code: def generalized_corrwith(
      x1: pd.DataFrame, x2: pd.DataFrame, method: t.Callable
  ):
      """
      Compute pairwise correlation.
  
      Pairwise correlation is computed between columns of one DataFrame with columns of another DataFrame.
      Pandas' method corrwith only applies when both dataframes have the same column names,
      this generalized method applies to any two Dataframes with the same number of rows, regardless of the column names.
  
      Parameters
      ----------
      x1: DataFrame
          Left data frame to compute correlations.
      x2: Dataframe
          Right data frame to compute correlations.
      method: Callable
          Method of correlation. callable with input two 1d ndarrays and returning a float.
  
      Returns
      -------
      DataFrame
          Pairwise correlations, the index matches the columns of x1 and the columns match the columns of x2.
      """
      corr_results = x2.apply(
          lambda col: x1.corrwith(col, method=method)
      )
      return corr_results
  
file_path: deepchecks/deepchecks/utils/dataframes.py
imports: import typing
  import numpy
  import pandas
  from pandas.core.dtypes.common import is_float_dtype, is_integer_dtype, is_numeric_dtype
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.utils.type_inference import infer_categorical_features
  from deepchecks.utils.typing import Hashable
  from deepchecks.utils.validation import ensure_hashable_or_mutable_sequence
label_desc: Use image node_id 8 for calling a global function with example usage: generalized_corrwith(x1, x2, method) and returns: corr_results