{"record":{"id":"2d976fcc09e3663d","repo":"apache/beam","slug":"corrwith-s","errorCode":null,"errorMessage":"corrwith(%s)","messagePattern":"corrwith\\((.+?)\\)","errorType":"exception","errorClass":"NotImplementedError","httpStatus":null,"severity":"error","filePath":"sdks/python/apache_beam/dataframe/frames.py","lineNumber":3133,"sourceCode":"      self, other = self.align(other, axis=0, join='inner')\n      col_names = proxy.index\n      other_cols = [other] * len(col_names)\n    elif isinstance(other, DeferredDataFrame):\n      proxy = self._expr.proxy().corrwith(\n          other._expr.proxy(), axis=axis, method=method, drop=drop)\n      self, other = self.align(other, axis=0, join='inner')\n      col_names = list(\n          set(self.columns)\n          .intersection(other.columns)\n          .intersection(proxy.index))\n      other_cols = [other[col_name] for col_name in col_names]\n    else:\n      # Raise the right error.\n      self._expr.proxy().corrwith(other._expr.proxy(), axis=axis, drop=drop,\n                                  method=method)\n\n      # Just in case something else becomes valid.\n      raise NotImplementedError('corrwith(%s)' % type(other._expr.proxy))\n\n    # Generate expressions to compute the actual correlations.\n    corrs = [\n        self[col_name].corr(other_col, method)\n        for col_name, other_col in zip(col_names, other_cols)]\n\n    # Combine the results\n    def fill_dataframe(*args):\n      result = proxy.copy(deep=True)\n      for col, value in zip(proxy.index, args):\n        result[col] = value\n      return result\n    with expressions.allow_non_parallel_operations(True):\n      return frame_base.DeferredFrame.wrap(\n        expressions.ComputedExpression(\n          'fill_dataframe',\n          fill_dataframe,\n          [corr._expr for corr in corrs],","sourceCodeStart":3115,"sourceCodeEnd":3151,"githubUrl":"https://github.com/apache/beam/blob/12126d8942aaf848030c478b4c6a28c6af861c66/sdks/python/apache_beam/dataframe/frames.py#L3115-L3151","documentation":"Apache Beam's DataFrame API (pandas-on-Beam) raised NotImplementedError after attempting to proxy a corrwith() call to pandas. The self._expr.proxy() call is expected to throw since corrwith with a deferred frame argument is not implemented; this raise is a safety net 'in case something else becomes valid'.","triggerScenarios":"Calling DeferredFrame.corrwith(other) where other is a deferred Beam series/frame, with axis/drop/method arguments, in apache_beam.dataframe.frames","commonSituations":"Porting pandas code that computes pairwise column correlations between two distributed dataframes to Beam pipelines","solutions":["Materialize one or both frames to pandas (e.g. to_pandas()) and use pandas corrwith directly","Compute correlations column-wise using self[col].corr(other_col) inside a Beam transform","Track/subscribe to the upstream Beam issue for corrwith support and use a non-deferred pandas object in the meantime"],"exampleFix":"// before\ncorr = df.beam.corrwith(other_df.beam)\n// after\nimport pandas as pd\ncorr = df.beam.to_pandas().corrwith(other_df.beam.to_pandas())","handlingStrategy":"fallback","validationCode":"if isinstance(other, frame_base.DeferredFrame):\n    raise TypeError('corrwith with a deferred argument is unsupported; materialize with to_pandas()')","typeGuard":"def is_concrete_pandas(obj):\n    return isinstance(obj, pd.Series) or isinstance(obj, pd.DataFrame)","tryCatchPattern":"try:\n    corr = dframe.corrwith(other)\nexcept NotImplementedError:\n    corr = dframe.to_pandas().corrwith(other.to_pandas())","preventionTips":["Check the Beam DataFrame API capability matrix before porting pandas calls","Keep a pandas fallback path for unsupported deferred operations","Search open Beam issues (github.com/apache/beam) for the method before using it"],"tags":["python","apache-beam","dataframe","not-implemented"],"backgroundTag":"unsupported-operation","analyzedSha":"12126d8942aaf848030c478b4c6a28c6af861c66","analyzedAt":"2026-09-13T01:50:10.254Z","contentChangedAt":"2026-09-13T01:50:10.254Z","schemaVersion":2},"datasetVersion":"2026-09-20T03:17:13.778Z"}