code: def df_corrwith(df, other, axis=0, drop=False, method="pearson"):
      """
      Compute pairwise correlation.
  
      Pairwise correlation is computed between rows or columns of
      DataFrame with rows or columns of Series or DataFrame. DataFrames
      are first aligned along both axes before computing the
      correlations.
  
      Parameters
      ----------
      other : DataFrame, Series
          Object with which to compute correlations.
      axis : {0 or 'index', 1 or 'columns'}, default 0
          The axis to use. 0 or 'index' to compute column-wise, 1 or 'columns' for
          row-wise.
      drop : bool, default False
          Drop missing indices from result.
      method : {'pearson', 'kendall', 'spearman'} or callable
          Method of correlation:
  
          * pearson : standard correlation coefficient
          * kendall : Kendall Tau correlation coefficient
          * spearman : Spearman rank correlation
          * callable: callable with input two 1d ndarrays
              and returning a float.
  
          .. note::
              kendall, spearman and callables not supported on multiple chunks yet.
  
      Returns
      -------
      Series
          Pairwise correlations.
  
      See Also
      --------
      DataFrame.corr : Compute pairwise correlation of columns.
      """
      axis = validate_axis(axis, df)
      if drop:
          # TODO implement with df.align(method='inner')
          raise NotImplementedError("drop=True not implemented")
      op = DataFrameCorr(
          other=other, method=method, axis=axis, drop=drop
      )
      return op(df)
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import ENTITY_TYPE, recursive_tile
  from ...serialization.serializables import BoolField, AnyField, KeyField, Int32Field
  from ...tensor.utils import filter_inputs
  from ...utils import has_unknown_shape
  from ..core import SERIES_TYPE, DATAFRAME_TYPE
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import build_empty_df, validate_axis, parse_index
label_desc: Use image node_id 3 for calling a global function with example usage: df_corrwith(df, other, axis, drop, method) and returns: op