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# 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) |

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