elif month == 'JUN':
return 6
elif month == 'JUL':
return 7
elif month == 'AUG':
return 8
elif month == 'SEP':
return 9
elif month == 'OCT':
return 10
elif month == 'NOV':
return 11
elif month == 'DEC':
return 12
gdb = google_db()
for airline in bob:
for date_obj in bob[airline]:
try:
year = int(date_obj[-4:])
month = int(convert_month_to_num(date_obj[3:6]))
day = int(date_obj[0:2])
except Exception:
continue
print(year, month, day)
timestamp = datetime(year, month, day)
new_data = bob[airline][date_obj]
new_data['timestamp'] = timestamp
gdb.store_data(new_data, date_obj, airline + '_delay_data')
def __init__(self):
setup_credentials()
self.g_db = google_db()
self.g_sa = g_sentiment_analysis()
self.count = 0
if count == 0:
print("UNDEFINED BEHAVIOR!!!!")
print("No data for day ", start, ". Will put zero...")
output.append(0)
else:
avg_sentiment_for_day = sentiment_sum / count
output.append(avg_sentiment_for_day)
start += day
return output
if __name__ == '__main__':
gdb = gdatabase.google_db()
jetblue_sentiment_each_day = extract_sources_label_per_day(gdb, JETBLUE_SENTIMENT_LABELS, START_DAY, END_DAY, 'sentiment')
#other_airline_sentiment_each_day = extract_sources_sentiment_per_day(gdb, OTHER_AIRLINE_SENTIMENT_LABELS, START_DAY, END_DAY, 'sentiment')
normalized_jetblue_sentiment_per_day = []
for i in range(len(jetblue_sentiment_each_day)):
# Positive sentiment for jetblue and all other airlines:
jetblue_sentiment_positive = jetblue_sentiment_each_day[i] + 1
#all_other_sentiment_positive = other_airline_sentiment_each_day[i] + 1
# Normalize jetblue sentiment relative to feedback for all other airlines:
#jetblue_sentiment_normalized = jetblue_sentiment_positive / all_other_sentiment_positive
jetblue_sentiment_normalized = jetblue_sentiment_positive / 1