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Interaction with scipy.sparse matrices.
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Currently only includes to_coo helpers.
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For a MultiIndexed sparse Series `ss`, return `ax_coords` and `ax_labels`,
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where `ax_coords` are the coordinates along one of the two axes of the
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destination sparse matrix, and `ax_labels` are the labels from `ss`' Index
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which correspond to these coordinates.
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Parameters
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----------
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ss : Series
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levels : tuple/list
|
valid_ilocs : numpy.ndarray
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Array of integer positions of valid values for the sparse matrix in ss.
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sort_labels : bool, default False
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Sort the axis labels before forming the sparse matrix. When `levels`
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refers to a single level, set to True for a faster execution.
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Returns
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-------
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ax_coords : numpy.ndarray (axis coordinates)
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ax_labels : list (axis labels)
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For an arbitrary MultiIndexed sparse Series return (v, i, j, ilabels,
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jlabels) where (v, (i, j)) is suitable for passing to scipy.sparse.coo
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constructor, and ilabels and jlabels are the row and column labels
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respectively.
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Parameters
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----------
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ss : Series
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row_levels : tuple/list
|
column_levels : tuple/list
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sort_labels : bool, default False
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Sort the row and column labels before forming the sparse matrix.
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When `row_levels` and/or `column_levels` refer to a single level,
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set to `True` for a faster execution.
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Returns
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-------
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values : numpy.ndarray
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Valid values to populate a sparse matrix, extracted from
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ss.
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i_coords : numpy.ndarray (row coordinates of the values)
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j_coords : numpy.ndarray (column coordinates of the values)
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i_labels : list (row labels)
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j_labels : list (column labels)
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Convert a sparse Series to a scipy.sparse.coo_matrix using index
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levels row_levels, column_levels as the row and column
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Convert a scipy.sparse.coo_matrix to a Series with type sparse.
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Parameters
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----------
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A : scipy.sparse.coo_matrix
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dense_index : bool, default False
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Returns
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-------
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Series
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Raises
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------
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TypeError if A is not a coo_matrix
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