pandas.DatetimeIndex   classpandas.DatetimeIndex(data=None, freq=NoDefault.no_default, tz=None, normalize=False, closed=None, ambiguous='raise', dayfirst=False, yearfirst=False, dtype=None, copy=False, name=None)[source]
 
Immutable ndarray-like of datetime64 data. Represented internally as int64, and which can be boxed to Timestamp objects that are subclasses of datetime and carry metadata.  Parameters 
 
data:array-like (1-dimensional), optional


Optional datetime-like data to construct index with.  
freq:str 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.  
tz:pytz.timezone or dateutil.tz.tzfile or datetime.tzinfo or str


Set the Timezone of the data.  
normalize:bool, default False


Normalize start/end dates to midnight before generating date range.  
closed:{‘left’, ‘right’}, optional


Set whether to include start and end that are on the boundary. The default includes boundary points on either end.  
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.   
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.  
dtype:numpy.dtype or DatetimeTZDtype or str, default None


Note that the only NumPy dtype allowed is ‘datetime64[ns]’.  
copy:bool, default False


Make a copy of input ndarray.  
name:label, default None


Name to be stored in the index.      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. Attributes       
year The year of the datetime.  
month The month as January=1, December=12.  
day The day 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.  
time Returns numpy array of datetime.time objects.  
timetz Returns numpy array of datetime.time objects with timezone information.  
dayofyear The ordinal day of the year.  
day_of_year The ordinal day of the year.  
weekofyear (DEPRECATED) The week ordinal of the year.  
week (DEPRECATED) The week ordinal of the year.  
dayofweek The day of the week with Monday=0, Sunday=6.  
day_of_week 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.  
tz Return the timezone.  
freq Return the frequency object if it is set, otherwise None.  
freqstr Return the frequency object as a string if its 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 Tries to return a string representing a frequency guess, generated by infer_freq.    Methods       
normalize(*args, **kwargs) Convert times to midnight.  
strftime(*args, **kwargs) Convert to Index using specified date_format.  
snap([freq]) Snap time stamps to nearest occurring frequency.  
tz_convert(tz) Convert tz-aware Datetime Array/Index from one time zone to another.  
tz_localize(tz[, ambiguous, nonexistent]) Localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index.  
round(*args, **kwargs) Perform round operation on the data to the specified freq.  
floor(*args, **kwargs) Perform floor operation on the data to the specified freq.  
ceil(*args, **kwargs) Perform ceil operation on the data to the specified freq.  
to_period(*args, **kwargs) Cast to PeriodArray/Index at a particular frequency.  
to_perioddelta(freq) Calculate TimedeltaArray of difference between index values and index converted to PeriodArray at specified freq.  
to_pydatetime(*args, **kwargs) Return Datetime Array/Index as object ndarray of datetime.datetime objects.  
to_series([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([index, name]) Create a DataFrame with a column containing the Index.  
month_name(*args, **kwargs) Return the month names of the DateTimeIndex with specified locale.  
day_name(*args, **kwargs) Return the day names of the DateTimeIndex with specified locale.  
mean(*args, **kwargs) Return the mean value of the Array.  
std(*args, **kwargs) Return sample standard deviation over requested axis.