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@rosiel
Created September 7, 2017 15:44
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Hypothesis: it's more likely to be cloudy given that yesterday was cloudy, than that the day before yesterday was cloudy.
#!/usr/local/bin/python3
import csv
dates = []
cloudyvalues = []
pattern = []
pattern3 = []
thisdate = '11-5-2005'
thissky = []
counter = 1
with open ('data.csv', 'r') as csvfile:
myreader = csv.reader(csvfile, delimiter=',')
for row in myreader:
counter = counter + 1
if counter > 100000:
break
[date, time] = row[0].split(' ')
if time not in set(['20:00:00', '21:00:00', '22:00:00']):
continue
if not date.startswith('9'):
continue
if date != thisdate:
# Evaluate the last cloudiness and clear it
cloudy = 0
for value in thissky:
if value < 5:
cloudy = 1
dates.append(date)
if len(cloudyvalues) > 0:
pattern.append(str(cloudyvalues[-1]) + str(cloudy))
if len(cloudyvalues) > 1:
pattern3.append(str(cloudyvalues[-2]) + str(cloudy))
cloudyvalues.append(cloudy)
thissky = []
thisdate = date
thissky.append(int(row[2]))
for i in range(len(pattern3)):
print(dates[i], pattern3[i])
print("Total days counted: ", len(dates))
print("Cloudy days counted: ", cloudyvalues.count(1))
print("P(cloudy): ", cloudyvalues.count(1)/len(dates))
print("\n")
print("Total days after cloudy days: ", pattern.count('11') + pattern.count('10'))
print("Cloudy days following cloudy days: ", pattern.count('11'))
print("P(cloudy|yesterday was cloudy): ", pattern.count('11') / (pattern.count('11') + pattern.count('10')))
print("\n")
print("Total days, where before yesterday was cloudy: ", pattern3.count('11') + pattern3.count('10'))
print("Cloudy days where before yesterday was cloudy: ", pattern3.count('11'))
print("P(cloudy|before yesterday was cloudy): ", pattern3.count('11') / (pattern3.count('11') + pattern3.count('10')))
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