# xarray.IndexVariable

class `xarray.``IndexVariable`(dims, data, attrs=None, encoding=None, fastpath=False)

  Wrapper for accommodating a pandas.Index in an xarray.Variable.

  IndexVariable preserve loaded values in the form of a pandas.Index instead of a NumPy array. Hence, their values are immutable and must always be one- dimensional.

  They also have a name property, which is the name of their sole dimension unless another name is given.

  `__init__`(dims, data, attrs=None, encoding=None, fastpath=False)

    Parameters:

    - dims (str or sequence of str) – Name(s) of the the data dimension(s). Must be either a string (only for 1D data) or a sequence of strings with length equal to the number of dimensions.
    - data (array_like) – Data array which supports numpy-like data access.
    - attrs (dict_like or None, optional) – Attributes to assign to the new variable. If None (default), an empty attribute dictionary is initialized.
    - encoding (dict_like or None, optional) – Dictionary specifying how to encode this array’s data into a serialized format like netCDF4. Currently used keys (for netCDF) include ‘_FillValue’, ‘scale_factor’, ‘add_offset’ and ‘dtype’. Well-behaved code to serialize a Variable should ignore unrecognized encoding items.

  Methods

  `__init__`(dims, data[, attrs, encoding, fastpath])

  param dims: | Name(s) of the the data dimension(s). Must be either a string (only

  `all`([dim, axis]) | Reduce this Variable’s data by applying all along some dimension(s).
  `any`([dim, axis]) | Reduce this Variable’s data by applying any along some dimension(s).
  `argmax`([dim, axis, skipna]) | Reduce this Variable’s data by applying argmax along some dimension(s).
  `argmin`([dim, axis, skipna]) | Reduce this Variable’s data by applying argmin along some dimension(s).
  `argsort`([axis, kind, order]) | Returns the indices that would sort this array.
  `astype`(dtype[, order, casting, subok, copy]) | Copy of the array, cast to a specified type.
  `broadcast_equals`(other[, equiv]) | True if two Variables have the values after being broadcast against each other; otherwise False.
  `chunk`([chunks, name, lock]) | Coerce this array’s data into a dask arrays with the given chunks.
  `clip`([min, max, out]) | Return an array whose values are limited to `[min, max]`.
  `coarsen`(windows, func[, boundary, side]) | Apply reduction function.
  `compute`(**kwargs) | Manually trigger loading of this variable’s data from disk or a remote source into memory and return a new variable.
  `concat`(variables[, dim, positions, shortcut]) | Specialized version of Variable.concat for IndexVariable objects.
  `conj`() | Complex-conjugate all elements.
  `conjugate`() | Return the complex conjugate, element-wise.
  `copy`([deep, data]) | Returns a copy of this object.
  `count`([dim, axis]) | Reduce this Variable’s data by applying count along some dimension(s).
  `cumprod`([dim, axis, skipna]) | Apply cumprod along some dimension of Variable.
  `cumsum`([dim, axis, skipna]) | Apply cumsum along some dimension of Variable.
  `equals`(other[, equiv]) | True if two Variables have the same dimensions and values; otherwise False.
  `fillna`(value) |
  `get_axis_num`(dim, Iterable[Hashable]]) | Return axis number(s) corresponding to dimension(s) in this array.
  `get_level_variable`(level) | Return a new IndexVariable from a given MultiIndex level.
  `identical`(other[, equiv]) | Like equals, but also checks attributes.
  `isel`(indexers, Any] = None, **indexers_kwargs) | Return a new array indexed along the specified dimension(s).
  `isnull`(*args, **kwargs) |
  `item`(*args) | Copy an element of an array to a standard Python scalar and return it.
  `load`() | Manually trigger loading of this variable’s data from disk or a remote source into memory and return this variable.
  `max`([dim, axis, skipna]) | Reduce this Variable’s data by applying max along some dimension(s).
  `mean`([dim, axis, skipna]) | Reduce this Variable’s data by applying mean along some dimension(s).
  `median`([dim, axis, skipna]) | Reduce this Variable’s data by applying median along some dimension(s).
  `min`([dim, axis, skipna]) | Reduce this Variable’s data by applying min along some dimension(s).
  `no_conflicts`(other[, equiv]) | True if the intersection of two Variable’s non-null data is equal; otherwise false.
  `notnull`(*args, **kwargs) |
  `pad_with_fill_value`([pad_widths, fill_value]) | Return a new Variable with paddings.
  `prod`([dim, axis, skipna]) | Reduce this Variable’s data by applying prod along some dimension(s).
  `quantile`(q[, dim, interpolation, keep_attrs]) | Compute the qth quantile of the data along the specified dimension.
  `rank`(dim[, pct]) | Ranks the data.
  `reduce`(func[, dim, axis, keep_attrs, …]) | Reduce this array by applying func along some dimension(s).
  `roll`([shifts]) | Return a new Variable with rolld data.
  `rolling_window`(dim, window, window_dim[, …]) | Make a rolling_window along dim and add a new_dim to the last place.
  `round`(*args, **kwargs) |
  `searchsorted`(v[, side, sorter]) | Find indices where elements of v should be inserted in a to maintain order.
  `set_dims`(dims[, shape]) | Return a new variable with given set of dimensions.
  `shift`([shifts, fill_value]) | Return a new Variable with shifted data.
  `squeeze`([dim]) | Return a new object with squeezed data.
  `stack`([dimensions]) | Stack any number of existing dimensions into a single new dimension.
  `std`([dim, axis, skipna]) | Reduce this Variable’s data by applying std along some dimension(s).
  `sum`([dim, axis, skipna]) | Reduce this Variable’s data by applying sum along some dimension(s).
  `to_base_variable`() | Return this variable as a base xarray.Variable
  `to_coord`() | to_coord has been deprecated.
  `to_dict`([data]) | Dictionary representation of variable.
  `to_index`() | Convert this variable to a pandas.Index
  `to_index_variable`() | Return this variable as an xarray.IndexVariable
  `to_variable`() | to_variable has been deprecated.
  `transpose`(*dims) | Return a new Variable object with transposed dimensions.
  `unstack`([dimensions]) | Unstack an existing dimension into multiple new dimensions.
  `var`([dim, axis, skipna]) | Reduce this Variable’s data by applying var along some dimension(s).
  `where`(cond[, other]) |

  Attributes

  `T` |
  `attrs` | Dictionary of local attributes on this variable.
  `chunks` | Block dimensions for this array’s data or None if it’s not a dask array.
  `data` |
  `dims` | Tuple of dimension names with which this variable is associated.
  `dtype` |
  `encoding` | Dictionary of encodings on this variable.
  `imag` |
  `level_names` | Return MultiIndex level names or None if this IndexVariable has no MultiIndex.
  `name` |
  `nbytes` |
  `ndim` |
  `real` |
  `shape` |
  `size` |
  `sizes` | Ordered mapping from dimension names to lengths.
  `values` | The variable’s data as a numpy.ndarray