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pandas.api.types.is_sparse

pandas.api.types.is_sparse(arr)[source]

Check whether an array-like is a 1-D pandas sparse array.

Check that the one-dimensional array-like is a pandas sparse array. Returns True if it is a pandas sparse array, not another type of sparse array.

Parameters:

arr : array-like

Array-like to check.

Returns:

bool

Whether or not the array-like is a pandas sparse array.

See also

DataFrame.to_sparse
Convert DataFrame to a SparseDataFrame.
Series.to_sparse
Convert Series to SparseSeries.
Series.to_dense
Return dense representation of a Series.

Examples

Returns True if the parameter is a 1-D pandas sparse array.

>>> is_sparse(pd.SparseArray([0, 0, 1, 0]))
True
>>> is_sparse(pd.SparseSeries([0, 0, 1, 0]))
True

Returns False if the parameter is not sparse.

>>> is_sparse(np.array([0, 0, 1, 0]))
False
>>> is_sparse(pd.Series([0, 1, 0, 0]))
False

Returns False if the parameter is not a pandas sparse array.

>>> from scipy.sparse import bsr_matrix
>>> is_sparse(bsr_matrix([0, 1, 0, 0]))
False

Returns False if the parameter has more than one dimension.

>>> df = pd.SparseDataFrame([389., 24., 80.5, np.nan],
                            columns=['max_speed'],
                            index=['falcon', 'parrot', 'lion', 'monkey'])
>>> is_sparse(df)
False
>>> is_sparse(df.max_speed)
True
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