DatetimeIndex

class DatetimeIndex

Immutable ndarray-like of datetime64 data.

Example

import pandasCore as pd

# Create DatetimeIndex
idx = pd.DatetimeIndex([1, 2, 3], name='my_index')
print(len(idx))  # 3

Attributes

Attribute	Description	Example
day	The day of the datetime
day_of_week	The day of the week with Monday=0, Sunday=6
day_of_year	The ordinal day of the year
dayofweek	The day of the week with Monday=0, Sunday=6
dayofyear	The ordinal day of the year
dtype	Return the dtype object of the underlying data
empty	Indicator whether DatetimeIndex is empty
freq	Return the frequency object
has_duplicates	Return if the index has duplicate values
hour	The hours of the datetime
is_leap_year	Boolean indicator if the date belongs to a leap year
is_monotonic_decreasing	Return if the index is monotonic decreasing
is_monotonic_increasing	Return if the index is monotonic increasing
is_month_end	Indicator for whether the date is the last day of the month
is_month_start	Indicator for whether the date is the first day of the month
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_unique	Return if the index has unique values
is_year_end	Indicator for whether the date is the last day of the year
is_year_start	Indicator for whether the date is the first day of the year
microsecond	The microseconds of the datetime
minute	The minutes of the datetime
month	The month of the datetime
name	Return the name of the DatetimeIndex
nanosecond	The nanoseconds of the datetime
ndim	Number of dimensions of the underlying data
nlevels	Number of levels in this index
quarter	The quarter of the date
second	The seconds of the datetime
shape	Return a tuple of the shape of the underlying data
size	Return the number of elements in the DatetimeIndex
str	Vectorized string functions for Index.	View
tz	Return timezone, if any
weekday	The day of the week with Monday=0, Sunday=6
year	The year of the datetime

Construction

Method	Description	Example
__init__() (*args, **kwargs) | () | (data: object = None, freq: object = None, tz: object = None, normalize: object = None, closed: object = None, ambiguous: str = 'raise', dayfirst: bool = False, yearfirst: bool = False, dtype: object = None, copy: bool = False, name: object = None)	Create an empty DatetimeIndex	View

Indexing / Selection

Method	Description	Example
__getitem__() (arg0: object)
take() (indices: collections.abc.Sequence[typing.SupportsInt], axis: typing.SupportsInt = 0, allow_fill: bool = True, fill_value: object = None)	Return a new DatetimeIndex of the values selected by the indices.
where() (cond: collections.abc.Sequence[bool], other: object = None)	Replace values where the condition is False.

Data Manipulation

Method	Description	Example
drop() (labels: collections.abc.Sequence[typing.SupportsInt], errors: str = 'raise')	Make new DatetimeIndex with passed list of labels deleted.
droplevel() (level: typing.SupportsInt = 0)	Return index with requested level(s) removed.
insert() (loc: typing.SupportsInt, item: typing.SupportsInt)	Insert new item at specified position
reindex() (target: pandasCore.DatetimeIndex, method: object = None, level: object = None, limit: object = None, tolerance: object = None)	Conform DatetimeIndex to new index.
rename() (name: object, *, inplace: bool = False)	Alter DatetimeIndex name.
set_names() (names: object, *, level: object = None, inplace: bool = False)	Set DatetimeIndex name.

Missing Data

Method	Description	Example
dropna() (how: str = 'any')	Return DatetimeIndex without NA/NaT values.
fillna() (value: object = None, downcast: object = None)	Fill NA/NaT values with the specified value.
isna() ()	Detect missing values (NaT)
isnull() ()	Alias for isna
notna() ()	Detect existing (non-missing) values
notnull() ()	Alias for notna

Statistics

Method	Description	Example
max() (axis: object = None, skipna: bool = True)	Return the maximum value of the Index.
mean() (*, skipna: bool = True, axis: object = 0)	Return the mean value of the Index as nanoseconds.
min() (axis: object = None, skipna: bool = True)	Return the minimum value of the Index.
nunique() (dropna: bool = True)	Return number of unique elements
std() (axis: object = None, dtype: object = None, out: object = None, ddof: typing.SupportsInt = 1, keepdims: bool = False, skipna: bool = True)	Return the standard deviation as nanoseconds.
value_counts() (normalize: bool = False, sort: bool = True, ascending: bool = False, bins: object = None, dropna: bool = True)	Return a Series containing counts of unique values.

Aggregation

Method	Description	Example
groupby() (values: collections.abc.Sequence[typing.SupportsInt])	Group the index labels by a mapping
map() (mapper: collections.abc.Callable, na_action: object = None)	Map values using an input mapping or function.

