pandas.arrays.DatetimeArray

class pandas.arrays.DatetimeArray(values, dtype=dtype('<M8[ns]'), freq=None, copy=False)

Pandas ExtensionArray for tz-naive or tz-aware datetime data.

New in version 0.24.0.

Parameters:

values : Series, Index, DatetimeArray, ndarray

The datetime data.

For DatetimeArray values (or a Series or Index boxing one), dtype and freq will be extracted from values, with precedence given to

dtype : numpy.dtype or DatetimeTZDtype

Note that the only NumPy dtype allowed is ‘datetime64[ns]’.

freq : str or Offset, optional

copy : bool, default False

Whether to copy the underlying array of values.

Attributes

asi8	Integer representation of the values.
date	Returns numpy array of python datetime.date objects (namely, the date part of Timestamps without timezone information).
day	The days of the datetime.
dayofweek	The day of the week with Monday=0, Sunday=6.
dayofyear	The ordinal day of the year.
days_in_month	The number of days in the month.
daysinmonth	The number of days in the month.
dtype	The dtype for the DatetimeArray.
freq	Return the frequency object if it is set, otherwise None.
freqstr	Return the frequency object as a string if its set, otherwise None
hour	The hours of the datetime.
inferred_freq	Tryies to return a string representing a frequency guess, generated by infer_freq.
is_leap_year	Boolean indicator if the date belongs to a leap year.
is_month_end	Indicates whether the date is the last day of the month.
is_month_start	Indicates whether the date is the first day of the month.
is_normalized	Returns True if all of the dates are at midnight (“no time”)
is_quarter_end	Indicator for whether the date is the last day of a quarter.
is_quarter_start	Indicator for whether the date is the first day of a quarter.
is_year_end	Indicate whether the date is the last day of the year.
is_year_start	Indicate whether the date is the first day of a year.
microsecond	The microseconds of the datetime.
minute	The minutes of the datetime.
month	The month as January=1, December=12.
nanosecond	The nanoseconds of the datetime.
nbytes	The number of bytes needed to store this object in memory.
quarter	The quarter of the date.
resolution	Returns day, hour, minute, second, millisecond or microsecond
second	The seconds of the datetime.
shape	Return a tuple of the array dimensions.
size	The number of elements in this array.
time	Returns numpy array of datetime.time.
timetz	Returns numpy array of datetime.time also containing timezone information.
tz	Return timezone, if any.
tzinfo	Alias for tz attribute
week	The week ordinal of the year.
weekday	The day of the week with Monday=0, Sunday=6.
weekday_name	(DEPRECATED) The name of day in a week (ex: Friday)
weekofyear	The week ordinal of the year.
year	The year of the datetime.

timetuple

Methods

argsort([ascending, kind])	Return the indices that would sort this array.
astype(dtype[, copy])	Cast to a NumPy array with ‘dtype’.
ceil(freq[, ambiguous, nonexistent])	Perform ceil operation on the data to the specified freq.
copy([deep])	Return a copy of the array.
day_name([locale])	Return the day names of the DateTimeIndex with specified locale.
dropna()	Return ExtensionArray without NA values
factorize([na_sentinel])	Encode the extension array as an enumerated type.
fillna([value, method, limit])	Fill NA/NaN values using the specified method.
floor(freq[, ambiguous, nonexistent])	Perform floor operation on the data to the specified freq.
isna()	A 1-D array indicating if each value is missing.
max([axis, skipna])	Return the maximum value of the Array or maximum along an axis.
min([axis, skipna])	Return the minimum value of the Array or minimum along an axis.
month_name([locale])	Return the month names of the DateTimeIndex with specified locale.
normalize()	Convert times to midnight.
repeat(repeats, *args, **kwargs)	Repeat elements of an array.
round(freq[, ambiguous, nonexistent])	Perform round operation on the data to the specified freq.
searchsorted(value[, side, sorter])	Find indices where elements should be inserted to maintain order.
shift([periods, fill_value])	Shift values by desired number.
strftime(date_format)	Convert to Index using specified date_format.
take(indices[, allow_fill, fill_value])	Take elements from an array.
to_julian_date()	Convert Datetime Array to float64 ndarray of Julian Dates.
to_period([freq])	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()	Return Datetime Array/Index as object ndarray of datetime.datetime objects
tz_convert(tz)	Convert tz-aware Datetime Array/Index from one time zone to another.
tz_localize(tz[, ambiguous, nonexistent, errors])	Localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index.
unique()	Compute the ExtensionArray of unique values.
value_counts([dropna])	Return a Series containing counts of unique values.
view([dtype])	New view on this array with the same data.

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