pandas.DatetimeIndex¶
-
class
pandas.
DatetimeIndex
[source]¶ Immutable ndarray of datetime64 data, represented internally as int64, and which can be boxed to Timestamp objects that are subclasses of datetime and carry metadata such as frequency information.
Parameters: - data : array-like (1-dimensional), optional
Optional datetime-like data to construct index with
- copy : bool
Make a copy of input ndarray
- freq : string or pandas offset object, optional
One of pandas date offset strings or corresponding objects. The string ‘infer’ can be passed in order to set the frequency of the index as the inferred frequency upon creation
- start : starting value, datetime-like, optional
If data is None, start is used as the start point in generating regular timestamp data.
Deprecated since version 0.24.0.
- periods : int, optional, > 0
Number of periods to generate, if generating index. Takes precedence over end argument
Deprecated since version 0.24.0.
- end : end time, datetime-like, optional
If periods is none, generated index will extend to first conforming time on or just past end argument
Deprecated since version 0.24.0.
- closed : string or None, default None
Make the interval closed with respect to the given frequency to the ‘left’, ‘right’, or both sides (None)
Deprecated since version 0.24.: 0
- tz : pytz.timezone or dateutil.tz.tzfile
- ambiguous : ‘infer’, bool-ndarray, ‘NaT’, default ‘raise’
When clocks moved backward due to DST, ambiguous times may arise. For example in Central European Time (UTC+01), when going from 03:00 DST to 02:00 non-DST, 02:30:00 local time occurs both at 00:30:00 UTC and at 01:30:00 UTC. In such a situation, the ambiguous parameter dictates how ambiguous times should be handled.
- ‘infer’ will attempt to infer fall dst-transition hours based on order
- bool-ndarray where True signifies a DST time, False signifies a non-DST time (note that this flag is only applicable for ambiguous times)
- ‘NaT’ will return NaT where there are ambiguous times
- ‘raise’ will raise an AmbiguousTimeError if there are ambiguous times
- name : object
Name to be stored in the index
- dayfirst : bool, default False
If True, parse dates in data with the day first order
- yearfirst : bool, default False
If True parse dates in data with the year first order
See also
Index
- The base pandas Index type.
TimedeltaIndex
- Index of timedelta64 data.
PeriodIndex
- Index of Period data.
to_datetime
- Convert argument to datetime.
date_range
- Create a fixed-frequency DatetimeIndex.
Notes
To learn more about the frequency strings, please see this link.
Creating a DatetimeIndex based on start, periods, and end has been deprecated in favor of
date_range()
.Attributes
year
The year of the datetime. month
The month as January=1, December=12. day
The days of the datetime. hour
The hours of the datetime. minute
The minutes of the datetime. second
The seconds of the datetime. microsecond
The microseconds of the datetime. nanosecond
The nanoseconds of the datetime. date
Returns numpy array of python datetime.date objects (namely, the date part of Timestamps without timezone information). time
Returns numpy array of datetime.time. timetz
Returns numpy array of datetime.time also containing timezone information. dayofyear
The ordinal day of the year. weekofyear
The week ordinal of the year. week
The week ordinal of the year. dayofweek
The day of the week with Monday=0, Sunday=6. weekday
The day of the week with Monday=0, Sunday=6. quarter
The quarter of the date. freq
Return the frequency object if it is set, otherwise None. freqstr
Return the frequency object as a string if it is set, otherwise None. is_month_start
Indicates whether the date is the first day of the month. is_month_end
Indicates whether the date is the last day of the month. is_quarter_start
Indicator for whether the date is the first day of a quarter. is_quarter_end
Indicator for whether the date is the last day of a quarter. is_year_start
Indicate whether the date is the first day of a year. is_year_end
Indicate whether the date is the last day of the year. is_leap_year
Boolean indicator if the date belongs to a leap year. inferred_freq
Tryies to return a string representing a frequency guess, generated by infer_freq. tz Methods
normalize
(self, \*args, \*\*kwargs)Convert times to midnight. strftime
(self, \*args, \*\*kwargs)Convert to Index using specified date_format. snap
(self[, freq])Snap time stamps to nearest occurring frequency tz_convert
(self, \*args, \*\*kwargs)Convert tz-aware Datetime Array/Index from one time zone to another. tz_localize
(self, \*args, \*\*kwargs)Localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index. round
(self, \*args, \*\*kwargs)Perform round operation on the data to the specified freq. floor
(self, \*args, \*\*kwargs)Perform floor operation on the data to the specified freq. ceil
(self, \*args, \*\*kwargs)Perform ceil operation on the data to the specified freq. to_period
(self, \*args, \*\*kwargs)Cast to PeriodArray/Index at a particular frequency. to_perioddelta
(self, \*args, \*\*kwargs)Calculate TimedeltaArray of difference between index values and index converted to PeriodArray at specified freq. to_pydatetime
(self, \*args, \*\*kwargs)Return Datetime Array/Index as object ndarray of datetime.datetime objects to_series
(self[, keep_tz, index, name])Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index to_frame
(self[, index, name])Create a DataFrame with a column containing the Index. month_name
(self, \*args, \*\*kwargs)Return the month names of the DateTimeIndex with specified locale. day_name
(self, \*args, \*\*kwargs)Return the day names of the DateTimeIndex with specified locale. mean
(self, \*args, \*\*kwargs)Return the mean value of the Array.