pandas.api.types.is_sparse¶
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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