CODEWITHSUNDEEP
pythontimepandas
Nilani Algiriyage
Nilani Algiriyage

Reputation: 35776

Calculate time difference in minutes

I'm reading a text file which has time(hours and minutes) and IP addresses. Then I want to get the time differences and do some activity for every 5 minutes. Following code does not calculate the time difference.

sample text file:

06:03 65.55.215.62
06:04 157.56.92.152
06:04 66.249.74.175
06:05 173.199.116.171

code:

time_ip = []
for line in open('minutes'):
    time_ip.append(line.split(' '))    

df = pandas.DataFrame(time_ip)
df['tvalue'] = df[0]
df['delta'] = (df['tvalue']-df['tvalue'])

Upvotes: 1

Views: 1743

Answers (3)

Andy Hayden
Andy Hayden

Reputation: 375915

You should use read_csv to read a csv into a DataFrame:

In [1]: df = pd.read_csv(file_name, sep='\s+', header=None, names=['time', 'ip'])

In [2]: df
Out[2]:
    time               ip
0  06:03     65.55.215.62
1  06:04    157.56.92.152
2  06:04    66.249.74.175
3  06:05  173.199.116.171

Pandas doesn't (yet) have any built in time object, and doing this in python isn't the easy... you can make the time column of time objects:

In [3]: df['time'] = df['time'].apply(lambda x: datetime.time(*map(int, x.split(':'))))

In [4]: df
Out[4]:
       time               ip
0  06:03:00     65.55.215.62
1  06:04:00    157.56.92.152
2  06:04:00    66.249.74.175
3  06:05:00  173.199.116.171

Not least because you can't do arithmetic on datetime.time objects. At any rate, I think you're going to get into a sticky situation by not having the year/month/day here too, for one thing, how to deal with the midnight?

So let's start again, assuming you had a datetime...

In [5]: df = pd.read_csv(file_name, sep='\s+', header=None, names=['time', 'ip'])

In [6]: df['time'] = pd.to_datetime(df['time'])  # let's use todays

In [7]: df
Out[7]:
                 time               ip
0 2013-06-12 06:03:00     65.55.215.62
1 2013-06-12 06:04:00    157.56.92.152
2 2013-06-12 06:04:00    66.249.74.175
3 2013-06-12 06:05:00  173.199.116.171

Then you can grab out the difference using a shift:

In [8]: df['time'].shift()
Out[8]:
0                   NaT
1   2013-06-12 06:03:00
2   2013-06-12 06:04:00
3   2013-06-12 06:04:00
Name: time, dtype: datetime64[ns]

In [9]: d['time'] - df['time'].shift()
Out[9]:
0        NaT
1   00:01:00
2   00:00:00
3   00:01:00
Name: time, dtype: timedelta64[ns]

Much easier. :)

Upvotes: 1

TerryA
TerryA

Reputation: 60024

You can use the datetime module

import datetime
with open('minutes', 'r') as myfile:
    times = myfile.read().split()[::2]
dates = [datetime.datetime.strptime(i, '%H:%M') for i in times]
differences = [j-i for i, j in zip(dates[:-1], dates[1:])]
print [divmod(i.seconds, 60)[0] for i in differences]

Prints:

[1, 0, 1]

Upvotes: 0

Atul Arvind
Atul Arvind

Reputation: 16763

>>> import datetime
>>> end = datetime.datetime.now()
>>> start = datetime.datetime.now()
>>> diff
datetime.timedelta(0, 7, 424199)
>>> diff = start - end
>>> divmod(diff.days * 86400 + diff.seconds, 60)
(0, 7) # 0 minutes, 7 seconds

Upvotes: 0

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