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# pandas.IntervalIndex

class pandas.IntervalIndex(data, closed=None, dtype=None, copy=False, name=None, verify_integrity=True)

  Immutable index of intervals that are closed on the same side.

  Parameters:
    dataarray-like (1-dimensional)

      Array-like (ndarray, `DateTimeArray`, `TimeDeltaArray`) containing Interval objects from which to build the IntervalIndex.

    closed{‘left’, ‘right’, ‘both’, ‘neither’}, default ‘right’

      Whether the intervals are closed on the left-side, right-side, both or neither.

    dtypedtype or None, default None

      If None, dtype will be inferred.

    copybool, default False

      Copy the input data.

    nameobject, optional

      Name to be stored in the index.

    verify_integritybool, default True

      Verify that the IntervalIndex is valid.

  Attributes

  `closed` | String describing the inclusive side the intervals.
  `is_empty` | Indicates if an interval is empty, meaning it contains no points.
  `is_non_overlapping_monotonic` | Return a boolean whether the IntervalArray is non-overlapping and monotonic.
  `is_overlapping` | Return True if the IntervalIndex has overlapping intervals, else False.
  `values` | Return an array representing the data in the Index.

  left |
  right |
  mid |
  length |

  Methods

  `from_arrays`(left, right[, closed, name, ...]) | Construct from two arrays defining the left and right bounds.
  `from_tuples`(data[, closed, name, copy, dtype]) | Construct an IntervalIndex from an array-like of tuples.
  `from_breaks`(breaks[, closed, name, copy, dtype]) | Construct an IntervalIndex from an array of splits.
  `contains`(*args, **kwargs) | Check elementwise if the Intervals contain the value.
  `overlaps`(*args, **kwargs) | Check elementwise if an Interval overlaps the values in the IntervalArray.
  `set_closed`(*args, **kwargs) | Return an identical IntervalArray closed on the specified side.
  `to_tuples`(*args, **kwargs) | Return an ndarray (if self is IntervalArray) or Index (if self is IntervalIndex) of tuples of the form (left, right).

  See also

  `Index`

    The base pandas Index type.

  `Interval`

    A bounded slice-like interval; the elements of an IntervalIndex.

  `interval_range`

    Function to create a fixed frequency IntervalIndex.

  `cut`

    Bin values into discrete Intervals.

  `qcut`

    Bin values into equal-sized Intervals based on rank or sample quantiles.

  Notes

  See the user guide for more.

  Examples

  A new `IntervalIndex` is typically constructed using `interval_range()`:

      >>> pd.interval_range(start=0, end=5)
      IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]],
                    dtype='interval[int64, right]')

  It may also be constructed using one of the constructor methods: `IntervalIndex.from_arrays()`, `IntervalIndex.from_breaks()`, and `IntervalIndex.from_tuples()`.

  See further examples in the doc strings of `interval_range` and the mentioned constructor methods.