Comparison

Method	Description	Example
__eq__() (self, value, /)	Return self==value.
__ge__() (self, value, /)	Return self>=value.
__gt__() (self, value, /)	Return self>value.
__le__() (self, value, /)	Return self<=value.
__lt__() (self, value, /)	Return self<value.
__ne__() (self, value, /)	Return self!=value.
equals() (other: pandasCore.DatetimeIndex)	Determine if two DatetimeIndex objects are equal

Sorting

Method	Description	Example
argsort() (*, ascending: bool = True, kind: str = 'quicksort', na_position: str = 'last')	Return the indices that would sort the index.
searchsorted() (value: typing.SupportsInt, side: str = 'left', sorter: object = None)	Find indices where elements should be inserted to maintain order.
sort_values() (*, return_indexer: bool = False, ascending: bool = True, na_position: str = 'last', key: object = None)	Return a sorted copy of the index.

Reshaping

Method	Description	Example
to_frame() (index: bool = True, name: object = None)	Create a DataFrame with a column containing the Index.
transpose() ()	Return the transpose (identity for 1D)

Combining

Method	Description	Example
append() (other: pandasCore.DatetimeIndex)	Append another DatetimeIndex to this one
join() (other: pandasCore.DatetimeIndex, *, how: str = 'left', level: object = None, return_indexers: bool = False, sort: bool = False)	Compute join of this index with other.

Time Series

Method	Description	Example
asof() (label: typing.SupportsInt)	Return the label from the index, or NaT
diff() (periods: typing.SupportsInt = 1)	Compute differences between consecutive elements
shift() (periods: typing.SupportsInt = 1, freq: object = None)	Shift index by desired number of periods.
to_period() (*args, **kwargs)	Cast to PeriodArray/PeriodIndex at a particular frequency.
tz_convert() (tz: object)	Convert tz-aware DatetimeIndex from one timezone to another.
tz_localize() (tz: object, ambiguous: str = 'raise', nonexistent: str = 'raise')	Localize tz-naive DatetimeIndex to tz-aware DatetimeIndex.

I/O

Method	Description	Example
to_flat_index() ()	Identity method; returns a copy
to_julian_date() ()	Convert DatetimeIndex to Julian Date.
to_list() ()	Return a list of the DatetimeIndex values as nanoseconds
to_numpy() (dtype: object = None, copy: bool = False, na_value: object = None)	Convert to a NumPy array.
to_pydatetime() (*args, **kwargs)	Return DatetimeIndex as object ndarray of datetime.datetime objects.
to_series() (index: object = None, name: object = None)	Create a Series with the Index values.
tolist() ()	Return a list of the DatetimeIndex values as nanoseconds

Conversion

Method	Description	Example
astype() (dtype: str, copy: bool = True)	Cast to a specified dtype.
copy() (name: object = None, deep: bool = False)	Make a copy of this DatetimeIndex.
infer_objects() (copy: bool = True)	Attempt to infer better dtype for object columns.
view() (cls: object = None)	Return a view on the index values.

Iteration

Method	Description	Example
__contains__() (arg0: typing.SupportsInt)
__iter__() ()
__len__() ()

Set Operations

Method	Description	Example
difference() (other: pandasCore.DatetimeIndex, sort: object = None)	Return a new DatetimeIndex with elements not in other.
drop_duplicates() (*, keep: str = 'first')	Return DatetimeIndex with duplicate values removed.
duplicated() (keep: str = 'first')	Indicate duplicate index values
intersection() (other: pandasCore.DatetimeIndex, sort: bool = False)	Form the intersection of two DatetimeIndex objects.
isin() (values: collections.abc.Sequence[typing.SupportsInt], level: object = None)	Check if values are in the DatetimeIndex.
symmetric_difference() (other: pandasCore.DatetimeIndex, result_name: object = None, sort: object = None)	Compute the symmetric difference of two Index objects.
union() (other: pandasCore.DatetimeIndex, sort: object = None)	Form the union of two DatetimeIndex objects.
unique() (level: object = None)	Return unique values in the index.

Datetime Methods

Method	Description	Example
ceil() (freq: str, ambiguous: str = 'raise', nonexistent: str = 'raise')	Perform ceil operation on the data to the specified freq.
floor() (freq: str, ambiguous: str = 'raise', nonexistent: str = 'raise')	Perform floor operation on the data to the specified freq.
normalize() ()	Convert times to midnight.
round() (freq: str, ambiguous: str = 'raise', nonexistent: str = 'raise')	Perform round operation on the data to the specified freq.
strftime() (date_format: str)	Convert to string array using specified date_format.

