code: def convert_input(X, columns=None, deep=False, index=None):
      """
      Unite data into a DataFrame.
      Objects that do not contain column names take the names from the argument.
      Optionally perform deep copy of the data.
      """
      if not isinstance(X, pd.DataFrame):
          if isinstance(X, pd.Series):
              X = pd.DataFrame(X, copy=deep)
          else:
              if columns is not None and np.size(X, 1) != len(columns):
                  raise ValueError(
                      "The count of the column names does not correspond to the count of the columns"
                  )
              if isinstance(X, list):
                  X = pd.DataFrame(
                      X, columns=columns, copy=deep, index=index
                  )  # lists are always copied, but for consistency, we still pass the argument
              elif isinstance(X, (np.generic, np.ndarray)):
                  X = pd.DataFrame(
                      X, columns=columns, copy=deep, index=index
                  )
              elif isinstance(X, csr_matrix):
                  X = pd.DataFrame(
                      X.todense(),
                      columns=columns,
                      copy=deep,
                      index=index,
                  )
              else:
                  raise ValueError(f"Unexpected input type: {type(X)}")
      elif deep:
          X = X.copy(deep=True)
  
      return X
  
imports: from abc import abstractmethod
  from enum import Enum, auto
  import warnings
  import pandas
  import numpy
  import sklearn.base
  from pandas.api.types import is_object_dtype, is_string_dtype, is_numeric_dtype
  from pandas.core.dtypes.dtypes import CategoricalDtype
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.exceptions import NotFittedError
  from typing import Dict, List, Optional, Union
  from scipy.sparse import csr_matrix
  from sklearn.preprocessing import LabelEncoder
label_desc: Use image node_id 5 for calling a global function with example usage: convert_input(X, columns, deep, index) and returns: X