每半小时可以使用熊猫TimeDeltaIndex，PeriodIndex或DateTimeIndex吗？

Question

I have a table of data values that should be indexed with half-hourly intervals, and I've been processing them with Pandas and Numpy. Currently they're in CSV files and I import them using read_csv to a dataframe with only the interval-endpoint as an index. I am uncomfortable with that and want to have the intervals themselves as the index.

I do not know whether to use a DateTimeIndex , a PeriodIndex or a TimedeltaIndex ... All of them seem very similar in practice, to me. My operations include

• Looking up a particular interval
• Checking if a DateTime is contained in a particular interval
• Intersection and (Set)Difference of intervals
• Split and join intervals

Can Pandas even do all of these? Is it advisable? I already am using this interval library , would using Pandas tslib and period be better?

Answer 1

if you only need a series with time interval of 30 minutes you can do this:

import pandas as pd
import datetime as dt

today = dt.datetime.date()
yesterday = dt.datetime.date()-dt.timedelta(days=1)
time_range = pd.date_range(yesterday,today, freq='30T')

now you could use it to set an index such has

pd.DataFrame(0, index=time_range,columns=['yourcol'])

Out[35]: 
                     yourcol
2016-09-25 00:00:00        0
2016-09-25 00:30:00        0
2016-09-25 01:00:00        0
2016-09-25 01:30:00        0
2016-09-25 02:00:00        0

this would be a DateTimeIndex

you can read more about time interval in pandas here: http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases