pandas.DatetimeIndex¶
- class pandas.DatetimeIndex¶
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
start : starting value, datetime-like, optional
If data is None, start is used as the start point in generating regular timestamp data.
periods : int, optional, > 0
Number of periods to generate, if generating index. Takes precedence over end argument
end : end time, datetime-like, optional
If periods is none, generated index will extend to first conforming time on or just past end argument
closed : string or None, default None
Make the interval closed with respect to the given frequency to the ‘left’, ‘right’, or both sides (None)
name : object
Name to be stored in the index
Attributes
T Same as self.transpose(), except that self is returned if self.ndim < 2. asi8 asobject Convert to Index of datetime objects base Base object if memory is from some other object. ctypes An object to simplify the interaction of the array with the ctypes module. data Python buffer object pointing to the start of the array’s data. date Returns numpy array of datetime.date. day dayofweek The day of the week with Monday=0, Sunday=6 dayofyear dtype flags flat A 1-D iterator over the array. freq freqstr hour imag The imaginary part of the array. inferred_type is_all_dates is_monotonic itemsize Length of one array element in bytes. microsecond minute month The month as January=1, December=12 names nanosecond nbytes Total bytes consumed by the elements of the array. ndim Number of array dimensions. nlevels quarter real The real part of the array. second shape Tuple of array dimensions. size Number of elements in the array. strides Tuple of bytes to step in each dimension when traversing an array. time Returns numpy array of datetime.time. tzinfo Alias for tz attribute values week weekday The day of the week with Monday=0, Sunday=6 weekofyear year inferred_freq is_normalized is_unique name offset resolution Methods
all([axis, out]) Returns True if all elements evaluate to True. any([axis, out]) Returns True if any of the elements of a evaluate to True. append(other) Append a collection of Index options together argmax([axis, out]) Return indices of the maximum values along the given axis. argmin() argsort(*args, **kwargs) See docstring for ndarray.argsort asof(label) For a sorted index, return the most recent label up to and including the passed label. asof_locs(where, mask) where : array of timestamps astype(dtype) byteswap(inplace) Swap the bytes of the array elements choose(choices[, out, mode]) Use an index array to construct a new array from a set of choices. clip(a_min, a_max[, out]) Return an array whose values are limited to [a_min, a_max]. compress(condition[, axis, out]) Return selected slices of this array along given axis. conj() Complex-conjugate all elements. conjugate() Return the complex conjugate, element-wise. copy([names, name, dtype, deep]) Make a copy of this object. cumprod([axis, dtype, out]) Return the cumulative product of the elements along the given axis. cumsum([axis, dtype, out]) Return the cumulative sum of the elements along the given axis. delete(loc) Make new DatetimeIndex with passed location deleted diagonal([offset, axis1, axis2]) Return specified diagonals. diff(other) Compute sorted set difference of two Index objects dot(b[, out]) Dot product of two arrays. drop(labels) Make new Index with passed list of labels deleted dump(file) Dump a pickle of the array to the specified file. dumps() Returns the pickle of the array as a string. equals(other) Determines if two Index objects contain the same elements. fill(*args, **kwargs) This method will not function because object is immutable. flatten([order]) Return a copy of the array collapsed into one dimension. format([name, formatter]) Render a string representation of the Index get_duplicates() get_indexer(target[, method, limit]) Compute indexer and mask for new index given the current index. get_indexer_non_unique(target, **kwargs) return an indexer suitable for taking from a non unique index get_level_values(level) Return vector of label values for requested level, equal to the length get_loc(key) Get integer location for requested label get_value(series, key) Fast lookup of value from 1-dimensional ndarray. get_value_maybe_box(series, key) get_values() getfield(dtype[, offset]) Returns a field of the given array as a certain type. groupby(f) holds_integer() identical(other) Similar to equals, but check that other comparable attributes are indexer_at_time(time[, asof]) Select values at particular time of day (e.g. indexer_between_time(start_time, end_time[, ...]) Select values between particular times of day (e.g., 9:00-9:30AM) insert(loc, item) Make new Index inserting new item at location intersection(other) Specialized intersection for DatetimeIndex objects. May be much faster is_(other) More flexible, faster check like is but that works through views is_floating() is_integer() is_lexsorted_for_tuple(tup) is_mixed() is_numeric() is_type_compatible(typ) isin(values) Compute boolean array of whether each index value is found in the item(*args) Copy an element of an array to a standard Python scalar and return it. itemset(*args, **kwargs) This method will not function because object is immutable. join(other[, how, level, return_indexers]) See Index.join map(f) max([axis]) Overridden ndarray.max to return a Timestamp mean([axis, dtype, out]) Returns the average of the array elements along given axis. min([axis]) Overridden ndarray.min to return a Timestamp newbyteorder([new_order]) Return the array with the same data viewed with a different byte order. nonzero() Return the indices of the elements that are non-zero. normalize() Return DatetimeIndex with times to midnight. Length is unaltered order([return_indexer, ascending]) Return sorted copy of Index prod([axis, dtype, out]) Return the product of the array elements over the given axis ptp([axis, out]) Peak to peak (maximum - minimum) value along a given axis. put(*args, **kwargs) This method will not function because object is immutable. ravel([order]) Return a flattened array. reindex(target[, method, level, limit, ...]) For Index, simply returns the new index and the results of rename(name[, inplace]) Set new names on index. repeat(repeats[, axis]) Analogous to ndarray.repeat reshape(shape[, order]) Returns an array containing the same data with a new shape. resize(new_shape[, refcheck]) Change shape and size of array in-place. round([decimals, out]) Return a with each element rounded to the given number of decimals. searchsorted(key[, side]) set_names(names[, inplace]) Set new names on index. set_value(arr, key, value) Fast lookup of value from 1-dimensional ndarray. setfield(val, dtype[, offset]) Put a value into a specified place in a field defined by a data-type. setflags([write, align, uic]) Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively. shift(n[, freq]) Specialized shift which produces a DatetimeIndex slice_indexer([start, end, step]) Index.slice_indexer, customized to handle time slicing slice_locs([start, end]) Index.slice_locs, customized to handle partial ISO-8601 string slicing snap([freq]) Snap time stamps to nearest occurring frequency sort(*args, **kwargs) squeeze([axis]) Remove single-dimensional entries from the shape of a. std([axis, dtype, out, ddof]) Returns the standard deviation of the array elements along given axis. sum([axis, dtype, out]) Return the sum of the array elements over the given axis. summary([name]) swapaxes(axis1, axis2) Return a view of the array with axis1 and axis2 interchanged. take(indices[, axis]) Analogous to ndarray.take to_datetime([dayfirst]) to_native_types([slicer]) slice and dice then format to_period([freq]) Cast to PeriodIndex at a particular frequency to_pydatetime() Return DatetimeIndex as object ndarray of datetime.datetime objects to_series() return a series with both index and values equal to the index keys tofile(fid[, sep, format]) Write array to a file as text or binary (default). tolist() See ndarray.tolist tostring([order]) Construct a Python string containing the raw data bytes in the array. trace([offset, axis1, axis2, dtype, out]) Return the sum along diagonals of the array. transpose(*axes) Returns a view of the array with axes transposed. tz_convert(tz) Convert DatetimeIndex from one time zone to another (using pytz) tz_localize(tz[, infer_dst]) Localize tz-naive DatetimeIndex to given time zone (using pytz) union(other) Specialized union for DatetimeIndex objects. If combine union_many(others) A bit of a hack to accelerate unioning a collection of indexes unique() Index.unique with handling for DatetimeIndex metadata var([axis, dtype, out, ddof]) Returns the variance of the array elements, along given axis. view(*args, **kwargs)