Pandas arrays — pandas 1.0.5 documentation (original) (raw)

NumPy cannot natively represent timezone-aware datetimes. Pandas supports this with the arrays.DatetimeArray extension array, which can hold timezone-naive or timezone-aware values.

Timestamp, a subclass of datetime.datetime, is pandas’ scalar type for timezone-naive or timezone-aware datetime data.

Methods

Timestamp.astimezone(self, tz) Convert tz-aware Timestamp to another time zone.
Timestamp.ceil(self, freq[, ambiguous, …]) return a new Timestamp ceiled to this resolution.
Timestamp.combine(date, time) date, time -> datetime with same date and time fields.
Timestamp.ctime() Return ctime() style string.
Timestamp.date() Return date object with same year, month and day.
Timestamp.day_name(self[, locale]) Return the day name of the Timestamp with specified locale.
Timestamp.dst() Return self.tzinfo.dst(self).
Timestamp.floor(self, freq[, ambiguous, …]) return a new Timestamp floored to this resolution.
Timestamp.freq
Timestamp.freqstr Return the total number of days in the month.
Timestamp.fromordinal(ordinal[, freq, tz]) Passed an ordinal, translate and convert to a ts.
Timestamp.fromtimestamp(ts) timestamp[, tz] -> tz’s local time from POSIX timestamp.
Timestamp.isocalendar() Return a 3-tuple containing ISO year, week number, and weekday.
Timestamp.isoformat(self[, sep]) [sep] -> string in ISO 8601 format, YYYY-MM-DDT[HH[:MM[:SS[.mmm[uuu]]]]][+HH:MM].
Timestamp.isoweekday() Return the day of the week represented by the date.
Timestamp.month_name(self[, locale]) Return the month name of the Timestamp with specified locale.
Timestamp.normalize(self) Normalize Timestamp to midnight, preserving tz information.
Timestamp.now([tz]) Return new Timestamp object representing current time local to tz.
Timestamp.replace(self[, year, month, day, …]) implements datetime.replace, handles nanoseconds.
Timestamp.round(self, freq[, ambiguous, …]) Round the Timestamp to the specified resolution.
Timestamp.strftime() format -> strftime() style string.
Timestamp.strptime(string, format) Function is not implemented.
Timestamp.time() Return time object with same time but with tzinfo=None.
Timestamp.timestamp() Return POSIX timestamp as float.
Timestamp.timetuple() Return time tuple, compatible with time.localtime().
Timestamp.timetz() Return time object with same time and tzinfo.
Timestamp.to_datetime64() Return a numpy.datetime64 object with ‘ns’ precision.
Timestamp.to_numpy() Convert the Timestamp to a NumPy datetime64.
Timestamp.to_julian_date(self) Convert TimeStamp to a Julian Date.
Timestamp.to_period(self[, freq]) Return an period of which this timestamp is an observation.
Timestamp.to_pydatetime() Convert a Timestamp object to a native Python datetime object.
Timestamp.today(cls[, tz]) Return the current time in the local timezone.
Timestamp.toordinal() Return proleptic Gregorian ordinal.
Timestamp.tz_convert(self, tz) Convert tz-aware Timestamp to another time zone.
Timestamp.tz_localize(self, tz[, ambiguous, …]) Convert naive Timestamp to local time zone, or remove timezone from tz-aware Timestamp.
Timestamp.tzname() Return self.tzinfo.tzname(self).
Timestamp.utcfromtimestamp(ts) Construct a naive UTC datetime from a POSIX timestamp.
Timestamp.utcnow() Return a new Timestamp representing UTC day and time.
Timestamp.utcoffset() Return self.tzinfo.utcoffset(self).
Timestamp.utctimetuple() Return UTC time tuple, compatible with time.localtime().
Timestamp.weekday() Return the day of the week represented by the date.

A collection of timestamps may be stored in a arrays.DatetimeArray. For timezone-aware data, the .dtype of a DatetimeArray is aDatetimeTZDtype. For timezone-naive data, np.dtype("datetime64[ns]")is used.

If the data are tz-aware, then every value in the array must have the same timezone.

arrays.DatetimeArray(values[, dtype, freq, copy]) Pandas ExtensionArray for tz-naive or tz-aware datetime data.
DatetimeTZDtype([unit, tz]) An ExtensionDtype for timezone-aware datetime data.