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问题:
I have two different dates and I want to know the difference in days between them. The format of the date is YYYY-MM-DD.
I have a function that can ADD or SUBTRACT a given number to a date:
def addonDays(a, x): ret = time.strftime("%Y-%m-%d",time.localtime(time.mktime(time.strptime(a,"%Y-%m-%d"))+x*3600*24+3600)) return ret
where A is the date and x the number of days I want to add. And the result is another date.
I need a function where I can give two dates and the result would be an int with date difference in days.
回答1:
Use - to get the difference between two datetime objects and take the days member.
from datetime import datetime def days_between(d1, d2): d1 = datetime.strptime(d1, "%Y-%m-%d") d2 = datetime.strptime(d2, "%Y-%m-%d") return abs((d2 - d1).days)
回答2:
Another short solution:
from datetime import date def diff_dates(date1, date2): return abs(date2-date1).days def main(): d1 = date(2013,1,1) d2 = date(2013,9,13) result1 = diff_dates(d2, d1) print '{} days between {} and {}'.format(result1, d1, d2) print ("Happy programmer's day!") main()
回答3:
I tried the code posted by larsmans above but, there are a couple of problems:
1) The code as is will throw the error as mentioned by mauguerra 2) If you change the code to the following:
... d1 = d1.strftime("%Y-%m-%d") d2 = d2.strftime("%Y-%m-%d") return abs((d2 - d1).days)
This will convert your datetime objects to strings but, two things
1) Trying to do d2 - d1 will fail as you cannot use the minus operator on strings and 2) If you read the first line of the above answer it stated, you want to use the - operator on two datetime objects but, you just converted them to strings
What I found is that you literally only need the following:
import datetime end_date = datetime.datetime.utcnow() start_date = end_date - datetime.timedelta(days=8) difference_in_days = abs((end_date - start_date).days) print difference_in_days
回答4:
Try this:
data=pd.read_csv('C:\Users\Desktop\Data Exploration.csv') data.head(5) first=data['1st Gift'] last=data['Last Gift'] maxi=data['Largest Gift'] l_1=np.mean(first)-3*np.std(first) u_1=np.mean(first)+3*np.std(first) m=np.abs(data['1st Gift']-np.mean(data['1st Gift']))>3*np.std(data['1st Gift']) pd.value_counts(m) l=first[m] data.loc[:,'1st Gift'][m==True]=np.mean(data['1st Gift'])+3*np.std(data['1st Gift']) data['1st Gift'].head() m=np.abs(data['Last Gift']-np.mean(data['Last Gift']))>3*np.std(data['Last Gift']) pd.value_counts(m) l=last[m] data.loc[:,'Last Gift'][m==True]=np.mean(data['Last Gift'])+3*np.std(data['Last Gift']) data['Last Gift'].head()
