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)

Methods

__init__(dims, data[, attrs, encoding, fastpath])
all([dim, axis, keep_attrs])	Reduce this Variable’s data by applying all along some dimension(s).
any([dim, axis, keep_attrs])	Reduce this Variable’s data by applying any along some dimension(s).
argmax([dim, axis, skipna, keep_attrs])	Reduce this Variable’s data by applying argmax along some dimension(s).
argmin([dim, axis, skipna, keep_attrs])	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])
clip([min, max, out])	Return an array whose values are limited to [min, max].
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])	Returns a copy of this object.
count([dim, axis, keep_attrs])	Reduce this Variable’s data by applying count along some dimension(s).
cumprod([dim, axis, skipna, keep_attrs])	Apply cumprod along some dimension of Variable.
cumsum([dim, axis, skipna, keep_attrs])	Apply cumsum along some dimension of Variable.
equals(other[, equiv])
expand_dims(*args)
fillna(value)
get_axis_num(dim)	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)	Like equals, but also checks attributes.
isel(**indexers)	Return a new array indexed along the specified dimension(s).
isnull(*args, **kwargs)	Detect missing values (NaN in numeric arrays, None/NaN in object arrays)
item(*args)	Copy an element of an array to a standard Python scalar and return it.
load()
max([dim, axis, skipna, keep_attrs])	Reduce this Variable’s data by applying max along some dimension(s).
mean([dim, axis, skipna, keep_attrs])	Reduce this Variable’s data by applying mean along some dimension(s).
median([dim, axis, skipna, keep_attrs])	Reduce this Variable’s data by applying median along some dimension(s).
min([dim, axis, skipna, keep_attrs])	Reduce this Variable’s data by applying min along some dimension(s).
no_conflicts(other)	True if the intersection of two Variable’s non-null data is equal; otherwise false.
notnull(*args, **kwargs)	Replacement for numpy.isfinite / -numpy.isnan which is suitable for use on object arrays.
prod([dim, axis, skipna, keep_attrs])	Reduce this Variable’s data by applying prod along some dimension(s).
quantile(q[, dim, interpolation])	Compute the qth quantile of the data along the specified dimension.
reduce(func[, dim, axis, keep_attrs, allow_lazy])	Reduce this array by applying func along some dimension(s).
roll(**shifts)	Return a new Variable with rolld data.
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)	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, keep_attrs])	Reduce this Variable’s data by applying std along some dimension(s).
sum([dim, axis, skipna, keep_attrs])	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. Use to_index_variable instead.
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. Use to_base_variable instead.
transpose(*dims)	Return a new Variable object with transposed dimensions.
unstack(**dimensions)	Unstack an existing dimension into multiple new dimensions.
var([dim, axis, skipna, keep_attrs])	Reduce this Variable’s data by applying var along some dimension(s).
where(cond[, other])