_ids[id]
venues[venue_name] = {}
cursor.execute(sql)
res = cursor.fetchall()
for r in res:
comments = [r['caption']]
for sentence in comments:
words = tokenize(sentence)
for word in words:
if word in global_word_freq:
global_word_freq[word]+=1
else:
global_word_freq[word] = 1
if word in venues[venue_name]:
venues[venue_name][word] += 1
else:
venues[venue_name][word] = 1
for w in venues[venue_name].keys():
if w in word_doc_freq:
word_doc_freq[w]+=1
else:
word_doc_freq[w] = 1
too_common_word = set()
for word in sorted(global_word_freq.items(), key = lambda tup: tup[1], reverse=True)[:300]:
too_common_word.add(word[0])
for venue_name in venues.keys():
word_score = []
words = venues[venue_name]
for word in words:
score = words[word]/(1+math.log(word_doc_freq[word]))
if word not in too_common_word:
word_score.append( (word, score, words[word]) )
print venue_name.encode('utf-8','ignore')
print sorted(word_score, key=lambda tup: tup[1], reverse=True)[0:50]
