pandas.tseries.offsets.Nano — pandas 2.2.3 documentation (original) (raw)
class pandas.tseries.offsets.Nano#
Offset n nanoseconds.
Parameters:
nint, default 1
The number of nanoseconds represented.
See also
Standard kind of date increment.
Examples
You can use the parameter n to represent a shift of n nanoseconds.
from pandas.tseries.offsets import Nano ts = pd.Timestamp(2022, 12, 9, 15) ts Timestamp('2022-12-09 15:00:00')
ts + Nano(n=1000) Timestamp('2022-12-09 15:00:00.000001')
ts - Nano(n=1000) Timestamp('2022-12-09 14:59:59.999999')
ts + Nano(n=-1000) Timestamp('2022-12-09 14:59:59.999999')
Attributes
| base | Returns a copy of the calling offset object with n=1 and all other attributes equal. |
|---|---|
| delta | |
| freqstr | Return a string representing the frequency. |
| kwds | Return a dict of extra parameters for the offset. |
| n | |
| name | Return a string representing the base frequency. |
| nanos | Return an integer of the total number of nanoseconds. |
| normalize | |
| rule_code |
Methods
| copy() | Return a copy of the frequency. |
|---|---|
| is_anchored() | (DEPRECATED) Return False. |
| is_month_end(ts) | Return boolean whether a timestamp occurs on the month end. |
| is_month_start(ts) | Return boolean whether a timestamp occurs on the month start. |
| is_on_offset(dt) | Return boolean whether a timestamp intersects with this frequency. |
| is_quarter_end(ts) | Return boolean whether a timestamp occurs on the quarter end. |
| is_quarter_start(ts) | Return boolean whether a timestamp occurs on the quarter start. |
| is_year_end(ts) | Return boolean whether a timestamp occurs on the year end. |
| is_year_start(ts) | Return boolean whether a timestamp occurs on the year start. |
| rollback(dt) | Roll provided date backward to next offset only if not on offset. |
| rollforward(dt) | Roll provided date forward to next offset only if not on offset. |