Is there a way to generate time range in pandas similar to date_range? something like:
pandas.time_range("11:00", "21:30", freq="30min")
Specifying the valuesSpecify start and end, with the default daily frequency. Specify start and periods, the number of periods (days). Specify end and periods, the number of periods (days). Specify start, end, and periods; the frequency is generated automatically (linearly spaced).
pandas contains extensive capabilities and features for working with time series data for all domains. Using the NumPy datetime64 and timedelta64 dtypes, pandas has consolidated a large number of features from other Python libraries like scikits.
A time range doesn't exist as a standalone index type. Generate using a single date
In [1]: pandas.date_range("11:00", "21:30", freq="30min") Out[1]: <class 'pandas.tseries.index.DatetimeIndex'> [2013-07-14 11:00:00, ..., 2013-07-14 21:30:00] Length: 22, Freq: 30T, Timezone: None
The time objects
In [2]: pandas.date_range("11:00", "21:30", freq="30min").time Out[2]: array([datetime.time(11, 0), datetime.time(11, 30), datetime.time(12, 0), datetime.time(12, 30), datetime.time(13, 0), datetime.time(13, 30), datetime.time(14, 0), datetime.time(14, 30), datetime.time(15, 0), datetime.time(15, 30), datetime.time(16, 0), datetime.time(16, 30), datetime.time(17, 0), datetime.time(17, 30), datetime.time(18, 0), datetime.time(18, 30), datetime.time(19, 0), datetime.time(19, 30), datetime.time(20, 0), datetime.time(20, 30), datetime.time(21, 0), datetime.time(21, 30)], dtype=object)
You can also resample if you are spanning multiple dates.
What are you trying to do?
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