code: def floatify_dataframe(df: pd.DataFrame):
      """Return a dataframe where all the int columns are converted to floats.
  
      Parameters
      ----------
      df : pd.DataFrame
          dataframe to convert
  
      Raises
      ------
      pd.DataFrame
          the dataframe where all the int columns are converted to floats
      """
      dtype_dict = df.dtypes.to_dict()
      for col_name, dtype in dtype_dict.items():
          if is_integer_dtype(dtype):
              dtype_dict[col_name] = "float"
      return df.astype(dtype_dict)
  
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 3 for calling a global function with example usage: floatify_dataframe(df) and returns: df