Python generate dates series
Question:
How can i generate array with dates like this:
Timestamps in javascript miliseconds format from 2010.12.01 00:00:00 to 2010.12.12.30 23.59.59
with step 5 minutes.
['2010.12.01 00:00:00', '2010.12.01 00:05:00','2010.12.01 00:10:00','2010.12.01 00:15:00', ...]
Answers:
Well, obviously you start at the start time, loop until you reach the end time and increment inbetween.
import datetime
dt = datetime.datetime(2010, 12, 1)
end = datetime.datetime(2010, 12, 30, 23, 59, 59)
step = datetime.timedelta(seconds=5)
result = []
while dt < end:
result.append(dt.strftime('%Y-%m-%d %H:%M:%S'))
dt += step
Fairly trivial.
this is my variant for python3, but it’s easy could be converted into python2.6 code:
import datetime as dt
dt1 = dt.datetime(2010, 12, 1)
dt2 = dt.datetime(2010, 12, 12, 23, 59, 59)
time_step = 5 # secoonds
delta = dt2 - dt1
delta_sec = delta.days * 24 * 60 * 60 + delta.seconds
res = [dt1 + dt.timedelta(0, t) for t in range(0, delta_sec, time_step)]
I just felt that it might be worthwhile to note that pandas
also has this functionality. Depending on what case you are dealing with exactly, pandas might be a worthy tool to invest time in.
import pandas as pd
times = pd.date_range('2012-10-01', periods=289, freq='5min')
This returns a pandas timeseries-index. Which can be converted to numpy arrays.
np.array(times)
How can i generate array with dates like this:
Timestamps in javascript miliseconds format from 2010.12.01 00:00:00 to 2010.12.12.30 23.59.59
with step 5 minutes.
['2010.12.01 00:00:00', '2010.12.01 00:05:00','2010.12.01 00:10:00','2010.12.01 00:15:00', ...]
Well, obviously you start at the start time, loop until you reach the end time and increment inbetween.
import datetime
dt = datetime.datetime(2010, 12, 1)
end = datetime.datetime(2010, 12, 30, 23, 59, 59)
step = datetime.timedelta(seconds=5)
result = []
while dt < end:
result.append(dt.strftime('%Y-%m-%d %H:%M:%S'))
dt += step
Fairly trivial.
this is my variant for python3, but it’s easy could be converted into python2.6 code:
import datetime as dt
dt1 = dt.datetime(2010, 12, 1)
dt2 = dt.datetime(2010, 12, 12, 23, 59, 59)
time_step = 5 # secoonds
delta = dt2 - dt1
delta_sec = delta.days * 24 * 60 * 60 + delta.seconds
res = [dt1 + dt.timedelta(0, t) for t in range(0, delta_sec, time_step)]
I just felt that it might be worthwhile to note that pandas
also has this functionality. Depending on what case you are dealing with exactly, pandas might be a worthy tool to invest time in.
import pandas as pd
times = pd.date_range('2012-10-01', periods=289, freq='5min')
This returns a pandas timeseries-index. Which can be converted to numpy arrays.
np.array(times)