code: def _sparse_reindex(cls, inp, index=None, columns=None):
      if inp.ndim == 2:
          columns = inp.columns if columns is None else columns
          index_shape = len(index) if index is not None else len(inp)
          i_to_columns = dict()
  
          for i, col in enumerate(columns):
              if col in inp.dtypes:
                  if index is None:
                      i_to_columns[i] = inp[col]
                  else:
                      indexer = inp.index.reindex(index)[1]
                      cond = indexer >= 0
                      available_indexer = indexer[cond]
                      del indexer
                      data = inp[col].iloc[available_indexer].to_numpy()
                      ind = cond.nonzero()[0]
                      spmatrix = sps.csc_matrix(
                          (data, (ind, np.zeros_like(ind))),
                          shape=(index_shape, 1),
                          dtype=inp[col].dtype,
                      )
                      # convert to SparseDtype(xxx, np.nan)
                      # to ensure 0 in sparse_array not converted to np.nan
                      if not _pd_sparse_miss_zero:
                          sparse_array = (
                              pd.arrays.SparseArray.from_spmatrix(
                                  spmatrix
                              )
                          )
                          sparse_array = pd.arrays.SparseArray(
                              sparse_array.sp_values,
                              sparse_index=sparse_array.sp_index,
                              fill_value=np.nan,
                              dtype=pd.SparseDtype(
                                  sparse_array.dtype, np.nan
                              ),
                          )
                      else:
                          from pandas._libs.sparse import IntIndex
  
                          sparse_array = pd.arrays.SparseArray(
                              data,
                              sparse_index=IntIndex(index_shape, ind),
                              fill_value=np.nan,
                              dtype=pd.SparseDtype(data.dtype, np.nan),
                          )
                      series = pd.Series(sparse_array, index=index)
  
                      i_to_columns[i] = series
              else:
                  ind = index if index is not None else inp.index
                  i_to_columns[i] = pd.DataFrame.sparse.from_spmatrix(
                      sps.coo_matrix(
                          (index_shape, 1), dtype=np.float64
                      ),
                      index=ind,
                  ).iloc[:, 0]
  
          df = pd.DataFrame(i_to_columns)
          df.columns = columns
          return df
      else:
          indexer = inp.index.reindex(index)[1]
          cond = indexer >= 0
          available_indexer = indexer[cond]
          del indexer
          data = inp.iloc[available_indexer].to_numpy()
          ind = cond.nonzero()[0]
          spmatrix = sps.csc_matrix(
              (data, (ind, np.zeros_like(ind))),
              shape=(len(index), 1),
              dtype=inp.dtype,
          )
          sparse_array = pd.arrays.SparseArray.from_spmatrix(spmatrix)
          # convert to SparseDtype(xxx, np.nan)
          # to ensure 0 in sparse_array not converted to np.nan
          sparse_array = pd.arrays.SparseArray(
              sparse_array.sp_values,
              sparse_index=sparse_array.sp_index,
              fill_value=np.nan,
              dtype=pd.SparseDtype(sparse_array.dtype, np.nan),
          )
          series = pd.Series(sparse_array, index=index, name=inp.name)
          return series
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import ENTITY_TYPE, recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import KeyField, AnyField, StringField, Int64Field, BoolField
  from ...tensor import tensor
  from ...utils import lazy_import, pd_release_version
  from ..core import Index, INDEX_TYPE
  from ..initializer import Index
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import validate_axis_style_args, parse_index
  from .index_lib import DataFrameReindexHandler
label_desc: Use image node_id 21 for calling the DataFrameReindex obj's underlying member method code with example usage: obj._sparse_reindex(cls, inp, index, columns) and returns: df, series