Other Methods

Method	Description	Example
__hash__() (self, /)	Return hash(self).
__repr__() ()
__str__() ()
all() (*, axis: object = None, skipna: bool = True)	Return whether all elements are truthy (non-NaT).
any() (*, axis: object = None, skipna: bool = True)	Return whether any element is truthy (non-NaT).
argmax() (axis: object = None, skipna: bool = True)	Return int position of the largest value in the Index.
argmin() (axis: object = None, skipna: bool = True)	Return int position of the smallest value in the Index.
as_unit() (unit: str, round_ok: bool = True)	Convert to a new unit resolution.
asof_locs() (where: pandasCore.DatetimeIndex, mask: collections.abc.Sequence[bool] | None = None)	Return the locations (indices) for asof queries.
day_name() (locale: object = None)	Return the day names of the DatetimeIndex with specified locale.
delete() (loc: typing.SupportsInt)	Make new DatetimeIndex with element at position deleted
factorize() (sort: bool = False, use_na_sentinel: bool = True)	Encode the object as an enumerated type or categorical variable.
format() (name: bool = False, formatter: object = None, na_rep: str = 'NaT', date_format: object = None)	Render a string representation of the Index.
get_indexer() (target: pandasCore.DatetimeIndex, method: object = None, limit: object = None, tolerance: object = None)	Compute indexer and mask for new index given the current index.
get_indexer_for() (target: collections.abc.Sequence[typing.SupportsInt])	Get indexer for target values
get_indexer_non_unique() (target: pandasCore.DatetimeIndex)	Get indexer and missing indices for non-unique target
get_level_values() (level: typing.SupportsInt)	Return an Index of values for requested level
get_loc() (key: typing.SupportsInt)	Get integer location for requested label
get_slice_bound() (label: typing.SupportsInt, side: str)	Get slice bound
holds_integer() ()	Return if the index holds integer values
identical() (other: pandasCore.DatetimeIndex)	Determine if two DatetimeIndex objects are identical
indexer_at_time() (time: str, asof: bool = False)	Return index locations of values at particular time of day.
indexer_between_time() (start_time: str, end_time: str, include_start: bool = True, include_end: bool = True)	Return index locations of values between particular times of day.
isocalendar() ()	Return a DataFrame containing ISO year, week number, and weekday.
item() ()	Return the first element of the data as a scalar
memory_usage() (deep: bool = False)	Memory usage of the Index values
month_name() (locale: object = None)	Return the month names of the DatetimeIndex with specified locale.
putmask() (mask: collections.abc.Sequence[bool], value: typing.SupportsInt)	Return a new DatetimeIndex with values put where mask is True.
ravel() (order: str = 'C')	Return a flattened array of the index values.
repeat() (repeats: typing.SupportsInt, axis: object = None)	Repeat elements of a DatetimeIndex.
slice_indexer() (start: object = None, end: object = None, step: object = None)	Compute slice locations for input labels.
slice_locs() (start: object = None, end: object = None, step: object = None)	Compute slice locations for input labels.
snap() (freq: str = 'S')	Snap time stamps to nearest occurring frequency.
sort() (ascending: bool = True)	Return a sorted copy of the index.
sortlevel() (level: object = None, ascending: bool = True, sort_remaining: object = None, na_position: str = 'first')	Sort Index by level.

Code Examples

The following examples are extracted from the test suite.

str (test_datetimeindex_str.py:72)

def test_datetimeindex_str_call_with_data():
    """Test DatetimeIndex.str(data) call."""
    print("Testing DatetimeIndex.str(data) call...")

    # Create a DatetimeIndex
    dti = pandasCore.DatetimeIndex(['2020-01-01', '2020-12-31'])

    # Call DatetimeIndex.str with the index as argument
    try:
        str_accessor = pandasCore.DatetimeIndex.str(dti)
        print(f"  DatetimeIndex.str(dti) returned: {type(str_accessor)}")
        print("  PASSED: DatetimeIndex.str(data) call works")
    except Exception as e:
        # Expected to raise error since DatetimeIndex doesn't contain strings
        print(f"  Error (expected for non-string data): {e}")
        print("  PASSED: Appropriate error raised for non-string Index")

def f_main():
    """Main test function."""
    print("=" * 60)

__init__ (test_datetimeindex.py:51)

TS_2020_01_04 = TS_2020_01_01 + 3 * NS_PER_DAY
TS_2020_01_05 = TS_2020_01_01 + 4 * NS_PER_DAY


def test_constructor_and_properties():
    """Test DatetimeIndex constructor and basic properties"""
    f_print_header("Test: Constructor and Properties")

    # Basic construction
    data = [TS_2020_01_01, TS_2020_01_02, TS_2020_01_03]
    dti = pandasCore.DatetimeIndex(data, name="test_dti")

    ctx.assert_equal(3, dti.size, "size")
    ctx.assert_equal("test_dti", dti.name, "name")
    ctx.assert_equal("datetime64[ns]", dti.dtype, "dtype")
    ctx.assert_false(dti.empty, "empty")
    ctx.assert_true(dti.is_unique, "is_unique")
    ctx.assert_equal(1, dti.ndim, "ndim")
    ctx.assert_equal((3,), dti.shape, "shape")
    ctx.assert_equal(1, dti.nlevels, "nlevels")