code: def masked_rec_array_to_mgr(data, index, columns, dtype, copy):
      """
      Extract from a masked rec array and create the manager.
      """
  
      # essentially process a record array then fill it
      fill_value = data.fill_value
      fdata = ma.getdata(data)
      if index is None:
          index = get_names_from_index(fdata)
          if index is None:
              index = ibase.default_index(len(data))
      index = ensure_index(index)
  
      if columns is not None:
          columns = ensure_index(columns)
      arrays, arr_columns = to_arrays(fdata, columns)
  
      # fill if needed
      new_arrays = []
      for fv, arr, col in zip(fill_value, arrays, arr_columns):
          mask = ma.getmaskarray(data[col])
          if mask.any():
              arr, fv = maybe_upcast(arr, fill_value=fv, copy=True)
              arr[mask] = fv
          new_arrays.append(arr)
  
      # create the manager
      arrays, arr_columns = reorder_arrays(
          new_arrays, arr_columns, columns
      )
      if columns is None:
          columns = arr_columns
  
      mgr = arrays_to_mgr(arrays, arr_columns, index, columns, dtype)
  
      if copy:
          mgr = mgr.copy()
      return mgr
  
imports: from collections import OrderedDict
  import numpy
  import numpy.ma
  from pandas._libs import lib
  from pandas._libs.tslibs import IncompatibleFrequency
  import pandas.compat
  from pandas.compat import get_range_parameters, lmap, lrange, raise_with_traceback, range
  from pandas.core.dtypes.cast import construct_1d_arraylike_from_scalar, construct_1d_ndarray_preserving_na, construct_1d_object_array_from_listlike, infer_dtype_from_scalar, maybe_cast_to_datetime, maybe_cast_to_integer_array, maybe_castable, maybe_convert_platform, maybe_infer_to_datetimelike, maybe_upcast
  from pandas.core.dtypes.common import is_categorical_dtype, is_datetime64tz_dtype, is_dtype_equal, is_extension_array_dtype, is_extension_type, is_float_dtype, is_integer_dtype, is_iterator, is_list_like, is_object_dtype, pandas_dtype
  from pandas.core.dtypes.generic import ABCDataFrame, ABCDatetimeIndex, ABCIndexClass, ABCPandasArray, ABCPeriodIndex, ABCSeries, ABCTimedeltaIndex
  from pandas.core.dtypes.missing import isna
  from pandas.core import algorithms, common
  from pandas.core.arrays import Categorical, ExtensionArray, period_array
  from pandas.core.index import Index, _get_objs_combined_axis, _union_indexes, ensure_index
  from pandas.core.indexes import base
  from pandas.core.internals import create_block_manager_from_arrays, create_block_manager_from_blocks
  from pandas.core.internals.arrays import extract_array
label_desc: Use image node_id 2 for calling a global function with example usage: masked_rec_array_to_mgr(data, index, columns, dtype, copy) and returns: mgr